From ad8dcbc8dfdae62e7e0dc36e0d991adf07cc06bb Mon Sep 17 00:00:00 2001
From: protections machine
 <72879786+protectionsmachine@users.noreply.github.com>
Date: Thu, 30 May 2024 18:27:56 +0200
Subject: [PATCH] [Detection Rules] Adding Documents for v8.11.17 Pre-Built
 Detection Rules (#5273)

---
 ...7-account-password-reset-remotely.asciidoc |   99 +
 ...-hidden-file-attribute-via-attrib.asciidoc |  151 ++
 ...e-8-11-17-adfind-command-activity.asciidoc |  169 ++
 ...-8-11-17-adobe-hijack-persistence.asciidoc |  157 ++
 ...tempt-to-clear-kernel-ring-buffer.asciidoc |  114 +
 ...credential-fetch-via-assumed-role.asciidoc |  123 +
 ...ion-lifecycle-configuration-added.asciidoc |  128 +
 ...ule-8-11-17-chkconfig-service-add.asciidoc |  202 ++
 ...dification-through-built-in-tools.asciidoc |  135 ++
 ...icy-modification-through-registry.asciidoc |  146 ++
 ...f-domain-backup-dpapi-private-key.asciidoc |  101 +
 ...ged-by-previously-unknown-process.asciidoc |  230 ++
 ...-11-17-delayed-execution-via-ping.asciidoc |  148 ++
 ...ting-backup-catalogs-with-wbadmin.asciidoc |  140 ++
 ...control-via-registry-modification.asciidoc |  182 ++
 ...s-over-https-enabled-via-registry.asciidoc |   91 +
 ...-rule-8-11-17-dynamic-linker-copy.asciidoc |  192 ++
 ...2-ami-shared-with-another-account.asciidoc |  117 +
 ...executable-stored-in-the-registry.asciidoc |   71 +
 ...ncrypting-files-with-winrar-or-7z.asciidoc |  153 ++
 ...ing-domain-trusts-via-dsquery-exe.asciidoc |  121 +
 ...ting-domain-trusts-via-nltest-exe.asciidoc |  126 +
 ...tion-command-spawned-via-wmiprvse.asciidoc |  137 ++
 ...le-masquerading-as-kernel-process.asciidoc |  110 +
 ...g-exchange-mailbox-via-powershell.asciidoc |  162 ++
 ...value-accessed-in-secrets-manager.asciidoc |  132 ++
 ...-17-first-time-seen-driver-loaded.asciidoc |  153 ++
 ...protected-branch-settings-changed.asciidoc |   63 +
 ...ocess-arguments-in-an-rdp-session.asciidoc |   83 +
 ...high-mean-of-rdp-session-duration.asciidoc |   83 +
 ...-variance-in-rdp-session-duration.asciidoc |   83 +
 ...security-group-ingress-rule-added.asciidoc |  124 +
 ...-rule-8-11-17-kirbi-file-creation.asciidoc |   67 +
 ...count-tokenfilter-policy-disabled.asciidoc |   91 +
 ...uest-predicted-to-be-a-dga-domain.asciidoc |  103 +
 ...with-a-high-dga-probability-score.asciidoc |  103 +
 ...redicted-to-be-malicious-activity.asciidoc |  102 +
 ...-high-malicious-probability-score.asciidoc |  103 +
 ...using-a-known-sunburst-dns-domain.asciidoc |  103 +
 ...rosoft-windows-defender-tampering.asciidoc |  171 ++
 ...mimikatz-memssp-log-file-detected.asciidoc |  140 ++
 ...cation-of-amsienable-registry-key.asciidoc |  162 ++
 ...ork-activity-detected-via-kworker.asciidoc |  124 +
 ...ted-by-previously-unknown-process.asciidoc |  220 ++
 ...8-11-17-new-systemd-timer-created.asciidoc |  187 ++
 ...tence-via-bits-job-notify-cmdline.asciidoc |   91 +
 ...ript-or-desktop-file-modification.asciidoc |  214 ++
 ...stence-via-scheduled-job-creation.asciidoc |   98 +
 ...-17-port-forwarding-rule-addition.asciidoc |  151 ++
 ...l-buffer-overflow-attack-detected.asciidoc |   86 +
 ...ty-to-an-unusual-destination-port.asciidoc |   83 +
 ...activity-to-an-unusual-ip-address.asciidoc |   83 +
 ...n-activity-to-an-unusual-iso-code.asciidoc |   83 +
 ...ion-activity-to-an-unusual-region.asciidoc |   83 +
 ...le-8-11-17-potential-dga-activity.asciidoc |   93 +
 ...ux-backdoor-user-account-creation.asciidoc |  168 ++
 ...-potential-network-sweep-detected.asciidoc |   75 +
 ...rsistence-through-init-d-detected.asciidoc |  189 ++
 ...rough-motd-file-creation-detected.asciidoc |  181 ++
 ...ence-through-run-control-detected.asciidoc |  184 ++
 ...h-count-of-readme-files-by-system.asciidoc |  125 +
 ...somware-note-file-dropped-via-smb.asciidoc |  136 ++
 ...remote-desktop-tunneling-detected.asciidoc |  147 ++
 ...potential-reverse-shell-via-child.asciidoc |  120 +
 ...e-8-11-17-potential-reverse-shell.asciidoc |  118 +
 ...17-potential-suspicious-file-edit.asciidoc |  112 +
 ...ell-script-block-logging-disabled.asciidoc |  135 ++
 ...pt-for-credentials-with-osascript.asciidoc |  111 +
 ...-by-unsigned-or-untrusted-process.asciidoc |  110 +
 ...istry-persistence-via-appcert-dll.asciidoc |  103 +
 ...r-query-log-configuration-deleted.asciidoc |  122 +
 ...ol-spawned-via-script-interpreter.asciidoc |  172 ++
 ...ged-by-previously-unknown-process.asciidoc |  185 ++
 ...s-disabling-services-via-registry.asciidoc |  113 +
 ...to-an-external-device-via-airdrop.asciidoc |   82 +
 ...-bytes-sent-to-an-external-device.asciidoc |   82 +
 ...connections-made-from-a-source-ip.asciidoc |   83 +
 ...nections-made-to-a-destination-ip.asciidoc |   83 +
 ...er-of-processes-in-an-rdp-session.asciidoc |   83 +
 ...17-spike-in-remote-file-transfers.asciidoc |   83 +
 ...authorized-keys-file-modification.asciidoc |  103 +
 ...-file-modified-inside-a-container.asciidoc |   85 +
 ...m-session-started-to-ec2-instance.asciidoc |  123 +
 ...ing-activity-with-high-confidence.asciidoc |   96 +
 ...el-detected-c2-beaconing-activity.asciidoc |   97 +
 ...us-antimalware-scan-interface-dll.asciidoc |  144 ++
 ...-endpoint-security-parent-process.asciidoc |  106 +
 ...e-creation-in-etc-for-persistence.asciidoc |  245 ++
 ...picious-file-creation-via-kworker.asciidoc |  193 ++
 ...7-suspicious-file-renamed-via-smb.asciidoc |  138 ++
 ...ous-macos-ms-office-child-process.asciidoc |  168 ++
 ...ft-365-mail-access-by-clientappid.asciidoc |  140 ++
 ...spicious-ms-outlook-child-process.asciidoc |  181 ++
 ...-by-previously-unknown-executable.asciidoc |  241 ++
 ...rocess-spawned-from-motd-detected.asciidoc |  201 ++
 ...creenconnect-client-child-process.asciidoc |   88 +
 ...rvice-was-installed-in-the-system.asciidoc |  134 ++
 ...web-browser-sensitive-file-access.asciidoc |  115 +
 ...suspicious-werfault-child-process.asciidoc |  117 +
 ...1-17-suspicious-which-enumeration.asciidoc |   68 +
 ...process-cluster-spawned-by-a-host.asciidoc |   83 +
 ...uster-spawned-by-a-parent-process.asciidoc |   85 +
 ...process-cluster-spawned-by-a-user.asciidoc |   85 +
 ...-17-suspicious-zoom-child-process.asciidoc |  146 ++
 ...-or-moved-to-suspicious-directory.asciidoc |  130 ++
 ...-11-17-system-shells-via-services.asciidoc |  147 ++
 ...started-by-unusual-parent-process.asciidoc |  217 ++
 ...es-deleted-via-unexpected-process.asciidoc |  164 ++
 ...ia-windows-directory-masquerading.asciidoc |  174 ++
 ...a-windows-firewall-snap-in-hijack.asciidoc |  177 ++
 ...ommon-registry-persistence-change.asciidoc |  142 ++
 ...e-8-11-17-untrusted-driver-loaded.asciidoc |  144 ++
 ...vity-from-a-windows-system-binary.asciidoc |  204 ++
 ...nusual-parent-process-for-cmd-exe.asciidoc |  106 +
 ...nusual-process-for-a-windows-host.asciidoc |  133 ++
 ...unusual-process-spawned-by-a-host.asciidoc |   85 +
 ...ocess-spawned-by-a-parent-process.asciidoc |   85 +
 ...unusual-process-spawned-by-a-user.asciidoc |   85 +
 ...riting-data-to-an-external-device.asciidoc |   82 +
 ...-17-unusual-remote-file-directory.asciidoc |   83 +
 ...-17-unusual-remote-file-extension.asciidoc |   83 +
 ...-8-11-17-unusual-remote-file-size.asciidoc |   83 +
 ...al-time-or-day-for-an-rdp-session.asciidoc |   83 +
 ...ess-child-of-common-web-processes.asciidoc |  192 ++
 ...isabled-via-registry-modification.asciidoc |  170 ++
 ...rpreter-executing-process-via-wmi.asciidoc |  114 +
 ...e-installed-via-an-unusual-client.asciidoc |   98 +
 .../prebuilt-rules-8-11-17-appendix.asciidoc  |  133 ++
 .../prebuilt-rules-8-11-17-summary.asciidoc   |  266 +++
 ...ebuilt-rules-downloadable-updates.asciidoc |    5 +
 .../prebuilt-rules-reference.asciidoc         | 2078 +++++++++--------
 .../prebuilt-rules/rule-desc-index.asciidoc   |    5 +
 .../account-password-reset-remotely.asciidoc  |    3 +-
 ...-hidden-file-attribute-via-attrib.asciidoc |   18 +-
 .../adfind-command-activity.asciidoc          |   10 +-
 .../adobe-hijack-persistence.asciidoc         |    4 +-
 ...tempt-to-clear-kernel-ring-buffer.asciidoc |   18 +-
 ...e-user-data-from-aws-ec2-instance.asciidoc |   67 +
 ...credential-fetch-via-assumed-role.asciidoc |    3 +-
 ...s-iam-login-profile-added-to-user.asciidoc |   18 +-
 ...ion-lifecycle-configuration-added.asciidoc |  128 +
 .../chkconfig-service-add.asciidoc            |    4 +-
 ...dification-through-built-in-tools.asciidoc |    6 +-
 ...icy-modification-through-registry.asciidoc |   14 +-
 ...f-domain-backup-dpapi-private-key.asciidoc |    4 +-
 ...ged-by-previously-unknown-process.asciidoc |   32 +-
 .../delayed-execution-via-ping.asciidoc       |   32 +-
 ...ting-backup-catalogs-with-wbadmin.asciidoc |   10 +-
 ...control-via-registry-modification.asciidoc |   10 +-
 ...s-over-https-enabled-via-registry.asciidoc |   10 +-
 .../rule-details/dynamic-linker-copy.asciidoc |    6 +-
 ...2-ami-shared-with-another-account.asciidoc |    3 +-
 ...executable-stored-in-the-registry.asciidoc |    4 +-
 ...ncrypting-files-with-winrar-or-7z.asciidoc |   10 +-
 ...ing-domain-trusts-via-dsquery-exe.asciidoc |   10 +-
 ...ting-domain-trusts-via-nltest-exe.asciidoc |   10 +-
 ...tion-command-spawned-via-wmiprvse.asciidoc |   26 +-
 ...le-masquerading-as-kernel-process.asciidoc |   10 +-
 ...g-exchange-mailbox-via-powershell.asciidoc |    6 +-
 ...ed-or-archived-into-common-format.asciidoc |   18 +-
 ...value-accessed-in-secrets-manager.asciidoc |    4 +-
 .../first-time-seen-driver-loaded.asciidoc    |    6 +-
 ...protected-branch-settings-changed.asciidoc |    4 +-
 ...ocess-arguments-in-an-rdp-session.asciidoc |   15 +-
 ...high-mean-of-rdp-session-duration.asciidoc |   15 +-
 ...-variance-in-rdp-session-duration.asciidoc |   15 +-
 ...security-group-ingress-rule-added.asciidoc |  124 +
 .../rule-details/kirbi-file-creation.asciidoc |    6 +-
 ...count-tokenfilter-policy-disabled.asciidoc |    7 +-
 ...uest-predicted-to-be-a-dga-domain.asciidoc |   35 +-
 ...with-a-high-dga-probability-score.asciidoc |   35 +-
 ...redicted-to-be-malicious-activity.asciidoc |   38 +-
 ...-high-malicious-probability-score.asciidoc |   38 +-
 ...using-a-known-sunburst-dns-domain.asciidoc |   35 +-
 ...rosoft-windows-defender-tampering.asciidoc |   10 +-
 ...mimikatz-memssp-log-file-detected.asciidoc |    4 +-
 ...cation-of-amsienable-registry-key.asciidoc |   10 +-
 ...ork-activity-detected-via-kworker.asciidoc |   10 +-
 ...ted-by-previously-unknown-process.asciidoc |    6 +-
 .../new-systemd-timer-created.asciidoc        |    6 +-
 ...tence-via-bits-job-notify-cmdline.asciidoc |    4 +-
 ...ript-or-desktop-file-modification.asciidoc |    6 +-
 ...stence-via-scheduled-job-creation.asciidoc |    4 +-
 .../port-forwarding-rule-addition.asciidoc    |    7 +-
 ...l-buffer-overflow-attack-detected.asciidoc |    4 +-
 ...ty-to-an-unusual-destination-port.asciidoc |   14 +-
 ...activity-to-an-unusual-ip-address.asciidoc |   14 +-
 ...n-activity-to-an-unusual-iso-code.asciidoc |   14 +-
 ...ion-activity-to-an-unusual-region.asciidoc |   14 +-
 .../potential-dga-activity.asciidoc           |   35 +-
 ...ux-backdoor-user-account-creation.asciidoc |    4 +-
 .../potential-network-sweep-detected.asciidoc |    4 +-
 ...andard-port-http-https-connection.asciidoc |   10 +-
 ...rsistence-through-init-d-detected.asciidoc |    4 +-
 ...rough-motd-file-creation-detected.asciidoc |    4 +-
 ...ence-through-run-control-detected.asciidoc |    4 +-
 ...h-count-of-readme-files-by-system.asciidoc |    4 +-
 ...somware-note-file-dropped-via-smb.asciidoc |   10 +-
 ...remote-desktop-tunneling-detected.asciidoc |    4 +-
 ...potential-reverse-shell-via-child.asciidoc |   15 +-
 .../potential-reverse-shell.asciidoc          |   15 +-
 .../potential-suspicious-file-edit.asciidoc   |   20 +-
 ...ell-script-block-logging-disabled.asciidoc |   10 +-
 ...pt-for-credentials-with-osascript.asciidoc |    4 +-
 ...-by-unsigned-or-untrusted-process.asciidoc |    4 +-
 ...istry-persistence-via-appcert-dll.asciidoc |    7 +-
 ...r-query-log-configuration-deleted.asciidoc |    3 +-
 ...ol-spawned-via-script-interpreter.asciidoc |   10 +-
 ...ged-by-previously-unknown-process.asciidoc |    4 +-
 ...s-disabling-services-via-registry.asciidoc |   10 +-
 ...to-an-external-device-via-airdrop.asciidoc |   14 +-
 ...-bytes-sent-to-an-external-device.asciidoc |   14 +-
 ...connections-made-from-a-source-ip.asciidoc |   15 +-
 ...nections-made-to-a-destination-ip.asciidoc |   15 +-
 ...er-of-processes-in-an-rdp-session.asciidoc |   15 +-
 .../spike-in-remote-file-transfers.asciidoc   |   14 +-
 ...authorized-keys-file-modification.asciidoc |   18 +-
 ...-file-modified-inside-a-container.asciidoc |   18 +-
 ...m-session-started-to-ec2-instance.asciidoc |  123 +
 ...ing-activity-with-high-confidence.asciidoc |    4 +-
 ...el-detected-c2-beaconing-activity.asciidoc |    4 +-
 ...us-antimalware-scan-interface-dll.asciidoc |    4 +-
 ...-endpoint-security-parent-process.asciidoc |    3 +-
 ...e-creation-in-etc-for-persistence.asciidoc |   22 +-
 ...picious-file-creation-via-kworker.asciidoc |   13 +-
 .../suspicious-file-renamed-via-smb.asciidoc  |   10 +-
 ...ous-macos-ms-office-child-process.asciidoc |    4 +-
 ...ft-365-mail-access-by-clientappid.asciidoc |   73 +-
 ...spicious-ms-outlook-child-process.asciidoc |    4 +-
 ...-by-previously-unknown-executable.asciidoc |   10 +-
 ...rocess-spawned-from-motd-detected.asciidoc |    8 +-
 ...creenconnect-client-child-process.asciidoc |    6 +-
 ...rvice-was-installed-in-the-system.asciidoc |    6 +-
 ...web-browser-sensitive-file-access.asciidoc |    6 +-
 ...suspicious-werfault-child-process.asciidoc |   12 +-
 .../suspicious-which-enumeration.asciidoc     |    4 +-
 ...process-cluster-spawned-by-a-host.asciidoc |   47 +-
 ...uster-spawned-by-a-parent-process.asciidoc |   47 +-
 ...process-cluster-spawned-by-a-user.asciidoc |   47 +-
 .../suspicious-zoom-child-process.asciidoc    |    4 +-
 ...-or-moved-to-suspicious-directory.asciidoc |   10 +-
 .../system-shells-via-services.asciidoc       |    4 +-
 ...started-by-unusual-parent-process.asciidoc |  217 ++
 ...es-deleted-via-unexpected-process.asciidoc |   10 +-
 ...ia-windows-directory-masquerading.asciidoc |   18 +-
 ...a-windows-firewall-snap-in-hijack.asciidoc |   18 +-
 ...ommon-registry-persistence-change.asciidoc |   18 +-
 ...igned-bits-service-client-process.asciidoc |   10 +-
 .../untrusted-driver-loaded.asciidoc          |    6 +-
 ...vity-from-a-windows-system-binary.asciidoc |   18 +-
 ...nusual-parent-process-for-cmd-exe.asciidoc |    4 +-
 ...nusual-process-for-a-windows-host.asciidoc |    6 +-
 ...unusual-process-spawned-by-a-host.asciidoc |   47 +-
 ...ocess-spawned-by-a-parent-process.asciidoc |   47 +-
 ...unusual-process-spawned-by-a-user.asciidoc |   47 +-
 ...riting-data-to-an-external-device.asciidoc |   14 +-
 .../unusual-remote-file-directory.asciidoc    |   14 +-
 .../unusual-remote-file-extension.asciidoc    |   14 +-
 .../unusual-remote-file-size.asciidoc         |   14 +-
 ...al-time-or-day-for-an-rdp-session.asciidoc |   15 +-
 ...ess-child-of-common-web-processes.asciidoc |    6 +-
 ...indows-account-or-group-discovery.asciidoc |   10 +-
 ...isabled-via-registry-modification.asciidoc |   10 +-
 ...rpreter-executing-process-via-wmi.asciidoc |   10 +-
 docs/index.asciidoc                           |    2 +
 265 files changed, 18962 insertions(+), 2113 deletions(-)
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-account-password-reset-remotely.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adding-hidden-file-attribute-via-attrib.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adfind-command-activity.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adobe-hijack-persistence.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-attempt-to-clear-kernel-ring-buffer.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-aws-ec2-admin-credential-fetch-via-assumed-role.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-chkconfig-service-add.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-code-signing-policy-modification-through-built-in-tools.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-code-signing-policy-modification-through-registry.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-creation-or-modification-of-domain-backup-dpapi-private-key.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-cron-job-created-or-changed-by-previously-unknown-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-delayed-execution-via-ping.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-deleting-backup-catalogs-with-wbadmin.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-disabling-user-account-control-via-registry-modification.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-dns-over-https-enabled-via-registry.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-dynamic-linker-copy.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ec2-ami-shared-with-another-account.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-encoded-executable-stored-in-the-registry.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-encrypting-files-with-winrar-or-7z.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumerating-domain-trusts-via-dsquery-exe.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumerating-domain-trusts-via-nltest-exe.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumeration-command-spawned-via-wmiprvse.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-executable-masquerading-as-kernel-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-exporting-exchange-mailbox-via-powershell.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-first-time-seen-aws-secret-value-accessed-in-secrets-manager.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-first-time-seen-driver-loaded.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-github-protected-branch-settings-changed.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-mean-of-process-arguments-in-an-rdp-session.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-mean-of-rdp-session-duration.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-variance-in-rdp-session-duration.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-kirbi-file-creation.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-local-account-tokenfilter-policy-disabled.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-with-a-high-dga-probability-score.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-microsoft-windows-defender-tampering.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-mimikatz-memssp-log-file-detected.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-modification-of-amsienable-registry-key.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-network-activity-detected-via-kworker.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-new-systemd-service-created-by-previously-unknown-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-new-systemd-timer-created.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-bits-job-notify-cmdline.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-kde-autostart-script-or-desktop-file-modification.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-scheduled-job-creation.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-port-forwarding-rule-addition.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-buffer-overflow-attack-detected.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-destination-port.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-ip-address.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-iso-code.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-region.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-dga-activity.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-linux-backdoor-user-account-creation.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-network-sweep-detected.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-init-d-detected.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-motd-file-creation-detected.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-run-control-detected.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-ransomware-behavior-high-count-of-readme-files-by-system.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-ransomware-note-file-dropped-via-smb.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-remote-desktop-tunneling-detected.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-reverse-shell-via-child.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-reverse-shell.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-suspicious-file-edit.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-powershell-script-block-logging-disabled.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-prompt-for-credentials-with-osascript.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-quarantine-attrib-removed-by-unsigned-or-untrusted-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-registry-persistence-via-appcert-dll.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-route53-resolver-query-log-configuration-deleted.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-service-control-spawned-via-script-interpreter.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-shared-object-created-or-changed-by-previously-unknown-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-solarwinds-process-disabling-services-via-registry.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device-via-airdrop.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-connections-made-from-a-source-ip.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-connections-made-to-a-destination-ip.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-processes-in-an-rdp-session.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-remote-file-transfers.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssh-authorized-keys-file-modification.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssh-authorized-keys-file-modified-inside-a-container.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssm-session-started-to-ec2-instance.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity-with-high-confidence.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-antimalware-scan-interface-dll.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-endpoint-security-parent-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-creation-in-etc-for-persistence.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-creation-via-kworker.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-renamed-via-smb.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-macos-ms-office-child-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-microsoft-365-mail-access-by-clientappid.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-ms-outlook-child-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-network-activity-to-the-internet-by-previously-unknown-executable.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-process-spawned-from-motd-detected.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-screenconnect-client-child-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-service-was-installed-in-the-system.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-web-browser-sensitive-file-access.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-werfault-child-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-which-enumeration.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-host.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-parent-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-user.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-zoom-child-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-system-binary-copied-and-or-moved-to-suspicious-directory.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-system-shells-via-services.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-systemd-service-started-by-unusual-parent-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-third-party-backup-files-deleted-via-unexpected-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uac-bypass-attempt-via-windows-directory-masquerading.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uac-bypass-via-windows-firewall-snap-in-hijack.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uncommon-registry-persistence-change.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-untrusted-driver-loaded.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-network-activity-from-a-windows-system-binary.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-parent-process-for-cmd-exe.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-for-a-windows-host.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-host.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-parent-process.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-user.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-writing-data-to-an-external-device.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-directory.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-extension.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-size.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-time-or-day-for-an-rdp-session.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-web-shell-detection-script-process-child-of-common-web-processes.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-defender-disabled-via-registry-modification.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-script-interpreter-executing-process-via-wmi.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-service-installed-via-an-unusual-client.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rules-8-11-17-appendix.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rules-8-11-17-summary.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/rule-details/attempt-to-retrieve-user-data-from-aws-ec2-instance.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/rule-details/aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/rule-details/insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/rule-details/ssm-session-started-to-ec2-instance.asciidoc
 create mode 100644 docs/detections/prebuilt-rules/rule-details/systemd-service-started-by-unusual-parent-process.asciidoc

diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-account-password-reset-remotely.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-account-password-reset-remotely.asciidoc
new file mode 100644
index 0000000000..84b06a6311
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-account-password-reset-remotely.asciidoc
@@ -0,0 +1,99 @@
+[[prebuilt-rule-8-11-17-account-password-reset-remotely]]
+=== Account Password Reset Remotely
+
+Identifies an attempt to reset a potentially privileged account password remotely. Adversaries may manipulate account passwords to maintain access or evade password duration policies and preserve compromised credentials.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-system.security*
+* logs-windows.forwarded*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.microsoft.com/en-us/windows/security/threat-protection/auditing/event-4724
+* https://stealthbits.com/blog/manipulating-user-passwords-with-mimikatz/
+* https://github.com/sbousseaden/EVTX-ATTACK-SAMPLES/blob/master/Credential%20Access/remote_pwd_reset_rpc_mimikatz_postzerologon_target_DC.evtx
+* https://www.elastic.co/security-labs/detect-credential-access
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Impact
+
+*Version*: 115
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Performance*
+
+This rule may cause medium to high performance impact due to logic scoping all remote Windows logon activity.
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by winlog.computer_name with maxspan=1m
+  [authentication where event.action == "logged-in" and
+    /* event 4624 need to be logged */
+    winlog.logon.type : "Network" and event.outcome == "success" and source.ip != null and
+    source.ip != "127.0.0.1" and source.ip != "::1" and
+    not winlog.event_data.TargetUserName : ("svc*", "PIM_*", "_*_", "*-*-*", "*$")] by winlog.event_data.TargetLogonId
+   /* event 4724 need to be logged */
+  [iam where event.action == "reset-password" and
+   (
+    /*
+       This rule is very noisy if not scoped to privileged accounts, duplicate the
+       rule and add your own naming convention and accounts of interest here.
+     */
+    winlog.event_data.TargetUserName: ("*Admin*", "*super*", "*SVC*", "*DC0*", "*service*", "*DMZ*", "*ADM*") or
+    winlog.event_data.TargetSid : ("S-1-5-21-*-500", "S-1-12-1-*-500")
+    )
+  ] by winlog.event_data.SubjectLogonId
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Account Manipulation
+** ID: T1098
+** Reference URL: https://attack.mitre.org/techniques/T1098/
+* Tactic:
+** Name: Impact
+** ID: TA0040
+** Reference URL: https://attack.mitre.org/tactics/TA0040/
+* Technique:
+** Name: Account Access Removal
+** ID: T1531
+** Reference URL: https://attack.mitre.org/techniques/T1531/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adding-hidden-file-attribute-via-attrib.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adding-hidden-file-attribute-via-attrib.asciidoc
new file mode 100644
index 0000000000..032a12a498
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adding-hidden-file-attribute-via-attrib.asciidoc
@@ -0,0 +1,151 @@
+[[prebuilt-rule-8-11-17-adding-hidden-file-attribute-via-attrib]]
+=== Adding Hidden File Attribute via Attrib
+
+Adversaries can add the 'hidden' attribute to files to hide them from the user in an attempt to evade detection.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Adding Hidden File Attribute via Attrib*
+
+
+The `Hidden` attribute is a file or folder attribute that makes the file or folder invisible to regular directory listings when the attribute is set. 
+
+Attackers can use this attribute to conceal tooling and malware to prevent administrators and users from finding it, even if they are looking specifically for it.
+
+This rule looks for the execution of the `attrib.exe` utility with a command line that indicates the modification of the `Hidden` attribute.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Examine the command line to identify the target file or folder.
+  - Examine the file, which process created it, header, etc.
+  - If suspicious, retrieve the files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Examine the host for derived artifacts that indicate suspicious activities:
+  - Observe and collect information about the following activities in the alert subject host:
+    - Attempts to contact external domains and addresses.
+      - Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' `process.entity_id`.
+      - Examine the DNS cache for suspicious or anomalous entries.
+        - !{osquery{"label":"Osquery - Retrieve DNS Cache","query":"SELECT * FROM dns_cache"}}
+    - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
+    - Examine the host services for suspicious or anomalous entries.
+      - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+      - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  (process.name : "attrib.exe" or ?process.pe.original_file_name == "ATTRIB.EXE") and process.args : "+h" and
+  not (process.parent.name: "cmd.exe" and process.command_line: "attrib  +R +H +S +A *.cui")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: File and Directory Permissions Modification
+** ID: T1222
+** Reference URL: https://attack.mitre.org/techniques/T1222/
+* Sub-technique:
+** Name: Windows File and Directory Permissions Modification
+** ID: T1222.001
+** Reference URL: https://attack.mitre.org/techniques/T1222/001/
+* Technique:
+** Name: Hide Artifacts
+** ID: T1564
+** Reference URL: https://attack.mitre.org/techniques/T1564/
+* Sub-technique:
+** Name: Hidden Files and Directories
+** ID: T1564.001
+** Reference URL: https://attack.mitre.org/techniques/T1564/001/
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adfind-command-activity.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adfind-command-activity.asciidoc
new file mode 100644
index 0000000000..0991bf5dbb
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adfind-command-activity.asciidoc
@@ -0,0 +1,169 @@
+[[prebuilt-rule-8-11-17-adfind-command-activity]]
+=== AdFind Command Activity
+
+This rule detects the Active Directory query tool, AdFind.exe. AdFind has legitimate purposes, but it is frequently leveraged by threat actors to perform post-exploitation Active Directory reconnaissance. The AdFind tool has been observed in Trickbot, Ryuk, Maze, and FIN6 campaigns. For Winlogbeat, this rule requires Sysmon.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.process-*
+* winlogbeat-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* http://www.joeware.net/freetools/tools/adfind/
+* https://thedfirreport.com/2020/05/08/adfind-recon/
+* https://www.fireeye.com/blog/threat-research/2020/05/tactics-techniques-procedures-associated-with-maze-ransomware-incidents.html
+* https://www.cybereason.com/blog/dropping-anchor-from-a-trickbot-infection-to-the-discovery-of-the-anchor-malware
+* https://www.fireeye.com/blog/threat-research/2019/04/pick-six-intercepting-a-fin6-intrusion.html
+* https://usa.visa.com/dam/VCOM/global/support-legal/documents/fin6-cybercrime-group-expands-threat-To-ecommerce-merchants.pdf
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Discovery
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating AdFind Command Activity*
+
+
+http://www.joeware.net/freetools/tools/adfind/[AdFind] is a freely available command-line tool used to retrieve information from Active Directory (AD). Network discovery and enumeration tools like `AdFind` are useful to adversaries in the same ways they are effective for network administrators. This tool provides quick ability to scope AD person/computer objects and understand subnets and domain information. There are many https://thedfirreport.com/category/adfind/[examples] of this tool being adopted by ransomware and criminal groups and used in compromises.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Examine the command line to determine what information was retrieved by the tool.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+
+
+*False positive analysis*
+
+
+- This rule has a high chance to produce false positives as it is a legitimate tool used by network administrators.
+- If this rule is noisy in your environment due to expected activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- Malicious behavior with `AdFind` should be investigated as part of a step within an attack chain. It doesn't happen in isolation, so reviewing previous logs/activity from impacted machines can be very telling.
+
+
+*Related rules*
+
+
+- Windows Network Enumeration - 7b8bfc26-81d2-435e-965c-d722ee397ef1
+- Enumeration of Administrator Accounts - 871ea072-1b71-4def-b016-6278b505138d
+- Enumeration Command Spawned via WMIPrvSE - 770e0c4d-b998-41e5-a62e-c7901fd7f470
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  (process.name : "AdFind.exe" or ?process.pe.original_file_name == "AdFind.exe") and
+  process.args : ("objectcategory=computer", "(objectcategory=computer)",
+                  "objectcategory=person", "(objectcategory=person)",
+                  "objectcategory=subnet", "(objectcategory=subnet)",
+                  "objectcategory=group", "(objectcategory=group)",
+                  "objectcategory=organizationalunit", "(objectcategory=organizationalunit)",
+                  "objectcategory=attributeschema", "(objectcategory=attributeschema)",
+                  "domainlist", "dcmodes", "adinfo", "dclist", "computers_pwnotreqd", "trustdmp")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Discovery
+** ID: TA0007
+** Reference URL: https://attack.mitre.org/tactics/TA0007/
+* Technique:
+** Name: System Network Configuration Discovery
+** ID: T1016
+** Reference URL: https://attack.mitre.org/techniques/T1016/
+* Technique:
+** Name: Remote System Discovery
+** ID: T1018
+** Reference URL: https://attack.mitre.org/techniques/T1018/
+* Technique:
+** Name: Permission Groups Discovery
+** ID: T1069
+** Reference URL: https://attack.mitre.org/techniques/T1069/
+* Sub-technique:
+** Name: Domain Groups
+** ID: T1069.002
+** Reference URL: https://attack.mitre.org/techniques/T1069/002/
+* Technique:
+** Name: Account Discovery
+** ID: T1087
+** Reference URL: https://attack.mitre.org/techniques/T1087/
+* Sub-technique:
+** Name: Domain Account
+** ID: T1087.002
+** Reference URL: https://attack.mitre.org/techniques/T1087/002/
+* Technique:
+** Name: Domain Trust Discovery
+** ID: T1482
+** Reference URL: https://attack.mitre.org/techniques/T1482/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adobe-hijack-persistence.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adobe-hijack-persistence.asciidoc
new file mode 100644
index 0000000000..c58747ee52
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-adobe-hijack-persistence.asciidoc
@@ -0,0 +1,157 @@
+[[prebuilt-rule-8-11-17-adobe-hijack-persistence]]
+=== Adobe Hijack Persistence
+
+Detects writing executable files that will be automatically launched by Adobe on launch.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.file-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://twitter.com/pabraeken/status/997997818362155008
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 213
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Adobe Hijack Persistence*
+
+
+Attackers can replace the `RdrCEF.exe` executable with their own to maintain their access, which will be launched whenever Adobe Acrobat Reader is executed.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+- Examine the host for derived artifacts that indicate suspicious activities:
+  - Analyze the file using a private sandboxed analysis system.
+  - Observe and collect information about the following activities in both the sandbox and the alert subject host:
+    - Attempts to contact external domains and addresses.
+      - Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' `process.entity_id`.
+      - Examine the DNS cache for suspicious or anomalous entries.
+        - !{osquery{"label":"Osquery - Retrieve DNS Cache","query":"SELECT * FROM dns_cache"}}
+    - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
+    - Examine the host services for suspicious or anomalous entries.
+      - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+      - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+  - Retrieve the files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Investigate potentially compromised accounts. Analysts can do this by searching for login events (for example, 4624) to the target host after the registry modification.
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "windows" and event.type == "creation" and
+  file.path : ("?:\\Program Files (x86)\\Adobe\\Acrobat Reader DC\\Reader\\AcroCEF\\RdrCEF.exe",
+               "?:\\Program Files\\Adobe\\Acrobat Reader DC\\Reader\\AcroCEF\\RdrCEF.exe") and
+  not process.name : "msiexec.exe"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Hijack Execution Flow
+** ID: T1574
+** Reference URL: https://attack.mitre.org/techniques/T1574/
+* Sub-technique:
+** Name: Services File Permissions Weakness
+** ID: T1574.010
+** Reference URL: https://attack.mitre.org/techniques/T1574/010/
+* Technique:
+** Name: Compromise Client Software Binary
+** ID: T1554
+** Reference URL: https://attack.mitre.org/techniques/T1554/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-attempt-to-clear-kernel-ring-buffer.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-attempt-to-clear-kernel-ring-buffer.asciidoc
new file mode 100644
index 0000000000..ef626ca4c5
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-attempt-to-clear-kernel-ring-buffer.asciidoc
@@ -0,0 +1,114 @@
+[[prebuilt-rule-8-11-17-attempt-to-clear-kernel-ring-buffer]]
+=== Attempt to Clear Kernel Ring Buffer
+
+Monitors for the deletion of the kernel ring buffer events through dmesg. Attackers may clear kernel ring buffer events to evade detection after installing a Linux kernel module (LKM).
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+* auditbeat-*
+* logs-auditd_manager.auditd-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Defend
+* Data Source: Elastic Endgame
+* Data Source: Auditd Manager
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "linux" and event.type == "start" and event.action in ("exec", "exec_event", "executed", "process_started")
+ and process.name == "dmesg" and process.args == "-c"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Indicator Removal
+** ID: T1070
+** Reference URL: https://attack.mitre.org/techniques/T1070/
+* Sub-technique:
+** Name: Clear Linux or Mac System Logs
+** ID: T1070.002
+** Reference URL: https://attack.mitre.org/techniques/T1070/002/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Tools
+** ID: T1562.001
+** Reference URL: https://attack.mitre.org/techniques/T1562/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-aws-ec2-admin-credential-fetch-via-assumed-role.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-aws-ec2-admin-credential-fetch-via-assumed-role.asciidoc
new file mode 100644
index 0000000000..355d312a64
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-aws-ec2-admin-credential-fetch-via-assumed-role.asciidoc
@@ -0,0 +1,123 @@
+[[prebuilt-rule-8-11-17-aws-ec2-admin-credential-fetch-via-assumed-role]]
+=== AWS EC2 Admin Credential Fetch via Assumed Role
+
+Identifies the first occurrence of a user identity in AWS using `GetPassword` for the administrator password of an EC2 instance with an assumed role. Adversaries may use this API call to escalate privileges or move laterally within EC2 instances.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://cloud.hacktricks.xyz/pentesting-cloud/aws-security/aws-privilege-escalation/aws-ec2-privesc
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: Amazon EC2
+* Use Case: Identity and Access Audit
+* Resources: Investigation Guide
+* Tactic: Credential Access
+
+*Version*: 3
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and Analysis*
+
+
+
+*Investigating AWS EC2 Admin Credential Fetch via Assumed Role*
+
+
+This rule detects the first occurrence of a user identity using the `GetPasswordData` API call in AWS, which retrieves the administrator password of an EC2 instance. This can be an indicator of an adversary attempting to escalate privileges or move laterally within EC2 instances.
+
+This is a New Terms rule, which means it will only trigger once for each unique value of the `aws.cloudtrail.user_identity.session_context.session_issuer.arn` field that has not been seen making this API request within the last 7 days. This field contains the Amazon Resource Name (ARN) of the assumed role that triggered the API call.
+
+
+*Possible Investigation Steps*
+
+
+- **Identify the User Identity and Role**: Examine the AWS CloudTrail logs to determine the user identity that made the `GetPasswordData` request. Pay special attention to the role and permissions associated with the user.
+- **Review Request and Response Parameters**: Analyze the `aws.cloudtrail.request_parameters` and `aws.cloudtrail.response_elements` fields to understand the context of the API call and the retrieved password.
+- **Contextualize with User Behavior**: Compare this activity against the user's typical behavior patterns. Look for unusual login times, IP addresses, or other anomalous actions taken by the user or role prior to and following the incident.
+- **Review EC2 Instance Details**: Check the details of the EC2 instance from which the password was retrieved. Assess the criticality and sensitivity of the applications running on this instance.
+- **Examine Related CloudTrail Events**: Search for other API calls made by the same user identity, especially those modifying security groups, network access controls, or instance metadata.
+- **Check for Lateral Movement**: Look for evidence that the obtained credentials have been used to access other resources or services within AWS.
+- **Investigate the Origin of the API Call**: Analyze the IP address and geographical location from which the request originated. Determine if it aligns with expected locations for legitimate administrative activity.
+
+
+*False Positive Analysis*
+
+
+- **Legitimate Administrative Actions**: Ensure that the activity was not part of legitimate administrative tasks such as system maintenance or updates.
+- **Automation Scripts**: Verify if the activity was generated by automation or deployment scripts that are authorized to use `GetPasswordData` for legitimate purposes.
+
+
+*Response and Remediation*
+
+
+- **Immediate Isolation**: If suspicious, isolate the affected instance to prevent any potential lateral movement or further unauthorized actions.
+- **Credential Rotation**: Rotate credentials of the affected instance or assumed role and any other potentially compromised credentials.
+- **User Account Review**: Review the permissions of the implicated user identity. Apply the principle of least privilege by adjusting permissions to prevent misuse.
+- **Enhanced Monitoring**: Increase monitoring on the user identity that triggered the rule and similar EC2 instances.
+- **Incident Response**: If malicious intent is confirmed, initiate the incident response protocol. This includes further investigation, containment of the threat, eradication of any threat actor presence, and recovery of affected systems.
+- **Preventative Measures**: Implement or enhance security measures such as multi-factor authentication and continuous audits of sensitive operations like `GetPasswordData`.
+
+
+*Additional Information*
+
+
+Refer to resources like https://cloud.hacktricks.xyz/pentesting-cloud/aws-security/aws-privilege-escalation/aws-ec2-privesc[AWS privilege escalation methods] and the MITRE ATT&CK technique https://attack.mitre.org/techniques/T1552/005/[T1552.005 - Cloud Instance Metadata API] for more details on potential vulnerabilities and mitigation strategies.
+
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset:"aws.cloudtrail"
+    and event.provider:"ec2.amazonaws.com" and event.action:"GetPasswordData"
+    and aws.cloudtrail.user_identity.type:"AssumedRole" and aws.cloudtrail.error_code:"Client.UnauthorizedOperation"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Credential Access
+** ID: TA0006
+** Reference URL: https://attack.mitre.org/tactics/TA0006/
+* Technique:
+** Name: Unsecured Credentials
+** ID: T1552
+** Reference URL: https://attack.mitre.org/techniques/T1552/
+* Sub-technique:
+** Name: Cloud Instance Metadata API
+** ID: T1552.005
+** Reference URL: https://attack.mitre.org/techniques/T1552/005/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc
new file mode 100644
index 0000000000..fb411ee28b
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc
@@ -0,0 +1,128 @@
+[[prebuilt-rule-8-11-17-aws-s3-bucket-expiration-lifecycle-configuration-added]]
+=== AWS S3 Bucket Expiration Lifecycle Configuration Added
+
+Identifies an expiration lifecycle configuration added to an S3 bucket. Lifecycle configurations can be used to manage objects in a bucket, including setting expiration policies. This rule detects when a lifecycle configuration is added to an S3 bucket, which could indicate that objects in the bucket will be automatically deleted after a specified period of time. This could be used to evade detection by deleting objects that contain evidence of malicious activity.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 10m
+
+*Searches indices from*: now-60m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/AmazonS3/latest/userguide/lifecycle-expire-general-considerations.html
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: Amazon S3
+* Use Case: Asset Visibility
+* Tactic: Defense Evasion
+
+*Version*: 1
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+
+*Triage and Analysis*
+
+
+
+*Investigating AWS S3 Bucket Expiration Lifecycle Configuration Added*
+
+
+This rule detects when an expiration lifecycle configuration is added to an S3 bucket in AWS. Such configurations can automate the deletion of objects within a bucket after a specified period, potentially obfuscating evidence of unauthorized access or malicious activity by automatically removing logs or other data.
+
+
+*Detailed Investigation Steps*
+
+
+- **Review the Affected S3 Bucket**: Check the bucket details (`bucketName`) where the lifecycle configuration has been added.
+    - Determine the contents and importance of the data stored in this bucket to assess the impact of the lifecycle policy.
+- **Analyze the Lifecycle Configuration**:
+  - **Expiration Policy**: Note the `Days` parameter under `Expiration` in the lifecycle rule. This indicates how long after creation data will remain in the bucket before being automatically deleted.
+  - **Rule ID and Status**: Review the `ID` and `Status` of the lifecycle rule to understand its operational scope and activation status.
+- **User Identity and Activity**:
+  - **User Details**: Investigate the user (`user_identity.arn`) who made the change. Determine whether this user's role typically involves managing S3 bucket configurations.
+  - **Authentication Details**: Examine the authentication method and whether the access key used (`access_key_id`) is routinely used for such configurations or if it has deviated from normal usage patterns.
+- **Source IP and User Agent**:
+  - **Source IP Address**: The IP address (`source.ip`) from which the request was made can provide clues about the geographical location of the requester. Determine if this location aligns with the user’s known locations.
+  - **User Agent**: Analyze the user agent string to understand the type of client or service that made the request, which can help identify scripted automation versus manual changes.
+
+
+*Possible Indicators of Compromise or Misuse*
+
+
+- **Frequent Changes**: Look for frequent modifications to lifecycle policies in the same or multiple buckets, which can indicate attempts to manipulate data retention dynamically.
+- **Unusual User Activity**: Activities that do not correlate with the user's typical behavior patterns, such as making changes during odd hours or from unusual locations, should be flagged for further investigation.
+
+
+*False Positive Analysis*
+
+
+- Verify the operational requirements that might necessitate such lifecycle policies, especially in environments where data retention policies are strictly governed for compliance and cost-saving reasons.
+
+
+*Response and Remediation*
+
+
+- **Immediate Review**: If the change was unauthorized, consider reverting the lifecycle configuration change immediately to prevent potential data loss.
+- **Enhance Monitoring**: Implement monitoring to alert on changes to lifecycle configurations across your S3 environments.
+- **User Education**: Ensure that users with access to critical resources like S3 buckets are aware of the best practices and company policies regarding data retention and security.
+
+
+*Additional Information*
+
+
+For further guidance on managing S3 lifecycle policies and ensuring compliance with organizational data retention and security policies, refer to the AWS official documentation on https://docs.aws.amazon.com/AmazonS3/latest/userguide/lifecycle-expire-general-considerations.html[S3 Lifecycle Configuration].
+
+
+==== Setup
+
+
+This rule requires S3 data events to be logged to CloudTrail. CloudTrail trails can be configured to log S3 data events in the AWS Management Console or using the AWS CLI.
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset: "aws.cloudtrail" and event.provider: "s3.amazonaws.com" and
+    event.action: PutBucketLifecycle and event.outcome: success and
+    aws.cloudtrail.request_parameters: (*LifecycleConfiguration* and *Expiration=*)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Indicator Removal
+** ID: T1070
+** Reference URL: https://attack.mitre.org/techniques/T1070/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-chkconfig-service-add.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-chkconfig-service-add.asciidoc
new file mode 100644
index 0000000000..dca88a3902
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-chkconfig-service-add.asciidoc
@@ -0,0 +1,202 @@
+[[prebuilt-rule-8-11-17-chkconfig-service-add]]
+=== Chkconfig Service Add
+
+Detects the use of the chkconfig binary to manually add a service for management by chkconfig. Threat actors may utilize this technique to maintain persistence on a system. When a new service is added, chkconfig ensures that the service has either a start or a kill entry in every runlevel and when the system is rebooted the service file added will run providing long-term persistence.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.intezer.com/blog/research/lightning-framework-new-linux-threat/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Threat: Lightning Framework
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Chkconfig Service Add*
+
+Service files are configuration files in Linux systems used to define and manage system services. The `Chkconfig` binary can be used to manually add, delete or modify a service. 
+
+Malicious actors can leverage services to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection.
+
+This rule monitors the usage of the `chkconfig` binary to manually add a service for management by `chkconfig`, potentially indicating the creation of a persistence mechanism.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the service that was created or modified.
+- Investigate the currently enabled system services through the following commands `sudo chkconfig --list | grep on` and `sudo systemctl list-unit-files`.
+- Investigate the status of potentially suspicious services through the `chkconfig --list service_name` command. 
+- Search for the `rc.d` or `init.d` service files that were created or modified, and analyze their contents.
+- Investigate whether any other files in any of the available `rc.d` or `init.d` directories have been altered through OSQuery.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (path LIKE '/etc/init.d/%' OR path LIKE '/etc/rc%.d/%')"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE (path LIKE '/etc/init.d/%' OR path LIKE\n'/etc/rc%.d/%')\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate syslog through the `sudo cat /var/log/syslog | grep 'LSB'` command to find traces of the LSB header of the script (if present). If syslog is being ingested into Elasticsearch, the same can be accomplished through Kibana.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator who uses the `chkconfig` binary for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- Suspicious File Creation in /etc for Persistence - 1c84dd64-7e6c-4bad-ac73-a5014ee37042
+- Potential Persistence Through Run Control Detected - 0f4d35e4-925e-4959-ab24-911be207ee6f
+- Potential Persistence Through init.d Detected - 474fd20e-14cc-49c5-8160-d9ab4ba16c8b
+- New Systemd Timer Created - 7fb500fa-8e24-4bd1-9480-2a819352602c
+- New Systemd Service Created by Previously Unknown Process - 17b0a495-4d9f-414c-8ad0-92f018b8e001
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service/timer or restore its original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "linux" and event.action in ("exec", "exec_event") and
+( 
+  (process.executable : "/usr/sbin/chkconfig" and process.args : "--add") or
+  (process.args : "*chkconfig" and process.args : "--add")
+) and 
+not process.parent.name in ("rpm", "qualys-scan-util", "qualys-cloud-agent", "update-alternatives") and
+not process.parent.args : ("/var/tmp/rpm*", "/var/lib/waagent/*")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Boot or Logon Initialization Scripts
+** ID: T1037
+** Reference URL: https://attack.mitre.org/techniques/T1037/
+* Sub-technique:
+** Name: RC Scripts
+** ID: T1037.004
+** Reference URL: https://attack.mitre.org/techniques/T1037/004/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-code-signing-policy-modification-through-built-in-tools.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-code-signing-policy-modification-through-built-in-tools.asciidoc
new file mode 100644
index 0000000000..ebae0f75f7
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-code-signing-policy-modification-through-built-in-tools.asciidoc
@@ -0,0 +1,135 @@
+[[prebuilt-rule-8-11-17-code-signing-policy-modification-through-built-in-tools]]
+=== Code Signing Policy Modification Through Built-in tools
+
+Identifies attempts to disable/modify the code signing policy through system native utilities. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 8
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Code Signing Policy Modification Through Built-in tools*
+
+
+Windows Driver Signature Enforcement (DSE) is a security feature introduced by Microsoft to enforce that only signed drivers can be loaded and executed into the kernel (ring 0). This feature was introduced to prevent attackers from loading their malicious drivers on targets. If the driver has an invalid signature, the system will not allow it to be loaded.
+
+This protection is essential for maintaining the security of the system. However, attackers or even administrators can disable this feature and load untrusted drivers, as this can put the system at risk. Therefore, it is important to keep this feature enabled and only load drivers from trusted sources to ensure the integrity and security of the system.
+
+This rule identifies commands that can disable the Driver Signature Enforcement feature.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Use Osquery and endpoint driver events (`event.category = "driver"`) to investigate if suspicious drivers were loaded into the system after the command was executed.
+  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+- Identify the driver's `Device Name` and `Service Name`.
+- Check for alerts from the rules specified in the `Related Rules` section.
+
+
+*False positive analysis*
+
+
+- This activity should not happen legitimately. The security team should address any potential benign true positive (B-TP), as this configuration can put the user and the domain at risk.
+
+
+*Related Rules*
+
+
+- First Time Seen Driver Loaded - df0fd41e-5590-4965-ad5e-cd079ec22fa9
+- Untrusted Driver Loaded - d8ab1ec1-feeb-48b9-89e7-c12e189448aa
+- Code Signing Policy Modification Through Registry - da7733b1-fe08-487e-b536-0a04c6d8b0cd
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Disable and uninstall all suspicious drivers found in the system. This can be done via Device Manager. (Note that this step may require you to boot the system into Safe Mode.)
+- Remove the related services and registry keys found in the system. Note that the service will probably not stop if the driver is still installed.
+  - This can be done via PowerShell `Remove-Service` cmdlet.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Remove and block malicious artifacts identified during triage.
+- Ensure that the Driver Signature Enforcement is enabled on the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  (process.name: "bcdedit.exe" or ?process.pe.original_file_name == "bcdedit.exe") and process.args: ("-set", "/set") and 
+  process.args: ("TESTSIGNING", "nointegritychecks", "loadoptions", "DISABLE_INTEGRITY_CHECKS")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Subvert Trust Controls
+** ID: T1553
+** Reference URL: https://attack.mitre.org/techniques/T1553/
+* Sub-technique:
+** Name: Code Signing Policy Modification
+** ID: T1553.006
+** Reference URL: https://attack.mitre.org/techniques/T1553/006/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-code-signing-policy-modification-through-registry.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-code-signing-policy-modification-through-registry.asciidoc
new file mode 100644
index 0000000000..5097207a40
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-code-signing-policy-modification-through-registry.asciidoc
@@ -0,0 +1,146 @@
+[[prebuilt-rule-8-11-17-code-signing-policy-modification-through-registry]]
+=== Code Signing Policy Modification Through Registry
+
+Identifies attempts to disable the code signing policy through the registry. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 10
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Code Signing Policy Modification Through Registry*
+
+
+Microsoft created the Windows Driver Signature Enforcement (DSE) security feature to prevent drivers with invalid signatures from loading and executing into the kernel (ring 0). DSE aims to protect systems by blocking attackers from loading malicious drivers on targets. 
+
+This protection is essential for maintaining system security. However, attackers or administrators can disable DSE and load untrusted drivers, which can put the system at risk. Therefore, it's important to keep this feature enabled and only load drivers from trusted sources to ensure system integrity and security.
+
+This rule identifies registry modifications that can disable DSE.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Use Osquery and endpoint driver events (`event.category = "driver"`) to investigate if suspicious drivers were loaded into the system after the registry was modified.
+  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+- Identify the driver's `Device Name` and `Service Name`.
+- Check for alerts from the rules specified in the `Related Rules` section.
+
+
+*False positive analysis*
+
+
+- This activity should not happen legitimately. The security team should address any potential benign true positive (B-TP), as this configuration can put the user and the domain at risk.
+
+
+*Related Rules*
+
+
+- First Time Seen Driver Loaded - df0fd41e-5590-4965-ad5e-cd079ec22fa9
+- Untrusted Driver Loaded - d8ab1ec1-feeb-48b9-89e7-c12e189448aa
+- Code Signing Policy Modification Through Built-in tools - b43570de-a908-4f7f-8bdb-b2df6ffd8c80
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Disable and uninstall all suspicious drivers found in the system. This can be done via Device Manager. (Note that this step may require you to boot the system into Safe Mode.)
+- Remove the related services and registry keys found in the system. Note that the service will probably not stop if the driver is still installed.
+  - This can be done via PowerShell `Remove-Service` cmdlet.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Remove and block malicious artifacts identified during triage.
+- Ensure that the Driver Signature Enforcement is enabled on the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and event.type : ("creation", "change") and
+(
+  registry.path : (
+    "HKEY_USERS\\*\\Software\\Policies\\Microsoft\\Windows NT\\Driver Signing\\BehaviorOnFailedVerify",
+    "HKU\\*\\Software\\Policies\\Microsoft\\Windows NT\\Driver Signing\\BehaviorOnFailedVerify",
+    "\\REGISTRY\\USER\\*\\Software\\Policies\\Microsoft\\Windows NT\\Driver Signing\\BehaviorOnFailedVerify"
+  ) and
+  registry.value: "BehaviorOnFailedVerify" and
+  registry.data.strings : ("0", "0x00000000", "1", "0x00000001")
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Subvert Trust Controls
+** ID: T1553
+** Reference URL: https://attack.mitre.org/techniques/T1553/
+* Sub-technique:
+** Name: Code Signing Policy Modification
+** ID: T1553.006
+** Reference URL: https://attack.mitre.org/techniques/T1553/006/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-creation-or-modification-of-domain-backup-dpapi-private-key.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-creation-or-modification-of-domain-backup-dpapi-private-key.asciidoc
new file mode 100644
index 0000000000..ee314c3431
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-creation-or-modification-of-domain-backup-dpapi-private-key.asciidoc
@@ -0,0 +1,101 @@
+[[prebuilt-rule-8-11-17-creation-or-modification-of-domain-backup-dpapi-private-key]]
+=== Creation or Modification of Domain Backup DPAPI private key
+
+Identifies the creation or modification of Domain Backup private keys. Adversaries may extract the Data Protection API (DPAPI) domain backup key from a Domain Controller (DC) to be able to decrypt any domain user master key file.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.file-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.dsinternals.com/en/retrieving-dpapi-backup-keys-from-active-directory/
+* https://posts.specterops.io/operational-guidance-for-offensive-user-dpapi-abuse-1fb7fac8b107
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Credential Access
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 210
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+Domain DPAPI Backup keys are stored on domain controllers and can be dumped remotely with tools such as Mimikatz. The resulting .pvk private key can be used to decrypt ANY domain user masterkeys, which then can be used to decrypt any secrets protected by those keys.
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "windows" and event.type != "deletion" and file.name : ("ntds_capi_*.pfx", "ntds_capi_*.pvk")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Credential Access
+** ID: TA0006
+** Reference URL: https://attack.mitre.org/tactics/TA0006/
+* Technique:
+** Name: Unsecured Credentials
+** ID: T1552
+** Reference URL: https://attack.mitre.org/techniques/T1552/
+* Sub-technique:
+** Name: Private Keys
+** ID: T1552.004
+** Reference URL: https://attack.mitre.org/techniques/T1552/004/
+* Technique:
+** Name: Credentials from Password Stores
+** ID: T1555
+** Reference URL: https://attack.mitre.org/techniques/T1555/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-cron-job-created-or-changed-by-previously-unknown-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-cron-job-created-or-changed-by-previously-unknown-process.asciidoc
new file mode 100644
index 0000000000..fbc4bb3bd6
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-cron-job-created-or-changed-by-previously-unknown-process.asciidoc
@@ -0,0 +1,230 @@
+[[prebuilt-rule-8-11-17-cron-job-created-or-changed-by-previously-unknown-process]]
+=== Cron Job Created or Changed by Previously Unknown Process
+
+Linux cron jobs are scheduled tasks that can be leveraged by malicious actors for persistence, privilege escalation and command execution. By creating or modifying cron job configurations, attackers can execute malicious commands or scripts at predefined intervals, ensuring their continued presence and enabling unauthorized activities.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://pberba.github.io/security/2022/01/30/linux-threat-hunting-for-persistence-systemd-timers-cron/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Privilege Escalation
+* Tactic: Execution
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 10
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Cron Job Created or Changed by Previously Unknown Process*
+
+Linux cron jobs are scheduled tasks that run at specified intervals or times, managed by the cron daemon. 
+
+By creating or modifying cron job configurations, attackers can execute malicious commands or scripts at predefined intervals, ensuring their continued presence and enabling unauthorized activities.
+
+This rule monitors the creation of previously unknown cron jobs by monitoring for file creation events in the most common cron job task location directories.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the cron job file that was created or modified.
+- Investigate whether any other files in any of the available cron job directories have been altered through OSQuery.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/etc/cron.allow.d/%' OR path LIKE '/etc/cron.d/%' OR path LIKE\n'/etc/cron.hourly/%' OR path LIKE '/etc/cron.daily/%' OR path LIKE '/etc/cron.weekly/%' OR path LIKE\n'/etc/cron.monthly/%' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve rc-local.service File Information","query":"SELECT * FROM file WHERE ( path = '/etc/cron.allow' OR path = '/etc/cron.deny' OR path = '/etc/crontab' OR path =\n'/usr/sbin/cron' OR path = '/usr/sbin/anacron' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/etc/cron.allow.d/%' OR path LIKE\n'/etc/cron.d/%' OR path LIKE '/etc/cron.hourly/%' OR path LIKE '/etc/cron.daily/%' OR path LIKE '/etc/cron.weekly/%' OR\npath LIKE '/etc/cron.monthly/%' )\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator who uses cron jobs for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- Suspicious File Creation in /etc for Persistence - 1c84dd64-7e6c-4bad-ac73-a5014ee37042
+- Potential Persistence Through Run Control Detected - 0f4d35e4-925e-4959-ab24-911be207ee6f
+- Potential Persistence Through init.d Detected - 474fd20e-14cc-49c5-8160-d9ab4ba16c8b
+- New Systemd Timer Created - 7fb500fa-8e24-4bd1-9480-2a819352602c
+- New Systemd Service Created by Previously Unknown Process - 17b0a495-4d9f-414c-8ad0-92f018b8e001
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service/timer or restore its original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type : "linux" and event.action : (
+  change or file_modify_event or creation or file_create_event or rename or file_rename_event
+) and file.path : (
+  /etc/cron.allow or /etc/cron.deny or /etc/cron.d/* or /etc/cron.hourly/* or /etc/cron.daily/* or /etc/cron.weekly/* or
+  /etc/cron.monthly/* or /etc/crontab or /usr/sbin/cron or /usr/sbin/anacron or /var/spool/cron/crontabs/*
+) and not (
+  (process.name : (
+    dpkg or dockerd or rpm or snapd or yum or exe or dnf or podman or dnf-automatic or puppet or autossl_check)
+  ) or 
+  (file.extension : (swp or swpx)) or 
+  (process.name : sed and file.name : sed*) or 
+  (process.name : perl and file.name : e2scrub_all.tmp*) or
+  (process.executable : /var/lib/dpkg*) or
+  (file.path:/var/spool/cron/crontabs/tmp.*)
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Scheduled Task/Job
+** ID: T1053
+** Reference URL: https://attack.mitre.org/techniques/T1053/
+* Sub-technique:
+** Name: Cron
+** ID: T1053.003
+** Reference URL: https://attack.mitre.org/techniques/T1053/003/
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Scheduled Task/Job
+** ID: T1053
+** Reference URL: https://attack.mitre.org/techniques/T1053/
+* Sub-technique:
+** Name: Cron
+** ID: T1053.003
+** Reference URL: https://attack.mitre.org/techniques/T1053/003/
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Scheduled Task/Job
+** ID: T1053
+** Reference URL: https://attack.mitre.org/techniques/T1053/
+* Sub-technique:
+** Name: Cron
+** ID: T1053.003
+** Reference URL: https://attack.mitre.org/techniques/T1053/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-delayed-execution-via-ping.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-delayed-execution-via-ping.asciidoc
new file mode 100644
index 0000000000..b9f8506e9f
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-delayed-execution-via-ping.asciidoc
@@ -0,0 +1,148 @@
+[[prebuilt-rule-8-11-17-delayed-execution-via-ping]]
+=== Delayed Execution via Ping
+
+Identifies the execution of commonly abused Windows utilities via a delayed Ping execution. This behavior is often observed during malware installation and is consistent with an attacker attempting to evade detection.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.process-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Execution
+* Tactic: Defense Evasion
+* Data Source: Elastic Defend
+
+*Version*: 3
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by process.parent.entity_id with maxspan=1m
+  [process where host.os.type == "windows" and event.action == "start" and process.name : "ping.exe" and
+   process.args : "-n" and process.parent.name : "cmd.exe" and not user.id : "S-1-5-18"]
+  [process where host.os.type == "windows" and event.action == "start" and
+   process.parent.name : "cmd.exe" and
+   (
+        process.name : (
+            "rundll32.exe", "powershell.exe",
+            "mshta.exe", "msbuild.exe",
+            "certutil.exe", "regsvr32.exe",
+            "powershell.exe", "cscript.exe",
+            "wscript.exe", "wmic.exe",
+            "installutil.exe", "msxsl.exe",
+            "Microsoft.Workflow.Compiler.exe",
+            "ieexec.exe", "iexpress.exe",
+            "RegAsm.exe", "installutil.exe",
+            "RegSvcs.exe", "RegAsm.exe"
+        ) or
+        (process.executable : "?:\\Users\\*\\AppData\\*.exe" and not process.code_signature.trusted == true)
+    ) and
+
+    not process.args : ("?:\\Program Files\\*", "?:\\Program Files (x86)\\*") and
+    not (process.name : ("openssl.exe", "httpcfg.exe", "certutil.exe") and process.parent.command_line : "*ScreenConnectConfigurator.cmd*") and
+    not (process.pe.original_file_name : "DPInst.exe" and process.command_line : "driver\\DPInst_x64  /f ") and
+    not (process.name : "powershell.exe" and process.args : "Write-Host ======*") and
+    not (process.name : "wscript.exe" and process.args : "launchquiet_args.vbs" and process.parent.args : "?:\\Windows\\TempInst\\7z*") and
+    not (process.name : "regsvr32.exe" and process.args : ("?:\\windows\\syswow64\\msxml?.dll", "msxml?.dll", "?:\\Windows\\SysWOW64\\mschrt20.ocx")) and 
+    not (process.name : "wscript.exe" and
+         process.working_directory :
+                    ("?:\\Windows\\TempInst\\*",
+                     "?:\\Users\\*\\AppData\\Local\\Temp\\BackupBootstrapper\\Logs\\",
+                     "?:\\Users\\*\\AppData\\Local\\Temp\\QBTools\\"))
+    ]
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
+* Sub-technique:
+** Name: PowerShell
+** ID: T1059.001
+** Reference URL: https://attack.mitre.org/techniques/T1059/001/
+* Sub-technique:
+** Name: Visual Basic
+** ID: T1059.005
+** Reference URL: https://attack.mitre.org/techniques/T1059/005/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: System Script Proxy Execution
+** ID: T1216
+** Reference URL: https://attack.mitre.org/techniques/T1216/
+* Technique:
+** Name: System Binary Proxy Execution
+** ID: T1218
+** Reference URL: https://attack.mitre.org/techniques/T1218/
+* Sub-technique:
+** Name: CMSTP
+** ID: T1218.003
+** Reference URL: https://attack.mitre.org/techniques/T1218/003/
+* Sub-technique:
+** Name: InstallUtil
+** ID: T1218.004
+** Reference URL: https://attack.mitre.org/techniques/T1218/004/
+* Sub-technique:
+** Name: Mshta
+** ID: T1218.005
+** Reference URL: https://attack.mitre.org/techniques/T1218/005/
+* Sub-technique:
+** Name: Regsvcs/Regasm
+** ID: T1218.009
+** Reference URL: https://attack.mitre.org/techniques/T1218/009/
+* Sub-technique:
+** Name: Regsvr32
+** ID: T1218.010
+** Reference URL: https://attack.mitre.org/techniques/T1218/010/
+* Sub-technique:
+** Name: Rundll32
+** ID: T1218.011
+** Reference URL: https://attack.mitre.org/techniques/T1218/011/
+* Technique:
+** Name: XSL Script Processing
+** ID: T1220
+** Reference URL: https://attack.mitre.org/techniques/T1220/
+* Technique:
+** Name: Virtualization/Sandbox Evasion
+** ID: T1497
+** Reference URL: https://attack.mitre.org/techniques/T1497/
+* Sub-technique:
+** Name: Time Based Evasion
+** ID: T1497.003
+** Reference URL: https://attack.mitre.org/techniques/T1497/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-deleting-backup-catalogs-with-wbadmin.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-deleting-backup-catalogs-with-wbadmin.asciidoc
new file mode 100644
index 0000000000..93eed8047e
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-deleting-backup-catalogs-with-wbadmin.asciidoc
@@ -0,0 +1,140 @@
+[[prebuilt-rule-8-11-17-deleting-backup-catalogs-with-wbadmin]]
+=== Deleting Backup Catalogs with Wbadmin
+
+Identifies use of the wbadmin.exe to delete the backup catalog. Ransomware and other malware may do this to prevent system recovery.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Impact
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Deleting Backup Catalogs with Wbadmin*
+
+
+Windows Server Backup stores the details about your backups (what volumes are backed up and where the backups are located) in a file called a backup catalog, which ransomware victims can use to recover corrupted backup files. Deleting these files is a common step in threat actor playbooks.
+
+This rule identifies the deletion of the backup catalog using the `wbadmin.exe` utility.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+- Check if any files on the host machine have been encrypted.
+
+
+*False positive analysis*
+
+
+- Administrators can use this command to delete corrupted catalogs, but overall the activity is unlikely to be legitimate.
+
+
+*Related rules*
+
+
+- Third-party Backup Files Deleted via Unexpected Process - 11ea6bec-ebde-4d71-a8e9-784948f8e3e9
+- Volume Shadow Copy Deleted or Resized via VssAdmin - b5ea4bfe-a1b2-421f-9d47-22a75a6f2921
+- Volume Shadow Copy Deletion via PowerShell - d99a037b-c8e2-47a5-97b9-170d076827c4
+- Volume Shadow Copy Deletion via WMIC - dc9c1f74-dac3-48e3-b47f-eb79db358f57
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Consider isolating the involved host to prevent destructive behavior, which is commonly associated with this activity.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- If any other destructive action was identified on the host, it is recommended to prioritize the investigation and look for ransomware preparation and execution activities.
+- If any backups were affected:
+  - Perform data recovery locally or restore the backups from replicated copies (cloud, other servers, etc.).
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  (process.name : "wbadmin.exe" or ?process.pe.original_file_name == "WBADMIN.EXE") and
+  process.args : "catalog" and process.args : "delete"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Impact
+** ID: TA0040
+** Reference URL: https://attack.mitre.org/tactics/TA0040/
+* Technique:
+** Name: Data Destruction
+** ID: T1485
+** Reference URL: https://attack.mitre.org/techniques/T1485/
+* Technique:
+** Name: Inhibit System Recovery
+** ID: T1490
+** Reference URL: https://attack.mitre.org/techniques/T1490/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-disabling-user-account-control-via-registry-modification.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-disabling-user-account-control-via-registry-modification.asciidoc
new file mode 100644
index 0000000000..4b9be438c7
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-disabling-user-account-control-via-registry-modification.asciidoc
@@ -0,0 +1,182 @@
+[[prebuilt-rule-8-11-17-disabling-user-account-control-via-registry-modification]]
+=== Disabling User Account Control via Registry Modification
+
+User Account Control (UAC) can help mitigate the impact of malware on Windows hosts. With UAC, apps and tasks always run in the security context of a non-administrator account, unless an administrator specifically authorizes administrator-level access to the system. This rule identifies registry value changes to bypass User Access Control (UAC) protection.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.greyhathacker.net/?p=796
+* https://docs.microsoft.com/en-us/windows/security/identity-protection/user-account-control/user-account-control-group-policy-and-registry-key-settings
+* https://docs.microsoft.com/en-us/windows/security/identity-protection/user-account-control/user-account-control-overview
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Privilege Escalation
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 111
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Disabling User Account Control via Registry Modification*
+
+
+Windows User Account Control (UAC) allows a program to elevate its privileges (tracked as low to high integrity levels) to perform a task under administrator-level permissions, possibly by prompting the user for confirmation. UAC can deny an operation under high-integrity enforcement, or allow the user to perform the action if they are in the local administrators group and enter an administrator password when prompted.
+
+For more information about the UAC and how it works, check the https://docs.microsoft.com/en-us/windows/security/identity-protection/user-account-control/how-user-account-control-works[official Microsoft docs page].
+
+Attackers may disable UAC to execute code directly in high integrity. This rule identifies registry value changes to bypass the UAC protection.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Inspect the host for suspicious or abnormal behaviors in the alert timeframe.
+- Investigate abnormal behaviors observed by the subject process such as network connections, registry or file modifications, and any spawned child processes.
+- Analyze non-system processes executed with high integrity after UAC was disabled for unknown or suspicious processes.
+- Retrieve the suspicious processes' executables and determine if they are malicious:
+  - Use a private sandboxed malware analysis system to perform analysis.
+    - Observe and collect information about the following activities:
+      - Attempts to contact external domains and addresses.
+      - File and registry access, modification, and creation activities.
+      - Service creation and launch activities.
+      - Scheduled tasks creation.
+  - Use the PowerShell `Get-FileHash` cmdlet to get the files' SHA-256 hash values.
+    - Search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Restore UAC settings to the desired state.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and event.type == "change" and
+  registry.path :
+    (
+      "HKLM\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\EnableLUA",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\ConsentPromptBehaviorAdmin",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\PromptOnSecureDesktop",
+      "\\REGISTRY\\MACHINE\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\EnableLUA",
+      "\\REGISTRY\\MACHINE\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\ConsentPromptBehaviorAdmin",
+      "\\REGISTRY\\MACHINE\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\PromptOnSecureDesktop"
+    ) and
+  registry.data.strings : ("0", "0x00000000")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Bypass User Account Control
+** ID: T1548.002
+** Reference URL: https://attack.mitre.org/techniques/T1548/002/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Bypass User Account Control
+** ID: T1548.002
+** Reference URL: https://attack.mitre.org/techniques/T1548/002/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Tools
+** ID: T1562.001
+** Reference URL: https://attack.mitre.org/techniques/T1562/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-dns-over-https-enabled-via-registry.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-dns-over-https-enabled-via-registry.asciidoc
new file mode 100644
index 0000000000..52f7e1211c
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-dns-over-https-enabled-via-registry.asciidoc
@@ -0,0 +1,91 @@
+[[prebuilt-rule-8-11-17-dns-over-https-enabled-via-registry]]
+=== DNS-over-HTTPS Enabled via Registry
+
+Identifies when a user enables DNS-over-HTTPS. This can be used to hide internet activity or the process of exfiltrating data. With this enabled, an organization will lose visibility into data such as query type, response, and originating IP, which are used to determine bad actors.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.tenforums.com/tutorials/151318-how-enable-disable-dns-over-https-doh-microsoft-edge.html
+* https://chromeenterprise.google/policies/?policy=DnsOverHttpsMode
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 110
+
+*Rule authors*: 
+
+* Austin Songer
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and event.type in ("creation", "change") and
+  (registry.path : "*\\SOFTWARE\\Policies\\Microsoft\\Edge\\BuiltInDnsClientEnabled" and
+  registry.data.strings : "1") or
+  (registry.path : "*\\SOFTWARE\\Google\\Chrome\\DnsOverHttpsMode" and
+  registry.data.strings : "secure") or
+  (registry.path : "*\\SOFTWARE\\Policies\\Mozilla\\Firefox\\DNSOverHTTPS" and
+  registry.data.strings : "1")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-dynamic-linker-copy.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-dynamic-linker-copy.asciidoc
new file mode 100644
index 0000000000..3d3d5e40ae
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-dynamic-linker-copy.asciidoc
@@ -0,0 +1,192 @@
+[[prebuilt-rule-8-11-17-dynamic-linker-copy]]
+=== Dynamic Linker Copy
+
+Detects the copying of the Linux dynamic loader binary and subsequent file creation for the purpose of creating a backup copy. This technique was seen recently being utilized by Linux malware prior to patching the dynamic loader in order to inject and preload a malicious shared object file. This activity should never occur and if it does then it should be considered highly suspicious or malicious.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.intezer.com/blog/incident-response/orbit-new-undetected-linux-threat/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Threat: Orbit
+* Data Source: Elastic Defend
+
+*Version*: 109
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Dynamic Linker Copy*
+
+
+The Linux dynamic linker is responsible for loading shared libraries required by executables at runtime. It is a critical component of the Linux operating system and should not be tampered with. 
+
+Adversaries may attempt to copy the dynamic linker binary and create a backup copy before patching it to inject and preload malicious shared object files. This technique has been observed in recent Linux malware attacks and is considered highly suspicious or malicious.
+
+The detection rule 'Dynamic Linker Copy' is designed to identify such abuse by monitoring for processes with names "cp" or "rsync" that involve copying the dynamic linker binary ("/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2") and modifying the "/etc/ld.so.preload" file. Additionally, the rule checks for the creation of new files with the "so" extension on Linux systems. By detecting these activities within a short time span (1 minute), the rule aims to alert security analysts to potential malicious behavior.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible investigation steps*
+
+
+- Investigate the dynamic linker that was copied or altered.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path = '/etc/ld.so.preload' OR path = '/lib64/ld-linux-x86-64.so.2' OR path =\n'/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' OR path = '/usr/lib64/ld-linux-x86-64.so.2' OR path =\n'/usr/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path = '/etc/ld.so.preload' OR path =\n'/lib64/ld-linux-x86-64.so.2' OR path = '/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' OR path =\n'/usr/lib64/ld-linux-x86-64.so.2' OR path = '/usr/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' )\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+- Any activity that triggered the alert and is not inherently malicious must be monitored by the security team.
+- The security team should address any potential benign true positive (B-TP), as this configuration can put the user and the domain at risk.
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- Modification of Dynamic Linker Preload Shared Object Inside A Container - 342f834b-21a6-41bf-878c-87d116eba3ee
+- Modification of Dynamic Linker Preload Shared Object - 717f82c2-7741-4f9b-85b8-d06aeb853f4f
+- Shared Object Created or Changed by Previously Unknown Process - aebaa51f-2a91-4f6a-850b-b601db2293f4
+
+
+*Response and Remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by process.entity_id with maxspan=1m
+[process where host.os.type == "linux" and event.type == "start" and process.name in ("cp", "rsync") and
+   process.args in (
+     "/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2", "/etc/ld.so.preload", "/lib64/ld-linux-x86-64.so.2",
+     "/usr/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2", "/usr/lib64/ld-linux-x86-64.so.2"
+    )]
+[file where host.os.type == "linux" and event.action == "creation" and file.extension == "so"]
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Hijack Execution Flow
+** ID: T1574
+** Reference URL: https://attack.mitre.org/techniques/T1574/
+* Sub-technique:
+** Name: Dynamic Linker Hijacking
+** ID: T1574.006
+** Reference URL: https://attack.mitre.org/techniques/T1574/006/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ec2-ami-shared-with-another-account.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ec2-ami-shared-with-another-account.asciidoc
new file mode 100644
index 0000000000..0ec7696a42
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ec2-ami-shared-with-another-account.asciidoc
@@ -0,0 +1,117 @@
+[[prebuilt-rule-8-11-17-ec2-ami-shared-with-another-account]]
+=== EC2 AMI Shared with Another Account
+
+Identifies an AWS Amazon Machine Image (AMI) being shared with another AWS account. Adversaries with access may share an AMI with an external AWS account as a means of data exfiltration. AMIs can contain secrets, bash histories, code artifacts, and other sensitive data that adversaries may abuse if shared with unauthorized accounts. AMIs can be made publicly available accidentally as well.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 10m
+
+*Searches indices from*: now-60m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AMIs.html
+* https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/sharingamis-explicit.html
+* https://stratus-red-team.cloud/attack-techniques/AWS/aws.exfiltration.ec2-share-ami/
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: AWS EC2
+* Use Case: Threat Detection
+* Tactic: Exfiltration
+
+*Version*: 2
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and Analysis*
+
+
+
+*Investigating EC2 AMI Shared with Another Account*
+
+
+This rule identifies when an Amazon Machine Image (AMI) is shared with another AWS account. While sharing AMIs is a common practice, adversaries may exploit this feature to exfiltrate data by sharing AMIs with external accounts under their control.
+
+
+*Possible Investigation Steps*
+
+
+- **Review the Sharing Event**: Identify the AMI involved and review the event details in AWS CloudTrail. Look for `ModifyImageAttribute` actions where the AMI attributes were changed to include additional user accounts.
+    - **Request and Response Parameters**: Check the `aws.cloudtrail.request_parameters` and `aws.response.response_elements` fields in the CloudTrail event to identify the AMI ID and the user ID of the account with which the AMI was shared.
+- **Verify the Shared AMI**: Check the AMI that was shared and its contents to determine the sensitivity of the data stored within it.
+- **Contextualize with Recent Changes**: Compare this sharing event against recent changes in AMI configurations and deployments. Look for any other recent permissions changes or unusual administrative actions.
+- **Validate External Account**: Examine the AWS account to which the AMI was shared. Determine whether this account is known and previously authorized to access such resources.
+- **Interview Relevant Personnel**: If the share was initiated by a user, verify the intent and authorization for this action with the person or team responsible for managing AMI deployments.
+- **Audit Related Security Policies**: Check the security policies governing AMI sharing within your organization to ensure they are being followed and are adequate to prevent unauthorized sharing.
+
+
+*False Positive Analysis*
+
+
+- **Legitimate Sharing Practices**: AMI sharing is a common and legitimate practice for collaboration and resource management in AWS. Always verify that the sharing activity was unauthorized before escalating.
+- **Automation Tools**: Some organizations use automation tools for AMI management which might programmatically share AMIs. Verify if such tools are in operation and whether their actions are responsible for the observed behavior.
+
+
+*Response and Remediation*
+
+
+- **Review and Revoke Unauthorized Shares**: If the share is found to be unauthorized, immediately revoke the shared permissions from the AMI.
+- **Enhance Monitoring of Shared AMIs**: Implement monitoring to track changes to shared AMIs and alert on unauthorized access patterns.
+- **Incident Response**: If malicious intent is confirmed, consider it a data breach incident and initiate the incident response protocol. This includes further investigation, containment, and recovery.
+- **Policy Update**: Review and possibly update your organization’s policies on AMI sharing to tighten control and prevent unauthorized access.
+- **Educate Users**: Conduct training sessions for users involved in managing AMIs to reinforce best practices and organizational policies regarding AMI sharing.
+
+
+*Additional Information*
+
+
+For more information on managing and sharing AMIs, refer to the https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AMIs.html[Amazon EC2 User Guide on AMIs] and https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/sharingamis-explicit.html[Sharing AMIs]. Additionally, explore adversarial techniques related to data exfiltration via AMI sharing as documented by Stratus Red Team https://stratus-red-team.cloud/attack-techniques/AWS/aws.exfiltration.ec2-share-ami/[here].
+
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset: "aws.cloudtrail" and event.provider: "ec2.amazonaws.com"
+    and event.action: ModifyImageAttribute and event.outcome: success
+    and aws.cloudtrail.request_parameters: (*imageId* and *add* and *userId*)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Exfiltration
+** ID: TA0010
+** Reference URL: https://attack.mitre.org/tactics/TA0010/
+* Technique:
+** Name: Transfer Data to Cloud Account
+** ID: T1537
+** Reference URL: https://attack.mitre.org/techniques/T1537/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-encoded-executable-stored-in-the-registry.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-encoded-executable-stored-in-the-registry.asciidoc
new file mode 100644
index 0000000000..284d7bd207
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-encoded-executable-stored-in-the-registry.asciidoc
@@ -0,0 +1,71 @@
+[[prebuilt-rule-8-11-17-encoded-executable-stored-in-the-registry]]
+=== Encoded Executable Stored in the Registry
+
+Identifies registry write modifications to hide an encoded portable executable. This could be indicative of adversary defense evasion by avoiding the storing of malicious content directly on disk.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.registry-*
+* endgame-*
+* logs-windows.sysmon_operational-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 209
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and
+/* update here with encoding combinations */
+ registry.data.strings : "TVqQAAMAAAAEAAAA*"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Deobfuscate/Decode Files or Information
+** ID: T1140
+** Reference URL: https://attack.mitre.org/techniques/T1140/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-encrypting-files-with-winrar-or-7z.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-encrypting-files-with-winrar-or-7z.asciidoc
new file mode 100644
index 0000000000..28e028a73a
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-encrypting-files-with-winrar-or-7z.asciidoc
@@ -0,0 +1,153 @@
+[[prebuilt-rule-8-11-17-encrypting-files-with-winrar-or-7z]]
+=== Encrypting Files with WinRar or 7z
+
+Identifies use of WinRar or 7z to create an encrypted files. Adversaries will often compress and encrypt data in preparation for exfiltration.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.process-*
+* winlogbeat-*
+* logs-windows.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.welivesecurity.com/2020/12/02/turla-crutch-keeping-back-door-open/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Collection
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Encrypting Files with WinRar or 7z*
+
+
+Attackers may compress and/or encrypt data collected before exfiltration. Compressing the data can help obfuscate the collected data and minimize the amount of data sent over the network. Encryption can be used to hide information that is being exfiltrated from detection or make exfiltration less apparent upon inspection by a defender.
+
+These steps are usually done in preparation for exfiltration, meaning the attack may be in its final stages.
+
+
+*Possible investigation steps*
+
+
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Retrieve the encrypted file.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Check if the password used in the encryption was included in the command line.
+- Decrypt the `.rar`/`.zip` and check if the information is sensitive.
+- If the password is not available, and the format is `.zip` or the option used in WinRAR is not the `-hp`, list the file names included in the encrypted file.
+- Investigate if the file was transferred to an attacker-controlled server.
+
+
+*False positive analysis*
+
+
+- Backup software can use these utilities. Check the `process.parent.executable` and `process.parent.command_line` fields to determine what triggered the encryption.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Prioritize cases that involve personally identifiable information (PII) or other classified data.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+(
+  (
+    (
+      process.name:"rar.exe" or ?process.code_signature.subject_name == "win.rar GmbH" or
+      ?process.pe.original_file_name == "Command line RAR"
+    ) and
+    process.args == "a" and process.args : ("-hp*", "-p*", "/hp*", "/p*")
+  ) or
+  (
+    ?process.pe.original_file_name in ("7z.exe", "7za.exe") and
+    process.args == "a" and process.args : "-p*"
+  )
+) and
+  not process.parent.executable : (
+        "C:\\Program Files\\*.exe",
+        "C:\\Program Files (x86)\\*.exe",
+        "?:\\ManageEngine\\*\\jre\\bin\\java.exe",
+        "?:\\Nox\\bin\\Nox.exe"
+      )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Collection
+** ID: TA0009
+** Reference URL: https://attack.mitre.org/tactics/TA0009/
+* Technique:
+** Name: Data from Local System
+** ID: T1005
+** Reference URL: https://attack.mitre.org/techniques/T1005/
+* Technique:
+** Name: Archive Collected Data
+** ID: T1560
+** Reference URL: https://attack.mitre.org/techniques/T1560/
+* Sub-technique:
+** Name: Archive via Utility
+** ID: T1560.001
+** Reference URL: https://attack.mitre.org/techniques/T1560/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumerating-domain-trusts-via-dsquery-exe.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumerating-domain-trusts-via-dsquery-exe.asciidoc
new file mode 100644
index 0000000000..4d92b9ab09
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumerating-domain-trusts-via-dsquery-exe.asciidoc
@@ -0,0 +1,121 @@
+[[prebuilt-rule-8-11-17-enumerating-domain-trusts-via-dsquery-exe]]
+=== Enumerating Domain Trusts via DSQUERY.EXE
+
+Identifies the use of dsquery.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate trust relationships that may be used for Lateral Movement opportunities in Windows multi-domain forest environments.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://learn.microsoft.com/en-us/previous-versions/windows/it-pro/windows-server-2012-r2-and-2012/cc732952(v=ws.11)
+* https://posts.specterops.io/a-guide-to-attacking-domain-trusts-971e52cb2944
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Discovery
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 8
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Enumerating Domain Trusts via DSQUERY.EXE*
+
+
+Active Directory (AD) domain trusts define relationships between domains within a Windows AD environment. In this setup, a "trusting" domain permits users from a "trusted" domain to access resources. These trust relationships can be configurable as one-way, two-way, transitive, or non-transitive, enabling controlled access and resource sharing across domains.
+
+This rule identifies the usage of the `dsquery.exe` utility to enumerate domain trusts. Attackers can use this information to enable the next actions in a target environment, such as lateral movement.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+
+
+*False positive analysis*
+
+
+- Discovery activities are not inherently malicious if they occur in isolation and are done within the user business context (e.g., an administrator in this context). As long as the analyst did not identify suspicious activity related to the user or host, such alerts can be dismissed.
+
+
+*Related rules*
+
+
+- Enumerating Domain Trusts via NLTEST.EXE - 84da2554-e12a-11ec-b896-f661ea17fbcd
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- Restrict PowerShell usage outside of IT and engineering business units using GPOs, AppLocker, Intune, or similar software.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+    (process.name : "dsquery.exe" or ?process.pe.original_file_name: "dsquery.exe") and 
+    process.args : "*objectClass=trustedDomain*"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Discovery
+** ID: TA0007
+** Reference URL: https://attack.mitre.org/tactics/TA0007/
+* Technique:
+** Name: Remote System Discovery
+** ID: T1018
+** Reference URL: https://attack.mitre.org/techniques/T1018/
+* Technique:
+** Name: Domain Trust Discovery
+** ID: T1482
+** Reference URL: https://attack.mitre.org/techniques/T1482/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumerating-domain-trusts-via-nltest-exe.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumerating-domain-trusts-via-nltest-exe.asciidoc
new file mode 100644
index 0000000000..81bddc08e0
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumerating-domain-trusts-via-nltest-exe.asciidoc
@@ -0,0 +1,126 @@
+[[prebuilt-rule-8-11-17-enumerating-domain-trusts-via-nltest-exe]]
+=== Enumerating Domain Trusts via NLTEST.EXE
+
+Identifies the use of nltest.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate domain trusts and gain insight into trust relationships, as well as the state of Domain Controller (DC) replication in a Microsoft Windows NT Domain.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.microsoft.com/en-us/previous-versions/windows/it-pro/windows-server-2012-r2-and-2012/cc731935(v=ws.11)
+* https://redcanary.com/blog/how-one-hospital-thwarted-a-ryuk-ransomware-outbreak/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Discovery
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 111
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Enumerating Domain Trusts via NLTEST.EXE*
+
+
+Active Directory (AD) domain trusts define relationships between domains within a Windows AD environment. In this setup, a "trusting" domain permits users from a "trusted" domain to access resources. These trust relationships can be configurable as one-way, two-way, transitive, or non-transitive, enabling controlled access and resource sharing across domains.
+
+This rule identifies the usage of the `nltest.exe` utility to enumerate domain trusts. Attackers can use this information to enable the next actions in a target environment, such as lateral movement.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+
+
+*False positive analysis*
+
+
+- Discovery activities are not inherently malicious if they occur in isolation and are done within the user business context (e.g., an administrator in this context). As long as the analyst did not identify suspicious activity related to the user or host, such alerts can be dismissed.
+
+
+*Related rules*
+
+
+- Enumerating Domain Trusts via DSQUERY.EXE - 06a7a03c-c735-47a6-a313-51c354aef6c3
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- Restrict PowerShell usage outside of IT and engineering business units using GPOs, AppLocker, Intune, or similar software.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+    process.name : "nltest.exe" and process.args : (
+        "/DCLIST:*", "/DCNAME:*", "/DSGET*",
+        "/LSAQUERYFTI:*", "/PARENTDOMAIN",
+        "/DOMAIN_TRUSTS", "/BDC_QUERY:*"
+        ) and 
+not process.parent.name : "PDQInventoryScanner.exe" and 
+not user.id in ("S-1-5-18", "S-1-5-19", "S-1-5-20")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Discovery
+** ID: TA0007
+** Reference URL: https://attack.mitre.org/tactics/TA0007/
+* Technique:
+** Name: Remote System Discovery
+** ID: T1018
+** Reference URL: https://attack.mitre.org/techniques/T1018/
+* Technique:
+** Name: Domain Trust Discovery
+** ID: T1482
+** Reference URL: https://attack.mitre.org/techniques/T1482/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumeration-command-spawned-via-wmiprvse.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumeration-command-spawned-via-wmiprvse.asciidoc
new file mode 100644
index 0000000000..2ec567c934
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-enumeration-command-spawned-via-wmiprvse.asciidoc
@@ -0,0 +1,137 @@
+[[prebuilt-rule-8-11-17-enumeration-command-spawned-via-wmiprvse]]
+=== Enumeration Command Spawned via WMIPrvSE
+
+Identifies native Windows host and network enumeration commands spawned by the Windows Management Instrumentation Provider Service (WMIPrvSE).
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Execution
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and process.command_line != null and 
+  process.name:
+  (
+    "arp.exe",
+    "dsquery.exe",
+    "dsget.exe",
+    "gpresult.exe",
+    "hostname.exe",
+    "ipconfig.exe",
+    "nbtstat.exe",
+    "net.exe",
+    "net1.exe",
+    "netsh.exe",
+    "netstat.exe",
+    "nltest.exe",
+    "ping.exe",
+    "qprocess.exe",
+    "quser.exe",
+    "qwinsta.exe",
+    "reg.exe",
+    "sc.exe",
+    "systeminfo.exe",
+    "tasklist.exe",
+    "tracert.exe",
+    "whoami.exe"
+  ) and
+  process.parent.name:"wmiprvse.exe" and 
+  not (
+    process.name : "sc.exe" and process.args : "RemoteRegistry" and process.args : "start=" and 
+    process.args : ("demand", "disabled")
+  ) and
+  not process.args : "tenable_mw_scan"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Windows Management Instrumentation
+** ID: T1047
+** Reference URL: https://attack.mitre.org/techniques/T1047/
+* Tactic:
+** Name: Discovery
+** ID: TA0007
+** Reference URL: https://attack.mitre.org/tactics/TA0007/
+* Technique:
+** Name: System Network Configuration Discovery
+** ID: T1016
+** Reference URL: https://attack.mitre.org/techniques/T1016/
+* Sub-technique:
+** Name: Internet Connection Discovery
+** ID: T1016.001
+** Reference URL: https://attack.mitre.org/techniques/T1016/001/
+* Technique:
+** Name: Remote System Discovery
+** ID: T1018
+** Reference URL: https://attack.mitre.org/techniques/T1018/
+* Technique:
+** Name: Process Discovery
+** ID: T1057
+** Reference URL: https://attack.mitre.org/techniques/T1057/
+* Technique:
+** Name: Account Discovery
+** ID: T1087
+** Reference URL: https://attack.mitre.org/techniques/T1087/
+* Technique:
+** Name: Software Discovery
+** ID: T1518
+** Reference URL: https://attack.mitre.org/techniques/T1518/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-executable-masquerading-as-kernel-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-executable-masquerading-as-kernel-process.asciidoc
new file mode 100644
index 0000000000..f83faed662
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-executable-masquerading-as-kernel-process.asciidoc
@@ -0,0 +1,110 @@
+[[prebuilt-rule-8-11-17-executable-masquerading-as-kernel-process]]
+=== Executable Masquerading as Kernel Process
+
+Monitors for kernel processes with associated process executable fields that are not empty. Unix kernel processes such as kthreadd and kworker typically do not have process.executable fields associated to them. Attackers may attempt to hide their malicious programs by masquerading as legitimate kernel processes.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://sandflysecurity.com/blog/linux-stealth-rootkit-malware-with-edr-evasion-analyzed/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Defend
+* Data Source: Elastic Endgame
+
+*Version*: 3
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "linux" and event.type == "start" and event.action in ("exec", "exec_event") and
+process.name : ("kworker*", "kthread*") and process.executable != null
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Sub-technique:
+** Name: Masquerade Task or Service
+** ID: T1036.004
+** Reference URL: https://attack.mitre.org/techniques/T1036/004/
+* Technique:
+** Name: Hide Artifacts
+** ID: T1564
+** Reference URL: https://attack.mitre.org/techniques/T1564/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-exporting-exchange-mailbox-via-powershell.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-exporting-exchange-mailbox-via-powershell.asciidoc
new file mode 100644
index 0000000000..a184330bef
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-exporting-exchange-mailbox-via-powershell.asciidoc
@@ -0,0 +1,162 @@
+[[prebuilt-rule-8-11-17-exporting-exchange-mailbox-via-powershell]]
+=== Exporting Exchange Mailbox via PowerShell
+
+Identifies the use of the Exchange PowerShell cmdlet, New-MailBoxExportRequest, to export the contents of a primary mailbox or archive to a .pst file. Adversaries may target user email to collect sensitive information.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.process-*
+* winlogbeat-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.volexity.com/blog/2020/12/14/dark-halo-leverages-solarwinds-compromise-to-breach-organizations/
+* https://docs.microsoft.com/en-us/powershell/module/exchange/new-mailboxexportrequest?view=exchange-ps
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Collection
+* Tactic: Execution
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: SentinelOne
+
+*Version*: 213
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Exporting Exchange Mailbox via PowerShell*
+
+
+Email mailboxes and their information can be valuable assets for attackers. Company mailboxes often contain sensitive information such as login credentials, intellectual property, financial data, and personal information, making them high-value targets for malicious actors.
+
+The `New-MailBoxExportRequest` cmdlet is used to begin the process of exporting contents of a primary mailbox or archive to a .pst file. Note that this is done on a per-mailbox basis and this cmdlet is available only in on-premises Exchange.
+
+Attackers can abuse this functionality in preparation for exfiltrating contents, which is likely to contain sensitive and strategic data.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Investigate the export operation:
+  - Identify the user account that performed the action and whether it should perform this kind of action.
+  - Contact the account owner and confirm whether they are aware of this activity.
+  - Check if this operation was approved and performed according to the organization's change management policy.
+  - Retrieve the operation status and use the `Get-MailboxExportRequest` cmdlet to review previous requests.
+  - By default, no group in Exchange has the privilege to import or export mailboxes. Investigate administrators that assigned the "Mailbox Import Export" privilege for abnormal activity.
+- Investigate if there is a significant quantity of export requests in the alert timeframe. This operation is done on a per-mailbox basis and can be part of a mass export.
+- If the operation was completed successfully:
+  - Check if the file is on the path specified in the command.
+  - Investigate if the file was compressed, archived, or retrieved by the attacker for exfiltration.
+
+
+*False positive analysis*
+
+
+- This mechanism can be used legitimately. Analysts can dismiss the alert if the administrator is aware of the activity and it is done with proper approval.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- If the involved host is not the Exchange server, isolate the host to prevent further post-compromise behavior.
+- Use the `Remove-MailboxExportRequest` cmdlet to remove fully or partially completed export requests.
+- Prioritize cases that involve personally identifiable information (PII) or other classified data.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Review the privileges of users with the "Mailbox Import Export" privilege to ensure that the least privilege principle is being followed.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  process.name: ("powershell.exe", "pwsh.exe", "powershell_ise.exe") and
+  process.command_line : ("*MailboxExportRequest*", "*-Mailbox*-ContentFilter*")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Collection
+** ID: TA0009
+** Reference URL: https://attack.mitre.org/tactics/TA0009/
+* Technique:
+** Name: Data from Local System
+** ID: T1005
+** Reference URL: https://attack.mitre.org/techniques/T1005/
+* Technique:
+** Name: Email Collection
+** ID: T1114
+** Reference URL: https://attack.mitre.org/techniques/T1114/
+* Sub-technique:
+** Name: Remote Email Collection
+** ID: T1114.002
+** Reference URL: https://attack.mitre.org/techniques/T1114/002/
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
+* Sub-technique:
+** Name: PowerShell
+** ID: T1059.001
+** Reference URL: https://attack.mitre.org/techniques/T1059/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-first-time-seen-aws-secret-value-accessed-in-secrets-manager.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-first-time-seen-aws-secret-value-accessed-in-secrets-manager.asciidoc
new file mode 100644
index 0000000000..c338a963de
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-first-time-seen-aws-secret-value-accessed-in-secrets-manager.asciidoc
@@ -0,0 +1,132 @@
+[[prebuilt-rule-8-11-17-first-time-seen-aws-secret-value-accessed-in-secrets-manager]]
+=== First Time Seen AWS Secret Value Accessed in Secrets Manager
+
+An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service may attempt to leverage the compromised service to access secrets in AWS Secrets Manager. This rule looks for the first time a specific user identity has programmatically retrieved a specific secret value from Secrets Manager using the `GetSecretValue` action. This rule assumes that AWS services such as Lambda functions and EC2 instances are setup with IAM role's assigned that have the necessary permissions to access the secrets in Secrets Manager. An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service would rely on the compromised service's IAM role to access the secrets in Secrets Manager.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 10m
+
+*Searches indices from*: now-60m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/secretsmanager/latest/apireference/API_GetSecretValue.html
+* https://detectioninthe.cloud/ttps/credential_access/access_secret_in_secrets_manager/
+* https://cloud.hacktricks.xyz/pentesting-cloud/aws-security/aws-services/aws-secrets-manager-enum
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Tactic: Credential Access
+* Resources: Investigation Guide
+
+*Version*: 311
+
+*Rule authors*: 
+
+* Nick Jones
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating First Time Seen AWS Secret Value Accessed in Secrets Manager*
+
+
+AWS Secrets Manager is a service that enables the replacement of hardcoded credentials in code, including passwords, with an API call to Secrets Manager to retrieve the secret programmatically.
+
+This rule looks for the retrieval of credentials using `GetSecretValue` action in Secrets Manager programmatically. This is a https://www.elastic.co/guide/en/security/master/rules-ui-create.html#create-new-terms-rule[New Terms] rule indicating this is the first time a specific user identity has successfuly retrieved a specific secret value from Secrets Manager within the last 15 days.
+
+
+*Possible investigation steps*
+
+
+- Identify the account and its role in the environment, and inspect the related policy.
+- Identify the applications that should use this account.
+- Investigate other alerts associated with the user account during the past 48 hours.
+- Investigate abnormal values in the `user_agent.original` field by comparing them with the intended and authorized usage and historical data. Suspicious user agent values include non-SDK, AWS CLI, custom user agents, etc.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences involving other users.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Considering the source IP address and geolocation of the user who issued the command:
+    - Do they look normal for the calling user?
+    - If the source is an EC2 IP address, is it associated with an EC2 instance in one of your accounts or is the source IP from an EC2 instance that's not under your control?
+    - If it is an authorized EC2 instance, is the activity associated with normal behavior for the instance role or roles? Are there any other alerts or signs of suspicious activity involving this instance?
+- Review IAM permission policies for the user identity and specific secrets accessed.
+- Examine the request parameters. These might indicate the source of the program or the nature of its tasks.
+- If you suspect the account has been compromised, scope potentially compromised assets by tracking servers, services, and data accessed by the account in the last 24 hours.
+
+
+*False positive analysis*
+
+
+- False positives may occur due to the intended usage of the service. Tuning is needed in order to have higher confidence. Consider adding exceptions — preferably with a combination of user agent and IP address conditions.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Disable or limit the account during the investigation and response.
+- Identify the possible impact of the incident and prioritize accordingly; the following actions can help you gain context:
+    - Identify the account role in the cloud environment.
+    - Assess the criticality of affected services and servers.
+    - Work with your IT team to identify and minimize the impact on users.
+    - Identify if the attacker is moving laterally and compromising other accounts, servers, or services.
+    - Identify any regulatory or legal ramifications related to this activity.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Rotate secrets or delete API keys as needed to revoke the attacker's access to the environment. Work with your IT teams to minimize the impact on business operations during these actions.
+- Check if unauthorized new users were created, remove unauthorized new accounts, and request password resets for other IAM users.
+- Consider enabling multi-factor authentication for users.
+- Review the permissions assigned to the implicated user to ensure that the least privilege principle is being followed.
+- Implement security best practices https://aws.amazon.com/premiumsupport/knowledge-center/security-best-practices/[outlined] by AWS.
+- Take the actions needed to return affected systems, data, or services to their normal operational levels.
+- Identify the initial vector abused by the attacker and take action to prevent reinfection via the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+==== Setup
+
+
+The AWS Fleet integration, Filebeat module, or similarly structured data is required to be compatible with this rule.
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset:aws.cloudtrail and event.provider:secretsmanager.amazonaws.com and
+    event.action:GetSecretValue and event.outcome:success and aws.cloudtrail.user_identity.session_context.session_issuer.type: Role and
+    not user_agent.name: ("Chrome" or "Firefox" or "Safari" or "Edge" or "Brave" or "Opera")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Credential Access
+** ID: TA0006
+** Reference URL: https://attack.mitre.org/tactics/TA0006/
+* Technique:
+** Name: Steal Application Access Token
+** ID: T1528
+** Reference URL: https://attack.mitre.org/techniques/T1528/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-first-time-seen-driver-loaded.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-first-time-seen-driver-loaded.asciidoc
new file mode 100644
index 0000000000..bb5657737e
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-first-time-seen-driver-loaded.asciidoc
@@ -0,0 +1,153 @@
+[[prebuilt-rule-8-11-17-first-time-seen-driver-loaded]]
+=== First Time Seen Driver Loaded
+
+Identifies the load of a driver with an original file name and signature values that were observed for the first time during the last 30 days. This rule type can help baseline drivers installation within your environment.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.library-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/kr/security-labs/stopping-vulnerable-driver-attacks
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Privilege Escalation
+* Tactic: Persistence
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 8
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating First Time Seen Driver Loaded*
+
+
+A driver is a software component that allows the operating system to communicate with hardware devices. It works at a high privilege level, the kernel level, having high control over the system's security and stability.
+
+Attackers may exploit known good but vulnerable drivers to execute code in their context because once an attacker can execute code in the kernel, security tools can no longer effectively protect the host. They can leverage these drivers to tamper, bypass and terminate security software, elevate privileges, create persistence mechanisms, and disable operating system protections and monitoring features. Attackers were seen in the wild conducting these actions before acting on their objectives, such as ransomware.
+
+Read the complete research on "Stopping Vulnerable Driver Attacks" done by Elastic Security Labs https://www.elastic.co/kr/security-labs/stopping-vulnerable-driver-attacks[here].
+
+This rule identifies the load of a driver with an original file name and signature values observed for the first time during the last 30 days. This rule type can help baseline drivers installation within your environment.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Examine the driver loaded to identify potentially suspicious characteristics. The following actions can help you gain context:
+  - Identify the path that the driver was loaded from. If using Elastic Defend, this information can be found in the `dll.path` field.
+  - Examine the digital signature of the driver, and check if it's valid.
+  - Examine the creation and modification timestamps of the file:
+    - On Elastic Defend, those can be found in the `dll.Ext.relative_file_creation_time` and `"dll.Ext.relative_file_name_modify_time"` fields, with the values being seconds.
+    - Search for file creation events sharing the same file name as the `dll.name` field and identify the process responsible for the operation.
+      - Investigate any other abnormal behavior by the subject process, such as network connections, registry or file modifications, and any spawned child processes.
+  - Use the driver SHA-256 (`dll.hash.sha256` field) hash value to search for the existence and reputation in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+- Use Osquery to investigate the drivers loaded into the system.
+  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+- Identify the driver's `Device Name` and `Service Name`.
+- Check for alerts from the rules specified in the `Related Rules` section.
+
+
+*False positive analysis*
+
+
+- Matches derived from these rules are not inherently malicious. The security team should investigate them to ensure they are legitimate and needed, then include them in an allowlist only if required. The security team should address any vulnerable driver installation as it can put the user and the domain at risk.
+
+
+*Related Rules*
+
+
+- Untrusted Driver Loaded - d8ab1ec1-feeb-48b9-89e7-c12e189448aa
+- Code Signing Policy Modification Through Registry - da7733b1-fe08-487e-b536-0a04c6d8b0cd
+- Code Signing Policy Modification Through Built-in tools - b43570de-a908-4f7f-8bdb-b2df6ffd8c80
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Disable and uninstall all suspicious drivers found in the system. This can be done via Device Manager. (Note that this step may require you to boot the system into Safe Mode)
+- Remove the related services and registry keys found in the system. Note that the service will probably not stop if the driver is still installed.
+  - This can be done via PowerShell `Remove-Service` cmdlet.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Ensure that the Driver Signature Enforcement is enabled on the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.category:"driver" and host.os.type:windows and event.action:"load"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Exploitation for Privilege Escalation
+** ID: T1068
+** Reference URL: https://attack.mitre.org/techniques/T1068/
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Windows Service
+** ID: T1543.003
+** Reference URL: https://attack.mitre.org/techniques/T1543/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-github-protected-branch-settings-changed.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-github-protected-branch-settings-changed.asciidoc
new file mode 100644
index 0000000000..c66bab47cf
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-github-protected-branch-settings-changed.asciidoc
@@ -0,0 +1,63 @@
+[[prebuilt-rule-8-11-17-github-protected-branch-settings-changed]]
+=== GitHub Protected Branch Settings Changed
+
+This rule detects setting modifications for protected branches of a GitHub repository. Branch protection rules can be used to enforce certain workflows or requirements before a contributor can push changes to a branch in your repository. Changes to these protected branch settings should be investigated and verified as legitimate activity. Unauthorized changes could be used to lower your organization's security posture and leave you exposed for future attacks.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-github.audit-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Cloud
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Github
+
+*Version*: 3
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+configuration where event.dataset == "github.audit" 
+  and github.category == "protected_branch" and event.type == "change"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Tools
+** ID: T1562.001
+** Reference URL: https://attack.mitre.org/techniques/T1562/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-mean-of-process-arguments-in-an-rdp-session.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-mean-of-process-arguments-in-an-rdp-session.asciidoc
new file mode 100644
index 0000000000..d307eeda13
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-mean-of-process-arguments-in-an-rdp-session.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-high-mean-of-process-arguments-in-an-rdp-session]]
+=== High Mean of Process Arguments in an RDP Session
+
+A machine learning job has detected unusually high number of process arguments in an RDP session. Executing sophisticated attacks such as lateral movement can involve the use of complex commands, obfuscation mechanisms, redirection and piping, which in turn increases the number of arguments in a command.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-12h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows RDP process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-mean-of-rdp-session-duration.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-mean-of-rdp-session-duration.asciidoc
new file mode 100644
index 0000000000..6486a2165a
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-mean-of-rdp-session-duration.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-high-mean-of-rdp-session-duration]]
+=== High Mean of RDP Session Duration
+
+A machine learning job has detected unusually high mean of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-12h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows RDP process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-variance-in-rdp-session-duration.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-variance-in-rdp-session-duration.asciidoc
new file mode 100644
index 0000000000..60b287d2b3
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-high-variance-in-rdp-session-duration.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-high-variance-in-rdp-session-duration]]
+=== High Variance in RDP Session Duration
+
+A machine learning job has detected unusually high variance of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-12h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows RDP process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc
new file mode 100644
index 0000000000..a45cdbb515
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc
@@ -0,0 +1,124 @@
+[[prebuilt-rule-8-11-17-insecure-aws-ec2-vpc-security-group-ingress-rule-added]]
+=== Insecure AWS EC2 VPC Security Group Ingress Rule Added
+
+Identifies when a specified inbound (ingress) rule is added or adjusted for a VPC security group in AWS EC2. This rule detects when a security group rule is added that allows traffic from any IP address or from a specific IP address to common remote access ports, such as 22 (SSH) or 3389 (RDP). Adversaries may add these rules to allow remote access to VPC instances from any location, increasing the attack surface and potentially exposing the instances to unauthorized access.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 10m
+
+*Searches indices from*: now-60m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/AWSEC2/latest/APIReference/API_AuthorizeSecurityGroupEgress.html
+* https://docs.aws.amazon.com/AWSEC2/latest/APIReference/API_AuthorizeSecurityGroupIngress.html
+* https://www.linkedin.com/pulse/my-backdoors-your-aws-infrastructure-part-3-network-micha%C5%82-brygidyn/
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: AWS EC2
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+
+*Version*: 1
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and Analysis*
+
+
+
+*Investigating Insecure AWS EC2 VPC Security Group Ingress Rule Added*
+
+
+This rule detects the addition of ingress rules to a VPC security group that allow traffic from any IP address (`0.0.0.0/0` or `::/0`) to sensitive ports commonly used for remote access, such as SSH (port 22) and RDP (port 3389). This configuration change can significantly increase the exposure of EC2 instances to potential threats, making it crucial to understand the context and legitimacy of such changes.
+
+
+*Possible Investigation Steps:*
+
+
+- **Identify the Actor**: Review the `aws.cloudtrail.user_identity.arn` and `aws.cloudtrail.user_identity.access_key_id` fields to identify who made the change. Investigate whether this actor has the necessary permissions and typically performs these actions.
+- **Review the Request Details**: Examine the `aws.cloudtrail.request_parameters` to understand exactly what changes were made to the security group. Check for any unusual parameters that could suggest a misconfiguration or malicious intent.
+- **Analyze the Source of the Request**: Look at the `source.ip` and `source.geo` fields to determine the geographical origin of the request. An external or unusual location could indicate compromised credentials.
+- **Contextualize with Timestamp**: Use the `@timestamp` field to check when the change occurred. Modifications outside of typical business hours might warrant additional scrutiny.
+- **Correlate with Other Activities**: Search for related CloudTrail events before and after this change to see if the same actor engaged in other potentially suspicious activities.
+
+
+*False Positive Analysis:*
+
+
+- **Legitimate Administrative Actions**: Verify if the ingress rule change aligns with scheduled updates, maintenance activities, or legitimate administrative tasks documented in change management tickets or systems.
+- **Consistency Check**: Compare the action against historical data of similar actions performed by the user or within the organization. Consistency with past legitimate actions might indicate a false alarm.
+- **Verify through Outcomes**: Check the `aws.cloudtrail.response_elements` and the `event.outcome` to confirm if the change was successful and intended as per policy.
+
+
+*Response and Remediation:*
+
+
+- **Immediate Review and Reversal if Necessary**: If the change was unauthorized, revert the security group rules to their previous state to close any unintended access.
+- **Enhance Monitoring and Alerts**: Adjust monitoring systems to alert on similar security group changes, especially those that open access to well-known ports from any IP address.
+- **Educate and Train**: Provide additional training to users with administrative rights on the importance of security best practices concerning security group management.
+- **Audit Security Groups and Policies**: Conduct a comprehensive audit of all security groups and associated policies to ensure they adhere to the principle of least privilege.
+- **Incident Response**: If there's an indication of malicious intent or a security breach, initiate the incident response protocol to mitigate any damage and prevent future occurrences.
+
+
+*Additional Information:*
+
+
+For further guidance on managing security group rules and securing AWS environments, refer to the https://docs.aws.amazon.com/vpc/latest/userguide/VPC_SecurityGroups.html[Amazon VPC Security Groups documentation] and AWS best practices for security.
+
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset: "aws.cloudtrail"
+    and event.provider: ec2.amazonaws.com
+    and event.action: AuthorizeSecurityGroupIngress
+    and event.outcome: success
+    and aws.cloudtrail.flattened.request_parameters.cidrIp: ("0.0.0.0/0" or "::/0")
+    and aws.cloudtrail.flattened.request_parameters.fromPort: (
+        21 or 22 or 23 or 445 or 3389 or 5985 or 5986)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Cloud Firewall
+** ID: T1562.007
+** Reference URL: https://attack.mitre.org/techniques/T1562/007/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-kirbi-file-creation.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-kirbi-file-creation.asciidoc
new file mode 100644
index 0000000000..c0d3f2d8d4
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-kirbi-file-creation.asciidoc
@@ -0,0 +1,67 @@
+[[prebuilt-rule-8-11-17-kirbi-file-creation]]
+=== Kirbi File Creation
+
+Identifies the creation of .kirbi files. The creation of this kind of file is an indicator of an attacker running Kerberos ticket dump utilities, such as Mimikatz, and precedes attacks such as Pass-The-Ticket (PTT), which allows the attacker to impersonate users using Kerberos tickets.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.file-*
+* logs-windows.sysmon_operational-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Credential Access
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 107
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "windows" and event.type == "creation" and file.extension : "kirbi"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Credential Access
+** ID: TA0006
+** Reference URL: https://attack.mitre.org/tactics/TA0006/
+* Technique:
+** Name: OS Credential Dumping
+** ID: T1003
+** Reference URL: https://attack.mitre.org/techniques/T1003/
+* Technique:
+** Name: Steal or Forge Kerberos Tickets
+** ID: T1558
+** Reference URL: https://attack.mitre.org/techniques/T1558/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-local-account-tokenfilter-policy-disabled.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-local-account-tokenfilter-policy-disabled.asciidoc
new file mode 100644
index 0000000000..3b2479ab06
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-local-account-tokenfilter-policy-disabled.asciidoc
@@ -0,0 +1,91 @@
+[[prebuilt-rule-8-11-17-local-account-tokenfilter-policy-disabled]]
+=== Local Account TokenFilter Policy Disabled
+
+Identifies registry modification to the LocalAccountTokenFilterPolicy policy. If this value exists (which doesn't by default) and is set to 1, then remote connections from all local members of Administrators are granted full high-integrity tokens during negotiation.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.stigviewer.com/stig/windows_server_2008_r2_member_server/2014-04-02/finding/V-36439
+* https://posts.specterops.io/pass-the-hash-is-dead-long-live-localaccounttokenfilterpolicy-506c25a7c167
+* https://www.welivesecurity.com/wp-content/uploads/2018/01/ESET_Turla_Mosquito.pdf
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Tactic: Lateral Movement
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 110
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and registry.path : (
+  "HKLM\\*\\LocalAccountTokenFilterPolicy",
+  "\\REGISTRY\\MACHINE\\*\\LocalAccountTokenFilterPolicy",
+  "MACHINE\\*\\LocalAccountTokenFilterPolicy") and
+  registry.data.strings : ("1", "0x00000001")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Use Alternate Authentication Material
+** ID: T1550
+** Reference URL: https://attack.mitre.org/techniques/T1550/
+* Sub-technique:
+** Name: Pass the Hash
+** ID: T1550.002
+** Reference URL: https://attack.mitre.org/techniques/T1550/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain.asciidoc
new file mode 100644
index 0000000000..ee7d6eaad2
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain.asciidoc
@@ -0,0 +1,103 @@
+[[prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain]]
+=== Machine Learning Detected a DNS Request Predicted to be a DGA Domain
+
+A supervised machine learning model has identified a DNS question name that is predicted to be the result of a Domain Generation Algorithm (DGA), which could indicate command and control network activity.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* logs-network_traffic.*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-10m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/dga
+* https://www.elastic.co/security-labs/detect-domain-generation-algorithm-activity-with-new-kibana-integration
+
+*Tags*: 
+
+* Domain: Network
+* Domain: Endpoint
+* Data Source: Elastic Defend
+* Use Case: Domain Generation Algorithm Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Command and Control
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Domain Generation Algorithm (DGA) Detection integration assets to be installed, as well as DNS events collected by integrations such as Elastic Defend, Network Packet Capture, or Packetbeat.  
+
+
+*DGA Detection Setup*
+
+The DGA Detection integration consists of an ML-based framework to detect DGA activity in DNS events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for DGA Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- DNS events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend], https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration, or https://www.elastic.co/guide/en/beats/packetbeat/current/packetbeat-overview.html[Packetbeat].
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+- To set up and run Packetbeat, follow https://www.elastic.co/guide/en/beats/packetbeat/current/setting-up-and-running.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the DGA Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Domain Generation Algorithm Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+ml_is_dga.malicious_prediction:1 and not dns.question.registered_domain:avsvmcloud.com
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Dynamic Resolution
+** ID: T1568
+** Reference URL: https://attack.mitre.org/techniques/T1568/
+* Sub-technique:
+** Name: Domain Generation Algorithms
+** ID: T1568.002
+** Reference URL: https://attack.mitre.org/techniques/T1568/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-with-a-high-dga-probability-score.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-with-a-high-dga-probability-score.asciidoc
new file mode 100644
index 0000000000..8a6fa09454
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-with-a-high-dga-probability-score.asciidoc
@@ -0,0 +1,103 @@
+[[prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-with-a-high-dga-probability-score]]
+=== Machine Learning Detected a DNS Request With a High DGA Probability Score
+
+A supervised machine learning model has identified a DNS question name with a high probability of sourcing from a Domain Generation Algorithm (DGA), which could indicate command and control network activity.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* logs-network_traffic.*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-10m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/dga
+* https://www.elastic.co/security-labs/detect-domain-generation-algorithm-activity-with-new-kibana-integration
+
+*Tags*: 
+
+* Domain: Network
+* Domain: Endpoint
+* Data Source: Elastic Defend
+* Use Case: Domain Generation Algorithm Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Command and Control
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Domain Generation Algorithm (DGA) Detection integration assets to be installed, as well as DNS events collected by integrations such as Elastic Defend, Network Packet Capture, or Packetbeat.  
+
+
+*DGA Detection Setup*
+
+The DGA Detection integration consists of an ML-based framework to detect DGA activity in DNS events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for DGA Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- DNS events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend], https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration, or https://www.elastic.co/guide/en/beats/packetbeat/current/packetbeat-overview.html[Packetbeat].
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+- To set up and run Packetbeat, follow https://www.elastic.co/guide/en/beats/packetbeat/current/setting-up-and-running.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the DGA Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Domain Generation Algorithm Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+ml_is_dga.malicious_probability > 0.98
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Dynamic Resolution
+** ID: T1568
+** Reference URL: https://attack.mitre.org/techniques/T1568/
+* Sub-technique:
+** Name: Domain Generation Algorithms
+** ID: T1568.002
+** Reference URL: https://attack.mitre.org/techniques/T1568/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity.asciidoc
new file mode 100644
index 0000000000..5fe8c557b3
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity.asciidoc
@@ -0,0 +1,102 @@
+[[prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity]]
+=== Machine Learning Detected a Suspicious Windows Event Predicted to be Malicious Activity
+
+A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* endgame-*
+* logs-endpoint.events.process-*
+* winlogbeat-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-10m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/problemchild
+* https://www.elastic.co/security-labs/detecting-living-off-the-land-attacks-with-new-elastic-integration
+
+*Tags*: 
+
+* OS: Windows
+* Data Source: Elastic Endgame
+* Use Case: Living off the Land Attack Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Defense Evasion
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Living off the Land (LotL) Attack Detection integration assets to be installed, as well as Windows process events collected by integrations such as Elastic Defend or Winlogbeat.  
+
+
+*LotL Attack Detection Setup*
+
+The LotL Attack Detection integration detects living-off-the-land activity in Windows process events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for LotL Attack Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration or Winlogbeat(https://www.elastic.co/guide/en/beats/winlogbeat/current/_winlogbeat_overview.html).
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To set up and run Winlogbeat, follow https://www.elastic.co/guide/en/beats/winlogbeat/current/winlogbeat-installation-configuration.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the LotL Attack Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where (problemchild.prediction == 1 or blocklist_label == 1) and not process.args : ("*C:\\WINDOWS\\temp\\nessus_*.txt*", "*C:\\WINDOWS\\temp\\nessus_*.tmp*")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Sub-technique:
+** Name: Masquerade Task or Service
+** ID: T1036.004
+** Reference URL: https://attack.mitre.org/techniques/T1036/004/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score.asciidoc
new file mode 100644
index 0000000000..1747a4a54a
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score.asciidoc
@@ -0,0 +1,103 @@
+[[prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score]]
+=== Machine Learning Detected a Suspicious Windows Event with a High Malicious Probability Score
+
+A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* endgame-*
+* logs-endpoint.events.process-*
+* winlogbeat-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-10m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/problemchild
+* https://www.elastic.co/security-labs/detecting-living-off-the-land-attacks-with-new-elastic-integration
+
+*Tags*: 
+
+* OS: Windows
+* Data Source: Elastic Endgame
+* Use Case: Living off the Land Attack Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Defense Evasion
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Living off the Land (LotL) Attack Detection integration assets to be installed, as well as Windows process events collected by integrations such as Elastic Defend or Winlogbeat.  
+
+
+*LotL Attack Detection Setup*
+
+The LotL Attack Detection integration detects living-off-the-land activity in Windows process events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for LotL Attack Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration or Winlogbeat(https://www.elastic.co/guide/en/beats/winlogbeat/current/_winlogbeat_overview.html).
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To set up and run Winlogbeat, follow https://www.elastic.co/guide/en/beats/winlogbeat/current/winlogbeat-installation-configuration.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the LotL Attack Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where ((problemchild.prediction == 1 and problemchild.prediction_probability > 0.98) or
+blocklist_label == 1) and not process.args : ("*C:\\WINDOWS\\temp\\nessus_*.txt*", "*C:\\WINDOWS\\temp\\nessus_*.tmp*")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Sub-technique:
+** Name: Masquerade Task or Service
+** ID: T1036.004
+** Reference URL: https://attack.mitre.org/techniques/T1036/004/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain.asciidoc
new file mode 100644
index 0000000000..5521f0e06b
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain.asciidoc
@@ -0,0 +1,103 @@
+[[prebuilt-rule-8-11-17-machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain]]
+=== Machine Learning Detected DGA activity using a known SUNBURST DNS domain
+
+A supervised machine learning model has identified a DNS question name that used by the SUNBURST malware and is predicted to be the result of a Domain Generation Algorithm.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* logs-network_traffic.*
+
+*Severity*: critical
+
+*Risk score*: 99
+
+*Runs every*: 5m
+
+*Searches indices from*: now-10m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/dga
+* https://www.elastic.co/security-labs/detect-domain-generation-algorithm-activity-with-new-kibana-integration
+
+*Tags*: 
+
+* Domain: Network
+* Domain: Endpoint
+* Data Source: Elastic Defend
+* Use Case: Domain Generation Algorithm Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Command and Control
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Domain Generation Algorithm (DGA) Detection integration assets to be installed, as well as DNS events collected by integrations such as Elastic Defend, Network Packet Capture, or Packetbeat.  
+
+
+*DGA Detection Setup*
+
+The DGA Detection integration consists of an ML-based framework to detect DGA activity in DNS events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for DGA Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- DNS events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend], https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration, or https://www.elastic.co/guide/en/beats/packetbeat/current/packetbeat-overview.html[Packetbeat].
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+- To set up and run Packetbeat, follow https://www.elastic.co/guide/en/beats/packetbeat/current/setting-up-and-running.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the DGA Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Domain Generation Algorithm Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+ml_is_dga.malicious_prediction:1 and dns.question.registered_domain:avsvmcloud.com
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Dynamic Resolution
+** ID: T1568
+** Reference URL: https://attack.mitre.org/techniques/T1568/
+* Sub-technique:
+** Name: Domain Generation Algorithms
+** ID: T1568.002
+** Reference URL: https://attack.mitre.org/techniques/T1568/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-microsoft-windows-defender-tampering.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-microsoft-windows-defender-tampering.asciidoc
new file mode 100644
index 0000000000..8511ba6efe
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-microsoft-windows-defender-tampering.asciidoc
@@ -0,0 +1,171 @@
+[[prebuilt-rule-8-11-17-microsoft-windows-defender-tampering]]
+=== Microsoft Windows Defender Tampering
+
+Identifies when one or more features on Microsoft Defender are disabled. Adversaries may disable or tamper with Microsoft Defender features to evade detection and conceal malicious behavior.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://thedfirreport.com/2021/10/18/icedid-to-xinglocker-ransomware-in-24-hours/
+* https://www.tenforums.com/tutorials/32236-enable-disable-microsoft-defender-pua-protection-windows-10-a.html
+* https://www.tenforums.com/tutorials/104025-turn-off-core-isolation-memory-integrity-windows-10-a.html
+* https://www.tenforums.com/tutorials/105533-enable-disable-windows-defender-exploit-protection-settings.html
+* https://www.tenforums.com/tutorials/123792-turn-off-tamper-protection-microsoft-defender-antivirus.html
+* https://www.tenforums.com/tutorials/51514-turn-off-microsoft-defender-periodic-scanning-windows-10-a.html
+* https://www.tenforums.com/tutorials/3569-turn-off-real-time-protection-microsoft-defender-antivirus.html
+* https://www.tenforums.com/tutorials/99576-how-schedule-scan-microsoft-defender-antivirus-windows-10-a.html
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 111
+
+*Rule authors*: 
+
+* Austin Songer
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Microsoft Windows Defender Tampering*
+
+
+Microsoft Windows Defender is an antivirus product built into Microsoft Windows, which makes it popular across multiple environments. Disabling it is a common step in threat actor playbooks.
+
+This rule monitors the registry for modifications that disable Windows Defender features.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Examine which features have been disabled, and check if this operation is done under change management and approved according to the organization's policy.
+
+
+*False positive analysis*
+
+
+- This mechanism can be used legitimately. Analysts can dismiss the alert if the administrator is aware of the activity, the configuration is justified (for example, it is being used to deploy other security solutions or troubleshooting), and no other suspicious activity has been observed.
+
+
+*Related rules*
+
+
+- Windows Defender Disabled via Registry Modification - 2ffa1f1e-b6db-47fa-994b-1512743847eb
+- Disabling Windows Defender Security Settings via PowerShell - c8cccb06-faf2-4cd5-886e-2c9636cfcb87
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Take actions to restore the appropriate Windows Defender antivirus configurations.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Review the privileges assigned to the user to ensure that the least privilege principle is being followed.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and event.type in ("creation", "change") and
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\PUAProtection" and
+  registry.data.strings : ("0", "0x00000000")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender Security Center\\App and Browser protection\\DisallowExploitProtectionOverride" and
+  registry.data.strings : ("0", "0x00000000")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\DisableAntiSpyware" and
+  registry.data.strings : ("1", "0x00000001")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Features\\TamperProtection" and
+  registry.data.strings : ("0", "0x00000000")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Real-Time Protection\\DisableRealtimeMonitoring" and
+  registry.data.strings : ("1", "0x00000001")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Real-Time Protection\\DisableIntrusionPreventionSystem" and
+  registry.data.strings : ("1", "0x00000001")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Real-Time Protection\\DisableScriptScanning" and
+  registry.data.strings : ("1", "0x00000001")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Windows Defender Exploit Guard\\Controlled Folder Access\\EnableControlledFolderAccess" and
+  registry.data.strings : ("0", "0x00000000")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Real-Time Protection\\DisableIOAVProtection" and
+  registry.data.strings : ("1", "0x00000001")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Reporting\\DisableEnhancedNotifications" and
+  registry.data.strings : ("1", "0x00000001")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\SpyNet\\DisableBlockAtFirstSeen" and
+  registry.data.strings : ("1", "0x00000001")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\SpyNet\\SpynetReporting" and
+  registry.data.strings : ("0", "0x00000000")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\SpyNet\\SubmitSamplesConsent" and
+  registry.data.strings : ("0", "0x00000000")) or
+  (registry.path : "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Real-Time Protection\\DisableBehaviorMonitoring" and
+  registry.data.strings : ("1", "0x00000001"))
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-mimikatz-memssp-log-file-detected.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-mimikatz-memssp-log-file-detected.asciidoc
new file mode 100644
index 0000000000..dc0b364308
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-mimikatz-memssp-log-file-detected.asciidoc
@@ -0,0 +1,140 @@
+[[prebuilt-rule-8-11-17-mimikatz-memssp-log-file-detected]]
+=== Mimikatz Memssp Log File Detected
+
+Identifies the password log file from the default Mimikatz memssp module.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.file-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/security-labs/detect-credential-access
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Credential Access
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 211
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Mimikatz Memssp Log File Detected*
+
+
+https://github.com/gentilkiwi/mimikatz[Mimikatz] is an open-source tool used to collect, decrypt, and/or use cached credentials. This tool is commonly abused by adversaries during the post-compromise stage where adversaries have gained an initial foothold on an endpoint and are looking to elevate privileges and seek out additional authentication objects such as tokens/hashes/credentials that can then be used to laterally move and pivot across a network.
+
+This rule looks for the creation of a file named `mimilsa.log`, which is generated when using the Mimikatz misc::memssp module, which injects a malicious Windows SSP to collect locally authenticated credentials, which includes the computer account password, running service credentials, and any accounts that logon.
+
+
+*Possible investigation steps*
+
+
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Investigate potentially compromised accounts. Analysts can do this by searching for login events (e.g., 4624) to the target host.
+- Retrieve and inspect the log file contents.
+- Search for DLL files created in the same location as the log file, and retrieve unsigned DLLs.
+  - Use the PowerShell Get-FileHash cmdlet to get the SHA-256 hash value of these files.
+    - Search for the existence of these files in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+  - Identify the process that created the DLL using file creation events.
+
+
+*False positive analysis*
+
+
+- This file name `mimilsa.log` should not legitimately be created.
+
+
+*Related rules*
+
+
+- Mimikatz Powershell Module Activity - ac96ceb8-4399-4191-af1d-4feeac1f1f46
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- If the host is a Domain Controller (DC):
+  - Activate your incident response plan for total Active Directory compromise.
+  - Review the privileges assigned to users that can access the DCs to ensure that the least privilege principle is being followed and reduce the attack surface.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Reboot the host to remove the injected SSP from memory.
+- Reimage the host operating system or restore compromised files to clean versions.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "windows" and file.name : "mimilsa.log" and process.name : "lsass.exe"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Credential Access
+** ID: TA0006
+** Reference URL: https://attack.mitre.org/tactics/TA0006/
+* Technique:
+** Name: OS Credential Dumping
+** ID: T1003
+** Reference URL: https://attack.mitre.org/techniques/T1003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-modification-of-amsienable-registry-key.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-modification-of-amsienable-registry-key.asciidoc
new file mode 100644
index 0000000000..068de73e73
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-modification-of-amsienable-registry-key.asciidoc
@@ -0,0 +1,162 @@
+[[prebuilt-rule-8-11-17-modification-of-amsienable-registry-key]]
+=== Modification of AmsiEnable Registry Key
+
+Identifies modifications of the AmsiEnable registry key to 0, which disables the Antimalware Scan Interface (AMSI). An adversary can modify this key to disable AMSI protections.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://hackinparis.com/data/slides/2019/talks/HIP2019-Dominic_Chell-Cracking_The_Perimeter_With_Sharpshooter.pdf
+* https://docs.microsoft.com/en-us/windows/win32/amsi/antimalware-scan-interface-portal
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 111
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Modification of AmsiEnable Registry Key*
+
+
+The Windows Antimalware Scan Interface (AMSI) is a versatile interface standard that allows your applications and services to integrate with any antimalware product on a machine. AMSI integrates with multiple Windows components, ranging from User Account Control (UAC) to VBA macros and PowerShell.
+
+Since AMSI is widely used across security products for increased visibility, attackers can disable it to evade detections that rely on it.
+
+This rule monitors the modifications to the Software\Microsoft\Windows Script\Settings\AmsiEnable registry key.
+
+
+*Possible investigation steps*
+
+
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Investigate the execution of scripts and macros after the registry modification.
+- Retrieve scripts or Microsoft Office files and determine if they are malicious:
+  - Use a private sandboxed malware analysis system to perform analysis.
+    - Observe and collect information about the following activities:
+      - Attempts to contact external domains and addresses.
+      - File and registry access, modification, and creation activities.
+      - Service creation and launch activities.
+      - Scheduled task creation.
+  - Use the PowerShell Get-FileHash cmdlet to get the files' SHA-256 hash values.
+    - Search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Use process name, command line, and file hash to search for occurrences on other hosts.
+
+
+*False positive analysis*
+
+
+- This modification should not happen legitimately. Any potential benign true positive (B-TP) should be mapped and monitored by the security team as these modifications expose the host to malware infections.
+
+
+*Related rules*
+
+
+- Microsoft Windows Defender Tampering - fe794edd-487f-4a90-b285-3ee54f2af2d3
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Delete or set the key to its default value.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and event.type in ("creation", "change") and
+  registry.path : (
+    "HKEY_USERS\\*\\Software\\Microsoft\\Windows Script\\Settings\\AmsiEnable",
+    "HKU\\*\\Software\\Microsoft\\Windows Script\\Settings\\AmsiEnable",
+    "\\REGISTRY\\USER\\*\\Software\\Microsoft\\Windows Script\\Settings\\AmsiEnable"
+  ) and
+  registry.data.strings: ("0", "0x00000000")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Tools
+** ID: T1562.001
+** Reference URL: https://attack.mitre.org/techniques/T1562/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-network-activity-detected-via-kworker.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-network-activity-detected-via-kworker.asciidoc
new file mode 100644
index 0000000000..ef8a81fc2c
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-network-activity-detected-via-kworker.asciidoc
@@ -0,0 +1,124 @@
+[[prebuilt-rule-8-11-17-network-activity-detected-via-kworker]]
+=== Network Activity Detected via Kworker
+
+This rule monitors for network connections from a kworker process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Command and Control
+* Data Source: Elastic Defend
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows
+the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest to select "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type:linux and event.category:network and event.action:(connection_attempted or connection_accepted) and 
+process.name:kworker* and not destination.ip:(
+  10.0.0.0/8 or
+  127.0.0.0/8 or
+  169.254.0.0/16 or
+  172.16.0.0/12 or
+  192.168.0.0/16 or
+  224.0.0.0/4 or
+  "::1" or
+  "FE80::/10" or
+  "FF00::/8"
+) and not destination.port:2049
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Rootkit
+** ID: T1014
+** Reference URL: https://attack.mitre.org/techniques/T1014/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Tactic:
+** Name: Exfiltration
+** ID: TA0010
+** Reference URL: https://attack.mitre.org/tactics/TA0010/
+* Technique:
+** Name: Exfiltration Over C2 Channel
+** ID: T1041
+** Reference URL: https://attack.mitre.org/techniques/T1041/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-new-systemd-service-created-by-previously-unknown-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-new-systemd-service-created-by-previously-unknown-process.asciidoc
new file mode 100644
index 0000000000..ba38462edf
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-new-systemd-service-created-by-previously-unknown-process.asciidoc
@@ -0,0 +1,220 @@
+[[prebuilt-rule-8-11-17-new-systemd-service-created-by-previously-unknown-process]]
+=== New Systemd Service Created by Previously Unknown Process
+
+Systemd service files are configuration files in Linux systems used to define and manage system services. Malicious actors can leverage systemd service files to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://opensource.com/article/20/7/systemd-timers
+* https://pberba.github.io/security/2022/01/30/linux-threat-hunting-for-persistence-systemd-timers-cron/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Privilege Escalation
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 10
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating New Systemd Service Created by Previously Unknown Process*
+
+
+Systemd service files are configuration files in Linux systems used to define and manage system services.
+
+Malicious actors can leverage systemd service files to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection.
+
+This rule monitors the creation of new systemd service files, potentially indicating the creation of a persistence mechanism.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the systemd service file that was created or modified.
+  - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
+- Investigate the currently enabled systemd services through the following command `sudo systemctl list-unit-files`.
+- Investigate whether any other files in any of the available systemd directories have been altered through OSQuery.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/etc/systemd/system/%' OR path LIKE '/usr/local/lib/systemd/system/%' OR path LIKE\n'/lib/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' OR path LIKE '/home/user/.config/systemd/user/%' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/etc/systemd/system/%' OR path LIKE\n'/usr/local/lib/systemd/system/%' OR path LIKE '/lib/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' OR path\nLIKE '/home/{{user.name}}/.config/systemd/user/%' )\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator who uses systemd services for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- Potential Persistence Through Run Control Detected - 0f4d35e4-925e-4959-ab24-911be207ee6f
+- Potential Persistence Through init.d Detected - 474fd20e-14cc-49c5-8160-d9ab4ba16c8b
+- New Systemd Timer Created - 7fb500fa-8e24-4bd1-9480-2a819352602c
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service/timer or restore its original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type:linux and event.category:file and event.action:("creation" or "file_create_event") and file.path:(
+  /etc/systemd/system/* or 
+  /usr/local/lib/systemd/system/* or 
+  /lib/systemd/system/* or 
+  /usr/lib/systemd/system/* or 
+  /home/*/.config/systemd/user/*
+) and 
+not (
+  process.name:(
+    "dpkg" or "dockerd" or "rpm" or "snapd" or "yum" or "exe" or "dnf" or "dnf-automatic" or python* or "puppetd" or
+    "elastic-agent" or "cinc-client" or "chef-client" or "pacman" or "puppet" or "cloudflared" or "packagekitd" or
+    "podman"
+  ) or 
+  file.extension:("swp" or "swpx")
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Systemd Service
+** ID: T1543.002
+** Reference URL: https://attack.mitre.org/techniques/T1543/002/
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Systemd Service
+** ID: T1543.002
+** Reference URL: https://attack.mitre.org/techniques/T1543/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-new-systemd-timer-created.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-new-systemd-timer-created.asciidoc
new file mode 100644
index 0000000000..5fa3b50b80
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-new-systemd-timer-created.asciidoc
@@ -0,0 +1,187 @@
+[[prebuilt-rule-8-11-17-new-systemd-timer-created]]
+=== New Systemd Timer Created
+
+Detects the creation of a systemd timer within any of the default systemd timer directories. Systemd timers can be used by an attacker to gain persistence, by scheduling the execution of a command or script. Similarly to cron/at, systemd timers can be set up to execute on boot time, or on a specific point in time, which allows attackers to regain access in case the connection to the infected asset was lost.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://opensource.com/article/20/7/systemd-timers
+* https://pberba.github.io/security/2022/01/30/linux-threat-hunting-for-persistence-systemd-timers-cron/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 10
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating New Systemd Timer Created*
+
+
+Systemd timers are used for scheduling and automating recurring tasks or services on Linux systems. 
+
+Attackers can leverage systemd timers to run scripts, commands, or malicious software at system boot or on a set time interval by creating a systemd timer and a corresponding systemd service file. 
+
+This rule monitors the creation of new systemd timer files, potentially indicating the creation of a persistence mechanism.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the timer file that was created or modified.
+  - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
+- Investigate the currently enabled systemd timers through the following command `sudo systemctl list-timers`.
+- Search for the systemd service file named similarly to the timer that was created.
+- Investigate whether any other files in any of the available systemd directories have been altered through OSQuery.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/etc/systemd/system/%' OR path LIKE '/usr/local/lib/systemd/system/%' OR path LIKE\n'/lib/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' OR path LIKE '/home/user/.config/systemd/user/%' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/etc/systemd/system/%' OR path LIKE\n'/usr/local/lib/systemd/system/%' OR path LIKE '/lib/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' OR path\nLIKE '/home/{{user.name}}/.config/systemd/user/%' )\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator who uses systemd timers for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service/timer or restore its original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type : "linux" and event.action : ("creation" or "file_create_event") and file.extension : "timer" and
+file.path : (/etc/systemd/system/* or /usr/local/lib/systemd/system/* or /lib/systemd/system/* or 
+/usr/lib/systemd/system/* or /home/*/.config/systemd/user/*) and not (
+  (process.name : (
+    "docker" or "dockerd" or "dnf" or "yum" or "rpm" or "dpkg" or "executor" or "cloudflared" or "pacman" or "podman" or 
+    "pamac-daemon"
+  ))
+  or (file.name:apt-*.timer)
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Scheduled Task/Job
+** ID: T1053
+** Reference URL: https://attack.mitre.org/techniques/T1053/
+* Sub-technique:
+** Name: Systemd Timers
+** ID: T1053.006
+** Reference URL: https://attack.mitre.org/techniques/T1053/006/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-bits-job-notify-cmdline.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-bits-job-notify-cmdline.asciidoc
new file mode 100644
index 0000000000..f99dabddc2
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-bits-job-notify-cmdline.asciidoc
@@ -0,0 +1,91 @@
+[[prebuilt-rule-8-11-17-persistence-via-bits-job-notify-cmdline]]
+=== Persistence via BITS Job Notify Cmdline
+
+An adversary can use the Background Intelligent Transfer Service (BITS) SetNotifyCmdLine method to execute a program that runs after a job finishes transferring data or after a job enters a specified state in order to persist on a system.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.process-*
+* winlogbeat-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://pentestlab.blog/2019/10/30/persistence-bits-jobs/
+* https://docs.microsoft.com/en-us/windows/win32/api/bits1_5/nf-bits1_5-ibackgroundcopyjob2-setnotifycmdline
+* https://docs.microsoft.com/en-us/windows-server/administration/windows-commands/bitsadmin-setnotifycmdline
+* https://www.elastic.co/blog/hunting-for-persistence-using-elastic-security-part-2
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 209
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  process.parent.name : "svchost.exe" and process.parent.args : "BITS" and
+  not process.executable :
+              ("?:\\Windows\\System32\\WerFaultSecure.exe",
+               "?:\\Windows\\System32\\WerFault.exe",
+               "?:\\Windows\\System32\\wermgr.exe",
+               "?:\\WINDOWS\\system32\\directxdatabaseupdater.exe")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: BITS Jobs
+** ID: T1197
+** Reference URL: https://attack.mitre.org/techniques/T1197/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-kde-autostart-script-or-desktop-file-modification.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-kde-autostart-script-or-desktop-file-modification.asciidoc
new file mode 100644
index 0000000000..5fb12dab55
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-kde-autostart-script-or-desktop-file-modification.asciidoc
@@ -0,0 +1,214 @@
+[[prebuilt-rule-8-11-17-persistence-via-kde-autostart-script-or-desktop-file-modification]]
+=== Persistence via KDE AutoStart Script or Desktop File Modification
+
+Identifies the creation or modification of a K Desktop Environment (KDE) AutoStart script or desktop file that will execute upon each user logon. Adversaries may abuse this method for persistence.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* auditbeat-*
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://userbase.kde.org/System_Settings/Autostart
+* https://www.amnesty.org/en/latest/research/2020/09/german-made-finspy-spyware-found-in-egypt-and-mac-and-linux-versions-revealed/
+* https://www.intezer.com/blog/research/operation-electrorat-attacker-creates-fake-companies-to-drain-your-crypto-wallets/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 111
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Persistence via KDE AutoStart Script or Desktop File Modification*
+
+
+K Desktop Environment (KDE) is a popular graphical desktop environment for Linux systems. It supports AutoStart scripts and desktop files that execute automatically upon user logon.
+
+Adversaries may exploit this feature to maintain persistence on a compromised system by creating or modifying these files.
+
+The detection rule 'Persistence via KDE AutoStart Script or Desktop File Modification' is designed to identify such activities by monitoring file events on Linux systems. It specifically targets the creation or modification of files with extensions ".sh" or ".desktop" in various AutoStart directories. By detecting these events, the rule helps security analysts identify potential abuse of KDE AutoStart functionality by malicious actors.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible investigation steps*
+
+
+- Investigate the file that was created or modified.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/home/%/.config/autostart/%.sh' OR path LIKE '/home/%/.config/autostart/%.desktop'\nOR path LIKE '/root/.config/autostart/%.sh' OR path LIKE '/root/.config/autostart/%.desktop' OR path LIKE\n'/home/%/.kde/Autostart/%.sh' OR path LIKE '/home/%/.kde/Autostart/%.desktop' OR path LIKE '/root/.kde/Autostart/%.sh'\nOR path LIKE '/root/.kde/Autostart/%.desktop' OR path LIKE '/home/%/.kde4/Autostart/%.sh' OR path LIKE\n'/home/%/.kde4/Autostart/%.desktop' OR path LIKE '/root/.kde4/Autostart/%.sh' OR path LIKE\n'/root/.kde4/Autostart/%.desktop' OR path LIKE '/home/%/.kde/share/autostart/%.sh' OR path LIKE\n'/home/%/.kde/share/autostart/%.desktop' OR path LIKE '/root/.kde/share/autostart/%.sh' OR path LIKE\n'/root/.kde/share/autostart/%.desktop' OR path LIKE '/home/%/.kde4/share/autostart/%.sh' OR path LIKE\n'/home/%/.kde4/share/autostart/%.desktop' OR path LIKE '/root/.kde4/share/autostart/%.sh' OR path LIKE\n'/root/.kde4/share/autostart/%.desktop' OR path LIKE '/home/%/.local/share/autostart/%.sh' OR path LIKE\n'/home/%/.local/share/autostart/%.desktop' OR path LIKE '/root/.local/share/autostart/%.sh' OR path LIKE\n'/root/.local/share/autostart/%.desktop' OR path LIKE '/home/%/.config/autostart-scripts/%.sh' OR path LIKE\n'/home/%/.config/autostart-scripts/%.desktop' OR path LIKE '/root/.config/autostart-scripts/%.sh' OR path LIKE\n'/root/.config/autostart-scripts/%.desktop' OR path LIKE '/etc/xdg/autostart/%.sh' OR path LIKE\n'/etc/xdg/autostart/%.desktop' OR path LIKE '/usr/share/autostart/%.sh' OR path LIKE '/usr/share/autostart/%.desktop' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/home/%/.config/autostart/%.sh' OR\npath LIKE '/home/%/.config/autostart/%.desktop' OR path LIKE '/root/.config/autostart/%.sh' OR path LIKE\n'/root/.config/autostart/%.desktop' OR path LIKE '/home/%/.kde/Autostart/%.sh' OR path LIKE\n'/home/%/.kde/Autostart/%.desktop' OR path LIKE '/root/.kde/Autostart/%.sh' OR path LIKE\n'/root/.kde/Autostart/%.desktop' OR path LIKE '/home/%/.kde4/Autostart/%.sh' OR path LIKE\n'/home/%/.kde4/Autostart/%.desktop' OR path LIKE '/root/.kde4/Autostart/%.sh' OR path LIKE\n'/root/.kde4/Autostart/%.desktop' OR path LIKE '/home/%/.kde/share/autostart/%.sh' OR path LIKE\n'/home/%/.kde/share/autostart/%.desktop' OR path LIKE '/root/.kde/share/autostart/%.sh' OR path LIKE\n'/root/.kde/share/autostart/%.desktop' OR path LIKE '/home/%/.kde4/share/autostart/%.sh' OR path LIKE\n'/home/%/.kde4/share/autostart/%.desktop' OR path LIKE '/root/.kde4/share/autostart/%.sh' OR path LIKE\n'/root/.kde4/share/autostart/%.desktop' OR path LIKE '/home/%/.local/share/autostart/%.sh' OR path LIKE\n'/home/%/.local/share/autostart/%.desktop' OR path LIKE '/root/.local/share/autostart/%.sh' OR path LIKE\n'/root/.local/share/autostart/%.desktop' OR path LIKE '/home/%/.config/autostart-scripts/%.sh' OR path LIKE\n'/home/%/.config/autostart-scripts/%.desktop' OR path LIKE '/root/.config/autostart-scripts/%.sh' OR path LIKE\n'/root/.config/autostart-scripts/%.desktop' OR path LIKE '/etc/xdg/autostart/%.sh' OR path LIKE\n'/etc/xdg/autostart/%.desktop' OR path LIKE '/usr/share/autostart/%.sh' OR path LIKE '/usr/share/autostart/%.desktop' )\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False positive analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator who uses cron jobs for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Response and Remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from one of the following integrations:
+- Elastic Defend
+- Auditbeat
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+*Auditbeat Setup*
+
+Auditbeat is a lightweight shipper that you can install on your servers to audit the activities of users and processes on your systems. For example, you can use Auditbeat to collect and centralize audit events from the Linux Audit Framework. You can also use Auditbeat to detect changes to critical files, like binaries and configuration files, and identify potential security policy violations.
+
+
+*The following steps should be executed in order to add the Auditbeat on a Linux System:*
+
+- Elastic provides repositories available for APT and YUM-based distributions. Note that we provide binary packages, but no source packages.
+- To install the APT and YUM repositories follow the setup instructions in this https://www.elastic.co/guide/en/beats/auditbeat/current/setup-repositories.html[helper guide].
+- To run Auditbeat on Docker follow the setup instructions in the https://www.elastic.co/guide/en/beats/auditbeat/current/running-on-docker.html[helper guide].
+- To run Auditbeat on Kubernetes follow the setup instructions in the https://www.elastic.co/guide/en/beats/auditbeat/current/running-on-kubernetes.html[helper guide].
+- For complete “Setup and Run Auditbeat” information refer to the https://www.elastic.co/guide/en/beats/auditbeat/current/setting-up-and-running.html[helper guide].
+
+
+*Custom Ingest Pipeline*
+
+For versions <8.2, you need to add a custom ingest pipeline to populate `event.ingested` with @timestamp for non-elastic-agent indexes, like auditbeats/filebeat/winlogbeat etc. For more details to add a custom ingest pipeline refer to the https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html[guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "linux" and event.type != "deletion" and
+  file.extension in ("sh", "desktop") and
+  file.path :
+    (
+      "/home/*/.config/autostart/*", "/root/.config/autostart/*",
+      "/home/*/.kde/Autostart/*", "/root/.kde/Autostart/*",
+      "/home/*/.kde4/Autostart/*", "/root/.kde4/Autostart/*",
+      "/home/*/.kde/share/autostart/*", "/root/.kde/share/autostart/*",
+      "/home/*/.kde4/share/autostart/*", "/root/.kde4/share/autostart/*",
+      "/home/*/.local/share/autostart/*", "/root/.local/share/autostart/*",
+      "/home/*/.config/autostart-scripts/*", "/root/.config/autostart-scripts/*",
+      "/etc/xdg/autostart/*", "/usr/share/autostart/*"
+    ) and
+    not process.name in ("yum", "dpkg", "install", "dnf", "teams", "yum-cron", "dnf-automatic", "docker", "dockerd", 
+    "rpm", "pacman", "podman", "nautilus", "remmina", "cinnamon-settings.py")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Boot or Logon Autostart Execution
+** ID: T1547
+** Reference URL: https://attack.mitre.org/techniques/T1547/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-scheduled-job-creation.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-scheduled-job-creation.asciidoc
new file mode 100644
index 0000000000..1e9c45e76a
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-persistence-via-scheduled-job-creation.asciidoc
@@ -0,0 +1,98 @@
+[[prebuilt-rule-8-11-17-persistence-via-scheduled-job-creation]]
+=== Persistence via Scheduled Job Creation
+
+A job can be used to schedule programs or scripts to be executed at a specified date and time. Adversaries may abuse task scheduling functionality to facilitate initial or recurring execution of malicious code.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.file-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 210
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "windows" and event.type != "deletion" and
+  file.path : "?:\\Windows\\Tasks\\*" and file.extension : "job" and
+  not (
+    (
+      process.executable : "?:\\Program Files\\CCleaner\\CCleaner64.exe" and
+      file.path : "?:\\Windows\\Tasks\\CCleanerCrashReporting.job"
+    ) or
+    (
+      process.executable : (
+        "?:\\Program Files (x86)\\ManageEngine\\UEMS_Agent\\bin\\dcagentregister.exe",
+        "?:\\Program Files (x86)\\DesktopCentral_Agent\\bin\\dcagentregister.exe"
+      ) and
+      file.path : "?:\\Windows\\Tasks\\DCAgentUpdater.job"
+    )
+  )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Scheduled Task/Job
+** ID: T1053
+** Reference URL: https://attack.mitre.org/techniques/T1053/
+* Sub-technique:
+** Name: Scheduled Task
+** ID: T1053.005
+** Reference URL: https://attack.mitre.org/techniques/T1053/005/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-port-forwarding-rule-addition.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-port-forwarding-rule-addition.asciidoc
new file mode 100644
index 0000000000..7d339de0d8
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-port-forwarding-rule-addition.asciidoc
@@ -0,0 +1,151 @@
+[[prebuilt-rule-8-11-17-port-forwarding-rule-addition]]
+=== Port Forwarding Rule Addition
+
+Identifies the creation of a new port forwarding rule. An adversary may abuse this technique to bypass network segmentation restrictions.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.fireeye.com/blog/threat-research/2019/01/bypassing-network-restrictions-through-rdp-tunneling.html
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Command and Control
+* Tactic: Defense Evasion
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 212
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Port Forwarding Rule Addition*
+
+
+Network port forwarding is a mechanism to redirect incoming TCP connections (IPv4 or IPv6) from the local TCP port to any other port number, or even to a port on a remote computer.
+
+Attackers may configure port forwarding rules to bypass network segmentation restrictions, using the host as a jump box to access previously unreachable systems.
+
+This rule monitors the modifications to the `HKLM\SYSTEM\*ControlSet*\Services\PortProxy\v4tov4\` subkeys.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account and system owners and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+- Identify the target host IP address, check the connections originating from the host where the modification occurred, and inspect the credentials used.
+  - Investigate suspicious login activity, such as unauthorized access and logins from outside working hours and unusual locations.
+
+
+*False positive analysis*
+
+
+- This mechanism can be used legitimately. Analysts can dismiss the alert if the Administrator is aware of the activity and there are justifications for this configuration.
+- If this rule is noisy in your environment due to expected activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Delete the port forwarding rule.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and registry.path : (
+  "HKLM\\SYSTEM\\*ControlSet*\\Services\\PortProxy\\v4tov4\\*",
+  "\\REGISTRY\\MACHINE\\SYSTEM\\*ControlSet*\\Services\\PortProxy\\v4tov4\\*",
+  "MACHINE\\SYSTEM\\*ControlSet*\\Services\\PortProxy\\v4tov4\\*"
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Protocol Tunneling
+** ID: T1572
+** Reference URL: https://attack.mitre.org/techniques/T1572/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-buffer-overflow-attack-detected.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-buffer-overflow-attack-detected.asciidoc
new file mode 100644
index 0000000000..2332712f78
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-buffer-overflow-attack-detected.asciidoc
@@ -0,0 +1,86 @@
+[[prebuilt-rule-8-11-17-potential-buffer-overflow-attack-detected]]
+=== Potential Buffer Overflow Attack Detected
+
+Detects potential buffer overflow attacks by querying the "Segfault Detected" pre-built rule signal index, through a threshold rule, with a minimum number of 100 segfault alerts in a short timespan. A large amount of segfaults in a short time interval could indicate application exploitation attempts.
+
+*Rule type*: threshold
+
+*Rule indices*: 
+
+* .alerts-security.*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Privilege Escalation
+* Tactic: Initial Access
+* Use Case: Vulnerability
+* Rule Type: Higher-Order Rule
+
+*Version*: 3
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+
+This rule leverages alert data from other prebuilt detection rules to function correctly. 
+
+
+*Dependent Elastic Detection Rule Enablement*
+
+As a higher-order rule (based on other detections), this rule also requires the following prerequisite Elastic detection rule to be installed and enabled:
+- Segfault Detected (5c81fc9d-1eae-437f-ba07-268472967013)
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+kibana.alert.rule.rule_id:"5c81fc9d-1eae-437f-ba07-268472967013" and host.os.type:linux and event.kind:signal
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Exploitation for Privilege Escalation
+** ID: T1068
+** Reference URL: https://attack.mitre.org/techniques/T1068/
+* Tactic:
+** Name: Initial Access
+** ID: TA0001
+** Reference URL: https://attack.mitre.org/tactics/TA0001/
+* Technique:
+** Name: Exploit Public-Facing Application
+** ID: T1190
+** Reference URL: https://attack.mitre.org/techniques/T1190/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-destination-port.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-destination-port.asciidoc
new file mode 100644
index 0000000000..5efbe63e83
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-destination-port.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-destination-port]]
+=== Potential Data Exfiltration Activity to an Unusual Destination Port
+
+A machine learning job has detected data exfiltration to a particular destination port. Data transfer patterns that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-6h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/ded
+* https://www.elastic.co/blog/detect-data-exfiltration-activity-with-kibanas-new-integration
+
+*Tags*: 
+
+* Use Case: Data Exfiltration Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Exfiltration
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Data Exfiltration Detection integration assets to be installed, as well as network and file events collected by integrations such as Elastic Defend and Network Packet Capture (for network events only).  
+
+
+*Data Exfiltration Detection Setup*
+
+The Data Exfiltration Detection integration detects data exfiltration activity by identifying abnormalities in network and file events. Anomalies are detected using Elastic's Anomaly Detection feature. 
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Data Exfiltration Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Network events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] or https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the Data Exfiltration Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Exfiltration
+** ID: TA0010
+** Reference URL: https://attack.mitre.org/tactics/TA0010/
+* Technique:
+** Name: Exfiltration Over C2 Channel
+** ID: T1041
+** Reference URL: https://attack.mitre.org/techniques/T1041/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-ip-address.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-ip-address.asciidoc
new file mode 100644
index 0000000000..e59a29cc5d
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-ip-address.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-ip-address]]
+=== Potential Data Exfiltration Activity to an Unusual IP Address
+
+A machine learning job has detected data exfiltration to a particular geo-location (by IP address). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-6h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/ded
+* https://www.elastic.co/blog/detect-data-exfiltration-activity-with-kibanas-new-integration
+
+*Tags*: 
+
+* Use Case: Data Exfiltration Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Exfiltration
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Data Exfiltration Detection integration assets to be installed, as well as network and file events collected by integrations such as Elastic Defend and Network Packet Capture (for network events only).  
+
+
+*Data Exfiltration Detection Setup*
+
+The Data Exfiltration Detection integration detects data exfiltration activity by identifying abnormalities in network and file events. Anomalies are detected using Elastic's Anomaly Detection feature. 
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Data Exfiltration Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Network events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] or https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the Data Exfiltration Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Exfiltration
+** ID: TA0010
+** Reference URL: https://attack.mitre.org/tactics/TA0010/
+* Technique:
+** Name: Exfiltration Over C2 Channel
+** ID: T1041
+** Reference URL: https://attack.mitre.org/techniques/T1041/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-iso-code.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-iso-code.asciidoc
new file mode 100644
index 0000000000..d219c8e04c
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-iso-code.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-iso-code]]
+=== Potential Data Exfiltration Activity to an Unusual ISO Code
+
+A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-6h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/ded
+* https://www.elastic.co/blog/detect-data-exfiltration-activity-with-kibanas-new-integration
+
+*Tags*: 
+
+* Use Case: Data Exfiltration Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Exfiltration
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Data Exfiltration Detection integration assets to be installed, as well as network and file events collected by integrations such as Elastic Defend and Network Packet Capture (for network events only).  
+
+
+*Data Exfiltration Detection Setup*
+
+The Data Exfiltration Detection integration detects data exfiltration activity by identifying abnormalities in network and file events. Anomalies are detected using Elastic's Anomaly Detection feature. 
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Data Exfiltration Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Network events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] or https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the Data Exfiltration Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Exfiltration
+** ID: TA0010
+** Reference URL: https://attack.mitre.org/tactics/TA0010/
+* Technique:
+** Name: Exfiltration Over C2 Channel
+** ID: T1041
+** Reference URL: https://attack.mitre.org/techniques/T1041/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-region.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-region.asciidoc
new file mode 100644
index 0000000000..026f0f6e09
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-region.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-region]]
+=== Potential Data Exfiltration Activity to an Unusual Region
+
+A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-6h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/ded
+* https://www.elastic.co/blog/detect-data-exfiltration-activity-with-kibanas-new-integration
+
+*Tags*: 
+
+* Use Case: Data Exfiltration Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Exfiltration
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Data Exfiltration Detection integration assets to be installed, as well as network and file events collected by integrations such as Elastic Defend and Network Packet Capture (for network events only).  
+
+
+*Data Exfiltration Detection Setup*
+
+The Data Exfiltration Detection integration detects data exfiltration activity by identifying abnormalities in network and file events. Anomalies are detected using Elastic's Anomaly Detection feature. 
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Data Exfiltration Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Network events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] or https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the Data Exfiltration Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Exfiltration
+** ID: TA0010
+** Reference URL: https://attack.mitre.org/tactics/TA0010/
+* Technique:
+** Name: Exfiltration Over C2 Channel
+** ID: T1041
+** Reference URL: https://attack.mitre.org/techniques/T1041/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-dga-activity.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-dga-activity.asciidoc
new file mode 100644
index 0000000000..d3851d4c74
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-dga-activity.asciidoc
@@ -0,0 +1,93 @@
+[[prebuilt-rule-8-11-17-potential-dga-activity]]
+=== Potential DGA Activity
+
+A population analysis machine learning job detected potential DGA (domain generation algorithm) activity. Such activity is often used by malware command and control (C2) channels. This machine learning job looks for a source IP address making DNS requests that have an aggregate high probability of being DGA activity.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-45m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/dga
+* https://www.elastic.co/security-labs/detect-domain-generation-algorithm-activity-with-new-kibana-integration
+
+*Tags*: 
+
+* Use Case: Domain Generation Algorithm Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Command and Control
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Domain Generation Algorithm (DGA) Detection integration assets to be installed, as well as DNS events collected by integrations such as Elastic Defend, Network Packet Capture, or Packetbeat.  
+
+
+*DGA Detection Setup*
+
+The DGA Detection integration consists of an ML-based framework to detect DGA activity in DNS events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for DGA Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- DNS events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend], https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration, or https://www.elastic.co/guide/en/beats/packetbeat/current/packetbeat-overview.html[Packetbeat].
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+- To set up and run Packetbeat, follow https://www.elastic.co/guide/en/beats/packetbeat/current/setting-up-and-running.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the DGA Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Domain Generation Algorithm Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Anomaly Detection Setup*
+
+Before you can enable this rule, you'll need to enable the corresponding Anomaly Detection job. 
+- Go to the Kibana homepage. Under Analytics, click Machine Learning.
+- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your enriched DNS events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `logs-network_traffic.*` if you used Network Packet Capture.
+- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/dga/kibana/ml_module/dga-ml.json[this] configuration file, you will see a card for DGA under "Use preconfigured jobs".
+- Keep the default settings and click "Create jobs" to start the anomaly detection job and datafeed.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Dynamic Resolution
+** ID: T1568
+** Reference URL: https://attack.mitre.org/techniques/T1568/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-linux-backdoor-user-account-creation.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-linux-backdoor-user-account-creation.asciidoc
new file mode 100644
index 0000000000..fa9e57b260
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-linux-backdoor-user-account-creation.asciidoc
@@ -0,0 +1,168 @@
+[[prebuilt-rule-8-11-17-potential-linux-backdoor-user-account-creation]]
+=== Potential Linux Backdoor User Account Creation
+
+Identifies the attempt to create a new backdoor user by setting the user's UID to 0. Attackers may alter a user's UID to 0 to establish persistence on a system.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+* auditbeat-*
+* logs-auditd_manager.auditd-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+* Data Source: Auditd Manager
+
+*Version*: 7
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Potential Linux Backdoor User Account Creation*
+
+
+The `usermod` command is used to modify user account attributes and settings in Linux-based operating systems.
+
+Attackers may create new accounts with a UID of 0 to maintain root access to target systems without leveraging the root user account.
+
+This rule identifies the usage of the `usermod` command to set a user's UID to 0, indicating that the user becomes a root account. 
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible investigation steps*
+
+- Investigate the user account that got assigned a uid of 0, and analyze its corresponding attributes.
+  - !{osquery{"label":"Osquery - Retrieve User Accounts with a UID of 0","query":"SELECT description, gid, gid_signed, shell, uid, uid_signed, username FROM users WHERE username != 'root' AND uid LIKE\n'0'\n"}}
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+  - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+  - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+- Identify if the account was added to privileged groups or assigned special privileges after creation.
+  - !{osquery{"label":"Osquery - Retrieve Information for a Specific Group","query":"SELECT * FROM groups WHERE groupname = {{group.name}}"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Any activity that triggered the alert and is not inherently malicious must be monitored by the security team.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Review the privileges assigned to the involved users to ensure that the least privilege principle is being followed.
+- Delete the created account.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "linux" and event.type == "start" and event.action in ("exec", "exec_event", "executed", "process_started")
+ and process.name == "usermod" and process.args : "-u" and process.args : "0" and process.args : "-o"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Create Account
+** ID: T1136
+** Reference URL: https://attack.mitre.org/techniques/T1136/
+* Sub-technique:
+** Name: Local Account
+** ID: T1136.001
+** Reference URL: https://attack.mitre.org/techniques/T1136/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-network-sweep-detected.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-network-sweep-detected.asciidoc
new file mode 100644
index 0000000000..0bba01ec43
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-network-sweep-detected.asciidoc
@@ -0,0 +1,75 @@
+[[prebuilt-rule-8-11-17-potential-network-sweep-detected]]
+=== Potential Network Sweep Detected
+
+This rule identifies a potential network sweep. A network sweep is a method used by attackers to scan a target network, identifying active hosts, open ports, and available services to gather information on vulnerabilities and weaknesses. This reconnaissance helps them plan subsequent attacks and exploit potential entry points for unauthorized access, data theft, or other malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination hosts on commonly used network services.
+
+*Rule type*: threshold
+
+*Rule indices*: 
+
+* packetbeat-*
+* auditbeat-*
+* filebeat-*
+* logs-network_traffic.*
+* logs-endpoint.events.network-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 5
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Network
+* Tactic: Discovery
+* Tactic: Reconnaissance
+* Use Case: Network Security Monitoring
+
+*Version*: 6
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+destination.port : (21 or 22 or 23 or 25 or 139 or 445 or 3389 or 5985 or 5986) and
+source.ip : (10.0.0.0/8 or 172.16.0.0/12 or 192.168.0.0/16)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Discovery
+** ID: TA0007
+** Reference URL: https://attack.mitre.org/tactics/TA0007/
+* Technique:
+** Name: Network Service Discovery
+** ID: T1046
+** Reference URL: https://attack.mitre.org/techniques/T1046/
+* Tactic:
+** Name: Reconnaissance
+** ID: TA0043
+** Reference URL: https://attack.mitre.org/tactics/TA0043/
+* Technique:
+** Name: Active Scanning
+** ID: T1595
+** Reference URL: https://attack.mitre.org/techniques/T1595/
+* Sub-technique:
+** Name: Scanning IP Blocks
+** ID: T1595.001
+** Reference URL: https://attack.mitre.org/techniques/T1595/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-init-d-detected.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-init-d-detected.asciidoc
new file mode 100644
index 0000000000..998dcc5c0b
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-init-d-detected.asciidoc
@@ -0,0 +1,189 @@
+[[prebuilt-rule-8-11-17-potential-persistence-through-init-d-detected]]
+=== Potential Persistence Through init.d Detected
+
+Files that are placed in the /etc/init.d/ directory in Unix can be used to start custom applications, services, scripts or commands during start-up. Init.d has been mostly replaced in favor of Systemd. However, the "systemd-sysv-generator" can convert init.d files to service unit files that run at boot. Adversaries may add or alter files located in the /etc/init.d/ directory to execute malicious code upon boot in order to gain persistence on the system.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.intezer.com/blog/malware-analysis/hiddenwasp-malware-targeting-linux-systems/
+* https://pberba.github.io/security/2022/02/06/linux-threat-hunting-for-persistence-initialization-scripts-and-shell-configuration/#8-boot-or-logon-initialization-scripts-rc-scripts
+* https://www.cyberciti.biz/faq/how-to-enable-rc-local-shell-script-on-systemd-while-booting-linux-system/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 10
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Potential Persistence Through init.d Detected*
+
+
+The `/etc/init.d` directory is used in Linux systems to store the initialization scripts for various services and daemons that are executed during system startup and shutdown.
+
+Attackers can abuse files within the `/etc/init.d/` directory to run scripts, commands or malicious software every time a system is rebooted by converting an executable file into a service file through the `systemd-sysv-generator`. After conversion, a unit file is created within the `/run/systemd/generator.late/` directory.
+
+This rule looks for the creation of new files within the `/etc/init.d/` directory. Executable files in these directories will automatically run at boot with root privileges.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+*Possible Investigation Steps*
+
+
+- Investigate the file that was created or modified.
+  - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
+- Investigate whether any other files in the `/etc/init.d/` or `/run/systemd/generator.late/` directories have been altered.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (path LIKE '/etc/init.d/%' OR path LIKE '/run/systemd/generator.late/%')"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE (path LIKE '/etc/init.d/%' OR path LIKE\n'/run/systemd/generator.late/%')\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate syslog through the `sudo cat /var/log/syslog | grep 'LSB'` command to find traces of the LSB header of the script (if present). If syslog is being ingested into Elasticsearch, the same can be accomplished through Kibana.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate whether this activity is related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator who uses init.d for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- Suspicious File Creation in /etc for Persistence - 1c84dd64-7e6c-4bad-ac73-a5014ee37042
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the maliciously created service/init.d files or restore it to the original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type :"linux" and event.action:("creation" or "file_create_event" or "rename" or "file_rename_event") and 
+file.path : /etc/init.d/* and not (
+  (process.name : ("dpkg" or "dockerd" or "rpm" or "dnf" or "chef-client" or "apk" or "yum" or "rpm" or
+  "vmis-launcher" or "exe" or "platform-python" or "executor" or "podman")) or
+  (file.extension : ("swp" or "swpx")) or
+  (process.name:mv and file.name:*.dpkg-remove) or
+  (process.name:sed and file.name:sed*) or
+  (process.name:systemd and file.name:*.dpkg-new)
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Boot or Logon Initialization Scripts
+** ID: T1037
+** Reference URL: https://attack.mitre.org/techniques/T1037/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-motd-file-creation-detected.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-motd-file-creation-detected.asciidoc
new file mode 100644
index 0000000000..24973e0b97
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-motd-file-creation-detected.asciidoc
@@ -0,0 +1,181 @@
+[[prebuilt-rule-8-11-17-potential-persistence-through-motd-file-creation-detected]]
+=== Potential Persistence Through MOTD File Creation Detected
+
+Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" and "/usr/lib/update-notifier/" directories. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. This rule detects the creation of potentially malicious files within the default MOTD file directories.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://pberba.github.io/security/2022/02/06/linux-threat-hunting-for-persistence-initialization-scripts-and-shell-configuration/#10-boot-or-logon-initialization-scripts-motd
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 10
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Potential Persistence Through MOTD File Creation Detected*
+
+
+The message-of-the-day (MOTD) is used to display a customizable system-wide message or information to users upon login in Linux.
+
+Attackers can abuse message-of-the-day (motd) files to run scripts, commands or malicious software every time a user connects to a system over SSH or a serial connection, by creating a new file within the `/etc/update-motd.d/` or `/usr/lib/update-notifier/` directory. Executable files in these directories automatically run with root privileges.
+
+This rule identifies the creation of new files within the `/etc/update-motd.d/` or `/usr/lib/update-notifier/` directories.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the file that was created or modified.
+  - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
+- Investigate whether any other files in the `/etc/update-motd.d/` or `/usr/lib/update-notifier/` directories have been altered.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE '/usr/lib/update-notifier/%')"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE\n'/usr/lib/update-notifier/%')\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Investigate whether the modified scripts call other malicious scripts elsewhere on the file system.
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+
+
+*Related Rules*
+
+
+- Suspicious Process Spawned from MOTD Detected - 4ec47004-b34a-42e6-8003-376a123ea447
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Any activity that triggered the alert and is not inherently malicious must be monitored by the security team.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the MOTD files or restore their original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type :linux and event.action:(creation or file_create_event or rename or file_rename_event) and
+file.path : (/etc/update-motd.d/* or /usr/lib/update-notifier/*) and not process.name : (
+  dpkg or dockerd or rpm or executor or dnf or podman or ln or yum 
+) and not (
+  (process.name:mv and file.extension:dpkg-remove) or
+  (file.extension:(swp or swpx))
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Boot or Logon Initialization Scripts
+** ID: T1037
+** Reference URL: https://attack.mitre.org/techniques/T1037/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-run-control-detected.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-run-control-detected.asciidoc
new file mode 100644
index 0000000000..abdf899b5b
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-persistence-through-run-control-detected.asciidoc
@@ -0,0 +1,184 @@
+[[prebuilt-rule-8-11-17-potential-persistence-through-run-control-detected]]
+=== Potential Persistence Through Run Control Detected
+
+This rule monitors the creation/alteration of the rc.local file by a previously unknown process executable through the use of the new terms rule type. The /etc/rc.local file is used to start custom applications, services, scripts or commands during start-up. The rc.local file has mostly been replaced by Systemd. However, through the "systemd-rc-local-generator", rc.local files can be converted to services that run at boot. Adversaries may alter rc.local to execute malicious code at start-up, and gain persistence onto the system.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.intezer.com/blog/malware-analysis/hiddenwasp-malware-targeting-linux-systems/
+* https://pberba.github.io/security/2022/02/06/linux-threat-hunting-for-persistence-initialization-scripts-and-shell-configuration/#8-boot-or-logon-initialization-scripts-rc-scripts
+* https://www.cyberciti.biz/faq/how-to-enable-rc-local-shell-script-on-systemd-while-booting-linux-system/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 111
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Potential Persistence Through Run Control Detected*
+
+
+The `rc.local` file executes custom commands or scripts during system startup on Linux systems. `rc.local` has been deprecated in favor of the use of `systemd services`, and more recent Unix distributions no longer leverage this method of on-boot script execution.
+
+There might still be users that use `rc.local` in a benign matter, so investigation to see whether the file is malicious is vital.
+
+Detection alerts from this rule indicate the creation of a new `/etc/rc.local` file.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Investigate the file that was created or modified.
+  - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate whether the `/lib/systemd/system/rc-local.service` and `/run/systemd/generator/multi-user.target.wants/rc-local.service` files were created through the `systemd-rc-local-generator` located at `/usr/lib/systemd/system-generators/systemd-rc-local-generator`.
+  - !{osquery{"label":"Osquery - Retrieve rc-local.service File Information","query":"SELECT * FROM file WHERE (path = '/run/systemd/generator/multi-user.target.wants/rc-local.service' OR path =\n'/run/systemd/generator/multi-user.target.wants/rc-local.service')\n"}}
+  - In case the file is not present here, `sudo systemctl status rc-local` can be executed to find the location of the rc-local unit file.
+  - If `rc-local.service` is found, manual investigation is required to check for the rc script execution. Systemd will generate syslogs in case of the execution of the rc-local service. `sudo cat /var/log/syslog | grep "rc-local.service|/etc/rc.local Compatibility"` can be executed to check for the execution of the service.
+    - If logs are found, it's likely that the contents of the `rc.local` file have been executed. Analyze the logs. In case several syslog log files are available, use a wildcard to search through all of the available logs.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate whether this activity is related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system.
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator who uses `rc.local` for administrative purposes, consider adding exceptions for this specific administrator user account.
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Response and remediation*
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the `service/rc.local` files or restore their original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type : "linux" and event.category : "file" and
+event.type : ("change" or "file_modify_event" or "creation" or "file_create_event") and
+file.path : "/etc/rc.local" and not process.name : (
+  "dockerd" or "docker" or "dnf" or "dnf-automatic" or "yum" or "rpm" or "dpkg"
+) and not file.extension : ("swp" or "swpx")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Boot or Logon Initialization Scripts
+** ID: T1037
+** Reference URL: https://attack.mitre.org/techniques/T1037/
+* Sub-technique:
+** Name: RC Scripts
+** ID: T1037.004
+** Reference URL: https://attack.mitre.org/techniques/T1037/004/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-ransomware-behavior-high-count-of-readme-files-by-system.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-ransomware-behavior-high-count-of-readme-files-by-system.asciidoc
new file mode 100644
index 0000000000..b2673a278a
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-ransomware-behavior-high-count-of-readme-files-by-system.asciidoc
@@ -0,0 +1,125 @@
+[[prebuilt-rule-8-11-17-potential-ransomware-behavior-high-count-of-readme-files-by-system]]
+=== Potential Ransomware Behavior - High count of Readme files by System
+
+This rule identifies a high number (20) of file creation event by the System virtual process from the same host and with same file name containing keywords similar to ransomware note files and all within a short time period.
+
+*Rule type*: threshold
+
+*Rule indices*: 
+
+* logs-endpoint.events.file-*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://news.sophos.com/en-us/2023/12/21/akira-again-the-ransomware-that-keeps-on-taking/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Impact
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 2
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Possible investigation steps*
+
+
+- Investigate the content of the readme files.
+- Investigate any file names with unusual extensions.
+- Investigate any incoming network connection to port 445 on this host.
+- Investigate any network logon events to this host.
+- Identify the total number and type of modified files by pid 4.
+- If the number of files is too high and source.ip connecting over SMB is unusual isolate the host and block the used credentials.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+
+
+*False positive analysis*
+
+
+- Local file modification from a Kernel mode driver.
+
+
+*Related rules*
+
+
+- Third-party Backup Files Deleted via Unexpected Process - 11ea6bec-ebde-4d71-a8e9-784948f8e3e9
+- Volume Shadow Copy Deleted or Resized via VssAdmin - b5ea4bfe-a1b2-421f-9d47-22a75a6f2921
+- Volume Shadow Copy Deletion via PowerShell - d99a037b-c8e2-47a5-97b9-170d076827c4
+- Volume Shadow Copy Deletion via WMIC - dc9c1f74-dac3-48e3-b47f-eb79db358f57
+- Potential Ransomware Note File Dropped via SMB - 02bab13d-fb14-4d7c-b6fe-4a28874d37c5
+- Suspicious File Renamed via SMB - 78e9b5d5-7c07-40a7-a591-3dbbf464c386
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Consider isolating the involved host to prevent destructive behavior, which is commonly associated with this activity.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- If any other destructive action was identified on the host, it is recommended to prioritize the investigation and look for ransomware preparation and execution activities.
+- If any backups were affected:
+  - Perform data recovery locally or restore the backups from replicated copies (cloud, other servers, etc.).
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.category:file and host.os.type:windows and process.pid:4 and event.action:creation and
+ file.name:(*read*me* or *README* or *lock* or *LOCK* or *how*to* or *HOW*TO* or *@* or *recover* or *RECOVER* or *decrypt* or *DECRYPT* or *restore* or *RESTORE* or *FILES_BACK* or *files_back*)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Impact
+** ID: TA0040
+** Reference URL: https://attack.mitre.org/tactics/TA0040/
+* Technique:
+** Name: Data Destruction
+** ID: T1485
+** Reference URL: https://attack.mitre.org/techniques/T1485/
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Remote Services
+** ID: T1021
+** Reference URL: https://attack.mitre.org/techniques/T1021/
+* Sub-technique:
+** Name: SMB/Windows Admin Shares
+** ID: T1021.002
+** Reference URL: https://attack.mitre.org/techniques/T1021/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-ransomware-note-file-dropped-via-smb.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-ransomware-note-file-dropped-via-smb.asciidoc
new file mode 100644
index 0000000000..b90f87b91d
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-ransomware-note-file-dropped-via-smb.asciidoc
@@ -0,0 +1,136 @@
+[[prebuilt-rule-8-11-17-potential-ransomware-note-file-dropped-via-smb]]
+=== Potential Ransomware Note File Dropped via SMB
+
+Identifies an incoming SMB connection followed by the creation of a file with a name similar to ransomware note files. This may indicate a remote ransomware attack via the SMB protocol.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Impact
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 2
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Performance*
+
+
+- This rule may cause medium to high performance impact due to logic scoping all icoming SMB network events.
+
+
+*Possible investigation steps*
+
+
+- Investigate the source.ip address connecting to port 445 on this host.
+- Identify the user account that performed the file creation via SMB.
+- If the number of files is too high and source.ip connecting over SMB is unusual isolate the host and block the used credentials.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+
+
+*False positive analysis*
+
+
+- Remote file creation with similar file naming convention via SMB.
+
+
+
+*Related rules*
+
+
+- Third-party Backup Files Deleted via Unexpected Process - 11ea6bec-ebde-4d71-a8e9-784948f8e3e9
+- Volume Shadow Copy Deleted or Resized via VssAdmin - b5ea4bfe-a1b2-421f-9d47-22a75a6f2921
+- Volume Shadow Copy Deletion via PowerShell - d99a037b-c8e2-47a5-97b9-170d076827c4
+- Volume Shadow Copy Deletion via WMIC - dc9c1f74-dac3-48e3-b47f-eb79db358f57
+- Suspicious File Renamed via SMB - 78e9b5d5-7c07-40a7-a591-3dbbf464c386
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Consider isolating the involved host to prevent destructive behavior, which is commonly associated with this activity.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- If any other destructive action was identified on the host, it is recommended to prioritize the investigation and look for ransomware preparation and execution activities.
+- If any backups were affected:
+  - Perform data recovery locally or restore the backups from replicated copies (cloud, other servers, etc.).
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by host.id with maxspan=1s
+ [network where host.os.type == "windows" and
+  event.action == "connection_accepted" and destination.port == 445 and source.port >= 49152 and process.pid == 4 and
+  source.ip != "127.0.0.1" and source.ip != "::1"]
+ [file where host.os.type == "windows" and event.action == "creation" and
+  process.pid == 4 and user.id : ("S-1-5-21*", "S-1-12-*") and file.extension : ("hta", "txt", "readme", "htm*") and
+   /* ransom file name keywords */
+    file.name : ("*read*me*", "*lock*", "*@*", "*RECOVER*", "*decrypt*", "*restore*file*", "*FILES_BACK*", "*how*to*")] with runs=3
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Impact
+** ID: TA0040
+** Reference URL: https://attack.mitre.org/tactics/TA0040/
+* Technique:
+** Name: Data Destruction
+** ID: T1485
+** Reference URL: https://attack.mitre.org/techniques/T1485/
+* Technique:
+** Name: Inhibit System Recovery
+** ID: T1490
+** Reference URL: https://attack.mitre.org/techniques/T1490/
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Remote Services
+** ID: T1021
+** Reference URL: https://attack.mitre.org/techniques/T1021/
+* Sub-technique:
+** Name: SMB/Windows Admin Shares
+** ID: T1021.002
+** Reference URL: https://attack.mitre.org/techniques/T1021/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-remote-desktop-tunneling-detected.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-remote-desktop-tunneling-detected.asciidoc
new file mode 100644
index 0000000000..e09b0dcff8
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-remote-desktop-tunneling-detected.asciidoc
@@ -0,0 +1,147 @@
+[[prebuilt-rule-8-11-17-potential-remote-desktop-tunneling-detected]]
+=== Potential Remote Desktop Tunneling Detected
+
+Identifies potential use of an SSH utility to establish RDP over a reverse SSH Tunnel. This can be used by attackers to enable routing of network packets that would otherwise not reach their intended destination.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.process-*
+* winlogbeat-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://blog.netspi.com/how-to-access-rdp-over-a-reverse-ssh-tunnel/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Command and Control
+* Tactic: Lateral Movement
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: SentinelOne
+
+*Version*: 212
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Potential Remote Desktop Tunneling Detected*
+
+
+Protocol Tunneling is a mechanism that involves explicitly encapsulating a protocol within another for various use cases, ranging from providing an outer layer of encryption (similar to a VPN) to enabling traffic that network appliances would filter to reach their destination.
+
+Attackers may tunnel Remote Desktop Protocol (RDP) traffic through other protocols like Secure Shell (SSH) to bypass network restrictions that block incoming RDP connections but may be more permissive to other protocols.
+
+This rule looks for command lines involving the `3389` port, which RDP uses by default and options commonly associated with tools that perform tunneling.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account and system owners and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+- Examine network data to determine if the host communicated with external servers using the tunnel.
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+- Investigate the command line for the execution of programs that are unrelated to tunneling, like Remote Desktop clients.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Take the necessary actions to disable the tunneling, which can be a process kill, service deletion, registry key modification, etc. Inspect the host to learn which method was used and to determine a response for the case.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  /* RDP port and usual SSH tunneling related switches in command line */
+  process.args : "*:3389" and
+  process.args : ("-L", "-P", "-R", "-pw", "-ssh")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Protocol Tunneling
+** ID: T1572
+** Reference URL: https://attack.mitre.org/techniques/T1572/
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Remote Services
+** ID: T1021
+** Reference URL: https://attack.mitre.org/techniques/T1021/
+* Sub-technique:
+** Name: SSH
+** ID: T1021.004
+** Reference URL: https://attack.mitre.org/techniques/T1021/004/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-reverse-shell-via-child.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-reverse-shell-via-child.asciidoc
new file mode 100644
index 0000000000..674a1cb4ca
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-reverse-shell-via-child.asciidoc
@@ -0,0 +1,120 @@
+[[prebuilt-rule-8-11-17-potential-reverse-shell-via-child]]
+=== Potential Reverse Shell via Child
+
+This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a network event that is followed by the creation of a shell process with suspicious command line arguments. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://github.com/swisskyrepo/PayloadsAllTheThings/blob/master/Methodology%20and%20Resources/Reverse%20Shell%20Cheatsheet.md
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Execution
+* Data Source: Elastic Defend
+
+*Version*: 3
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows
+the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click Add integrations.
+- In the query bar, search for Elastic Defend and select the integration to see more details about it.
+- Click Add Elastic Defend.
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either Traditional Endpoints or Cloud Workloads.
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest to select "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in New agent policy name. If other agent policies already exist, you can click the Existing hosts tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click Save and Continue.
+- To complete the integration, select Add Elastic Agent to your hosts and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by host.id, process.entity_id with maxspan=5s
+  [network where event.type == "start" and host.os.type == "linux" and
+     event.action in ("connection_attempted", "connection_accepted") and
+     process.name : ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish", "socat") and destination.ip != null and
+     not cidrmatch(destination.ip, "127.0.0.0/8", "169.254.0.0/16", "224.0.0.0/4", "::1")]
+  [process where event.type == "start" and host.os.type == "linux" and event.action == "exec" and
+     process.name in ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish") and (
+       (process.args : ("-i", "-l")) or (process.parent.name == "socat" and process.parent.args : "*exec*")
+   )]
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
+* Sub-technique:
+** Name: Unix Shell
+** ID: T1059.004
+** Reference URL: https://attack.mitre.org/techniques/T1059/004/
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Application Layer Protocol
+** ID: T1071
+** Reference URL: https://attack.mitre.org/techniques/T1071/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-reverse-shell.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-reverse-shell.asciidoc
new file mode 100644
index 0000000000..06f535a21f
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-reverse-shell.asciidoc
@@ -0,0 +1,118 @@
+[[prebuilt-rule-8-11-17-potential-reverse-shell]]
+=== Potential Reverse Shell
+
+This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a parent-child relationship where a network event is followed by the creation of a shell process. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://github.com/swisskyrepo/PayloadsAllTheThings/blob/master/Methodology%20and%20Resources/Reverse%20Shell%20Cheatsheet.md
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Execution
+* Data Source: Elastic Defend
+
+*Version*: 9
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by host.id with maxspan=5s
+  [network where event.type == "start" and host.os.type == "linux" and
+     event.action in ("connection_attempted", "connection_accepted") and
+     process.name : ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish", "socat") and destination.ip != null and
+     not cidrmatch(destination.ip, "127.0.0.0/8", "169.254.0.0/16", "224.0.0.0/4", "::1")] by process.entity_id
+  [process where event.type == "start" and host.os.type == "linux" and event.action in ("exec", "fork") and
+     process.name in ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish") and (
+       (process.args : ("-i", "-l")) or (process.parent.name == "socat" and process.parent.args : "*exec*")
+   )] by process.parent.entity_id
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
+* Sub-technique:
+** Name: Unix Shell
+** ID: T1059.004
+** Reference URL: https://attack.mitre.org/techniques/T1059/004/
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Application Layer Protocol
+** ID: T1071
+** Reference URL: https://attack.mitre.org/techniques/T1071/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-suspicious-file-edit.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-suspicious-file-edit.asciidoc
new file mode 100644
index 0000000000..ae855cc559
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-potential-suspicious-file-edit.asciidoc
@@ -0,0 +1,112 @@
+[[prebuilt-rule-8-11-17-potential-suspicious-file-edit]]
+=== Potential Suspicious File Edit
+
+This rule monitors for the potential edit of a suspicious file. In Linux, when editing a file through an editor, a temporary .swp file is created. By monitoring for the creation of this .swp file, we can detect potential file edits of suspicious files. The execution of this rule is not a clear sign of the file being edited, as just opening the file through an editor will trigger this event. Attackers may alter any of the files added in this rule to establish persistence, escalate privileges or perform reconnaisance on the system.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 1
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Privilege Escalation
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "linux" and event.action in ("creation", "file_create_event") and file.extension == "swp" and
+file.path : (
+  /* common interesting files and locations */
+  "/etc/.shadow.swp", "/etc/.shadow-.swp", "/etc/.shadow~.swp", "/etc/.gshadow.swp", "/etc/.gshadow-.swp",
+  "/etc/.passwd.swp", "/etc/.pwd.db.swp", "/etc/.master.passwd.swp", "/etc/.spwd.db.swp", "/etc/security/.opasswd.swp",
+  "/etc/.environment.swp", "/etc/.profile.swp", "/etc/sudoers.d/.*.swp", "/etc/ld.so.conf.d/.*.swp",
+  "/etc/init.d/.*.swp", "/etc/.rc.local.swp", "/etc/rc*.d/.*.swp", "/dev/shm/.*.swp", "/etc/update-motd.d/.*.swp",
+  "/usr/lib/update-notifier/.*.swp",
+
+  /* service, timer, want, socket and lock files */
+  "/etc/systemd/system/.*.swp", "/usr/local/lib/systemd/system/.*.swp", "/lib/systemd/system/.*.swp",
+  "/usr/lib/systemd/system/.*.swp","/home/*/.config/systemd/user/.*.swp", "/run/.*.swp", "/var/run/.*.swp/",
+
+  /* profile and shell configuration files */  
+  "/home/*.profile.swp", "/home/*.bash_profile.swp", "/home/*.bash_login.swp", "/home/*.bashrc.swp", "/home/*.bash_logout.swp",
+  "/home/*.zshrc.swp", "/home/*.zlogin.swp", "/home/*.tcshrc.swp", "/home/*.kshrc.swp", "/home/*.config.fish.swp",
+  "/root/*.profile.swp", "/root/*.bash_profile.swp", "/root/*.bash_login.swp", "/root/*.bashrc.swp", "/root/*.bash_logout.swp",
+  "/root/*.zshrc.swp", "/root/*.zlogin.swp", "/root/*.tcshrc.swp", "/root/*.kshrc.swp", "/root/*.config.fish.swp"
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Boot or Logon Initialization Scripts
+** ID: T1037
+** Reference URL: https://attack.mitre.org/techniques/T1037/
+* Sub-technique:
+** Name: RC Scripts
+** ID: T1037.004
+** Reference URL: https://attack.mitre.org/techniques/T1037/004/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Systemd Service
+** ID: T1543.002
+** Reference URL: https://attack.mitre.org/techniques/T1543/002/
+* Technique:
+** Name: Hijack Execution Flow
+** ID: T1574
+** Reference URL: https://attack.mitre.org/techniques/T1574/
+* Sub-technique:
+** Name: Dynamic Linker Hijacking
+** ID: T1574.006
+** Reference URL: https://attack.mitre.org/techniques/T1574/006/
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Sudo and Sudo Caching
+** ID: T1548.003
+** Reference URL: https://attack.mitre.org/techniques/T1548/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-powershell-script-block-logging-disabled.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-powershell-script-block-logging-disabled.asciidoc
new file mode 100644
index 0000000000..5394553d69
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-powershell-script-block-logging-disabled.asciidoc
@@ -0,0 +1,135 @@
+[[prebuilt-rule-8-11-17-powershell-script-block-logging-disabled]]
+=== PowerShell Script Block Logging Disabled
+
+Identifies attempts to disable PowerShell Script Block Logging via registry modification. Attackers may disable this logging to conceal their activities in the host and evade detection.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://admx.help/?Category=Windows_10_2016&Policy=Microsoft.Policies.PowerShell::EnableScriptBlockLogging
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 110
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating PowerShell Script Block Logging Disabled*
+
+
+PowerShell is one of the main tools system administrators use for automation, report routines, and other tasks, making it available in various environments and creating an attractive way for attackers to execute code.
+
+PowerShell Script Block Logging is a feature of PowerShell that records the content of all script blocks that it processes, giving defenders visibility of PowerShell scripts and sequences of executed commands.
+
+
+*Possible investigation steps*
+
+
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Check whether it makes sense for the user to use PowerShell to complete tasks.
+- Investigate if PowerShell scripts were run after logging was disabled.
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+
+
+*Related rules*
+
+
+- PowerShell Suspicious Discovery Related Windows API Functions - 61ac3638-40a3-44b2-855a-985636ca985e
+- PowerShell Keylogging Script - bd2c86a0-8b61-4457-ab38-96943984e889
+- PowerShell Suspicious Script with Audio Capture Capabilities - 2f2f4939-0b34-40c2-a0a3-844eb7889f43
+- Potential Process Injection via PowerShell - 2e29e96a-b67c-455a-afe4-de6183431d0d
+- Suspicious .NET Reflection via PowerShell - e26f042e-c590-4e82-8e05-41e81bd822ad
+- PowerShell Suspicious Payload Encoded and Compressed - 81fe9dc6-a2d7-4192-a2d8-eed98afc766a
+- PowerShell Suspicious Script with Screenshot Capabilities - 959a7353-1129-4aa7-9084-30746b256a70
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- Review the privileges assigned to the involved users to ensure that the least privilege principle is being followed.
+- Restrict PowerShell usage outside of IT and engineering business units using GPOs, AppLocker, Intune, or similar software.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and event.type == "change" and
+    registry.path : (
+        "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows\\PowerShell\\ScriptBlockLogging\\EnableScriptBlockLogging",
+        "\\REGISTRY\\MACHINE\\SOFTWARE\\Policies\\Microsoft\\Windows\\PowerShell\\ScriptBlockLogging\\EnableScriptBlockLogging"
+    ) and registry.data.strings : ("0", "0x00000000")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable Windows Event Logging
+** ID: T1562.002
+** Reference URL: https://attack.mitre.org/techniques/T1562/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-prompt-for-credentials-with-osascript.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-prompt-for-credentials-with-osascript.asciidoc
new file mode 100644
index 0000000000..1812e3b43f
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-prompt-for-credentials-with-osascript.asciidoc
@@ -0,0 +1,111 @@
+[[prebuilt-rule-8-11-17-prompt-for-credentials-with-osascript]]
+=== Prompt for Credentials with OSASCRIPT
+
+Identifies the use of osascript to execute scripts via standard input that may prompt a user with a rogue dialog for credentials.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://github.com/EmpireProject/EmPyre/blob/master/lib/modules/collection/osx/prompt.py
+* https://ss64.com/osx/osascript.html
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: macOS
+* Use Case: Threat Detection
+* Tactic: Credential Access
+* Data Source: Elastic Defend
+
+*Version*: 208
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a macOS System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, for MacOS it is recommended to select "Traditional Endpoints".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/current/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where event.action == "exec" and host.os.type == "macos" and
+ process.name : "osascript" and process.args : "-e" and process.command_line : ("*osascript*display*dialog*password*", "*osascript*display*dialog*passphrase*") and
+ not (process.parent.executable : "/usr/bin/sudo" and process.command_line : "*Encryption Key Escrow*") and
+ not (process.command_line : "*-e with timeout of 3600 seconds*" and user.id == "0" and process.parent.executable : "/bin/bash") and
+ not process.Ext.effective_parent.executable : ("/usr/local/jamf/*", 
+                                                "/Applications/Karabiner-Elements.app/Contents/MacOS/Karabiner-Elements",
+                                                "/System/Applications/Utilities/Terminal.app/Contents/MacOS/Terminal",
+                                                "/Library/Application Support/JAMF/Jamf.app/Contents/MacOS/JamfDaemon.app/Contents/MacOS/JamfDaemon",
+                                                "/Library/Application Support/JAMF/Jamf.app/Contents/MacOS/JamfManagementService.app/Contents/MacOS/JamfManagementService")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Credential Access
+** ID: TA0006
+** Reference URL: https://attack.mitre.org/tactics/TA0006/
+* Technique:
+** Name: Input Capture
+** ID: T1056
+** Reference URL: https://attack.mitre.org/techniques/T1056/
+* Sub-technique:
+** Name: GUI Input Capture
+** ID: T1056.002
+** Reference URL: https://attack.mitre.org/techniques/T1056/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-quarantine-attrib-removed-by-unsigned-or-untrusted-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-quarantine-attrib-removed-by-unsigned-or-untrusted-process.asciidoc
new file mode 100644
index 0000000000..02a31ff018
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-quarantine-attrib-removed-by-unsigned-or-untrusted-process.asciidoc
@@ -0,0 +1,110 @@
+[[prebuilt-rule-8-11-17-quarantine-attrib-removed-by-unsigned-or-untrusted-process]]
+=== Quarantine Attrib Removed by Unsigned or Untrusted Process
+
+Detects deletion of the quarantine attribute by an unusual process (xattr). In macOS, when applications or programs are downloaded from the internet, there is a quarantine flag set on the file. This attribute is read by Apple's Gatekeeper defense program at execution time. An adversary may disable this attribute to evade defenses.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://nixhacker.com/security-protection-in-macos-1/
+* https://eclecticlight.co/2020/10/29/quarantine-and-the-quarantine-flag/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: macOS
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Defend
+
+*Version*: 109
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a macOS System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, for MacOS it is recommended to select "Traditional Endpoints".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/current/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where event.action == "extended_attributes_delete" and host.os.type == "macos" and process.executable != null and
+(process.code_signature.trusted == false or process.code_signature.exists == false) and not
+process.executable : ("/usr/bin/xattr", 
+                      "/System/*", 
+                      "/private/tmp/KSInstallAction.*/*/Install Google Software Update.app/Contents/Helpers/ksinstall",
+                      "/Applications/CEWE Fotoschau.app/Contents/MacOS/FotoPlus",
+                      "/Applications/.com.bomgar.scc.*/Remote Support Customer Client.app/Contents/MacOS/sdcust") and not
+file.path : "/private/var/folders/*"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Tools
+** ID: T1562.001
+** Reference URL: https://attack.mitre.org/techniques/T1562/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-registry-persistence-via-appcert-dll.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-registry-persistence-via-appcert-dll.asciidoc
new file mode 100644
index 0000000000..0c3a1783d0
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-registry-persistence-via-appcert-dll.asciidoc
@@ -0,0 +1,103 @@
+[[prebuilt-rule-8-11-17-registry-persistence-via-appcert-dll]]
+=== Registry Persistence via AppCert DLL
+
+Detects attempts to maintain persistence by creating registry keys using AppCert DLLs. AppCert DLLs are loaded by every process using the common API functions to create processes.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Privilege Escalation
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 210
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and
+/* uncomment once stable length(bytes_written_string) > 0 and */
+  registry.path : (
+    "HKLM\\SYSTEM\\*ControlSet*\\Control\\Session Manager\\AppCertDLLs\\*",
+    "\\REGISTRY\\MACHINE\\SYSTEM\\*ControlSet*\\Control\\Session Manager\\AppCertDLLs\\*",
+    "MACHINE\\SYSTEM\\*ControlSet*\\Control\\Session Manager\\AppCertDLLs\\*"
+  )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Event Triggered Execution
+** ID: T1546
+** Reference URL: https://attack.mitre.org/techniques/T1546/
+* Sub-technique:
+** Name: AppCert DLLs
+** ID: T1546.009
+** Reference URL: https://attack.mitre.org/techniques/T1546/009/
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Event Triggered Execution
+** ID: T1546
+** Reference URL: https://attack.mitre.org/techniques/T1546/
+* Sub-technique:
+** Name: AppCert DLLs
+** ID: T1546.009
+** Reference URL: https://attack.mitre.org/techniques/T1546/009/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-route53-resolver-query-log-configuration-deleted.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-route53-resolver-query-log-configuration-deleted.asciidoc
new file mode 100644
index 0000000000..937d170e7a
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-route53-resolver-query-log-configuration-deleted.asciidoc
@@ -0,0 +1,122 @@
+[[prebuilt-rule-8-11-17-route53-resolver-query-log-configuration-deleted]]
+=== Route53 Resolver Query Log Configuration Deleted
+
+Identifies when a Route53 Resolver Query Log Configuration is deleted. When a Route53 Resolver query log configuration is deleted, Resolver stops logging DNS queries and responses for the specified configuration. Adversaries may delete query log configurations to evade detection or cover their tracks.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 10m
+
+*Searches indices from*: now-60m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/Route53/latest/APIReference/API_route53resolver_DeleteResolverQueryLogConfig.html
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: Amazon Route53
+* Use Case: Log Auditing
+* Resources: Investigation Guide
+* Tactic: Defense Evasion
+
+*Version*: 2
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and Analysis*
+
+
+
+*Investigating Route53 Resolver Query Log Configuration Deleted*
+
+
+This rule detects when a Route53 Resolver Query Log Configuration is deleted. Deleting these configurations stops the logging of DNS queries and responses, which can significantly impede network monitoring and compromise security visibility. Adversaries may delete these configurations to evade detection, remove evidence, or obscure their activities within a network.
+
+Adversaries target Route53 Resolver query log configurations because these logs can contain evidence of malicious domain queries or responses. By deleting these logs, an adversary can prevent the capture of information that could reveal unauthorized network activities, aiding in avoiding detection and thwarting incident response efforts.
+
+
+*Possible Investigation Steps*
+
+
+- **Review the Deletion Details**: Examine the CloudTrail logs to identify when and by whom the deletion was initiated.
+    - Check the `event.action` and `user_identity` elements to understand the scope and authorization of the deletion.
+- **Contextualize with User Actions**: Assess whether the deletion aligns with the user’s role and job responsibilities.
+    - Investigate if similar modifications have occurred recently that could suggest a pattern or broader campaign.
+- **Analyze Access Patterns and Permissions**: Verify whether the user had the appropriate permissions to delete log configurations.
+    - Investigate any recent permission changes that might indicate role abuse or credentials compromise.
+- **Correlate with Other Security Incidents**: Look for related security alerts or incidents that could be connected to the log deletion.
+    - This includes unusual network traffic, alerts from other AWS services, or findings from intrusion detection systems.
+- **Interview the Responsible Team**: If the deletion was initiated by an internal team member, confirm their intent and authorization to ensure it was a legitimate action.
+
+
+*False Positive Analysis*
+
+
+- **Legitimate Administrative Actions**: Confirm that the deletion was part of scheduled IT operations or network management activities, possibly linked to maintenance or infrastructure updates. Validate this action against change management records or through interviews with relevant personnel.
+
+
+*Response and Remediation*
+
+
+- **Restore Logs if Feasible**: If the deletion was unauthorized, consider restoring the configuration from backups to ensure continuous visibility into DNS queries.
+- **Review and Tighten Permissions**: Ensure that only authorized personnel have the capability to delete critical configurations.
+    - Adjust AWS IAM policies to reinforce security measures.
+- **Enhance Monitoring of Log Management**: Implement or enhance monitoring rules to detect and alert on unauthorized changes to logging configurations, focusing on critical deletions.
+- **Conduct Comprehensive Security Review**: If the deletion is verified as malicious, initiate a thorough security assessment to identify any further unauthorized changes or ongoing malicious activities.
+
+
+*Additional Information*
+
+
+For detailed instructions on managing Route53 Resolver and securing its configurations, refer to the https://docs.aws.amazon.com/Route53/latest/APIReference/API_route53resolver_DeleteResolverQueryLogConfig.html[Amazon Route53 Resolver documentation].
+
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset:aws.cloudtrail and event.provider: route53resolver.amazonaws.com
+    and event.action: DeleteResolverQueryLogConfig and event.outcome: success
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Cloud Logs
+** ID: T1562.008
+** Reference URL: https://attack.mitre.org/techniques/T1562/008/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-service-control-spawned-via-script-interpreter.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-service-control-spawned-via-script-interpreter.asciidoc
new file mode 100644
index 0000000000..7230a2b90c
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-service-control-spawned-via-script-interpreter.asciidoc
@@ -0,0 +1,172 @@
+[[prebuilt-rule-8-11-17-service-control-spawned-via-script-interpreter]]
+=== Service Control Spawned via Script Interpreter
+
+Identifies Service Control (sc.exe) spawning from script interpreter processes to create, modify, or start services. This can potentially indicate an attempt to elevate privileges or maintain persistence.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.process-*
+* logs-system.*
+* winlogbeat-*
+* logs-windows.*
+* endgame-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Privilege Escalation
+* Tactic: Defense Evasion
+* Tactic: Execution
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 109
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Service Control Spawned via Script Interpreter*
+
+
+Windows services are background processes that run with SYSTEM privileges and provide specific functionality or support to other applications and system components.
+
+The `sc.exe` command line utility is used to manage and control Windows services on a local or remote computer. Attackers may use `sc.exe` to create, modify, and start services to elevate their privileges from administrator to SYSTEM.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Examine the command line, registry changes events, and Windows events related to service activities (for example, 4697 and/or 7045) for suspicious characteristics.
+  - Examine the created and existent services, the executables or drivers referenced, and command line arguments for suspicious entries.
+    - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+    - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+    - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+  - Retrieve the referenced files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+
+
+*False positive analysis*
+
+
+- This activity is not inherently malicious if it occurs in isolation. As long as the analyst did not identify suspicious activity related to the user, host, and service, such alerts can be dismissed.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service or restore it to the original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+/* This rule is not compatible with Sysmon due to user.id issues */
+
+process where host.os.type == "windows" and event.type == "start" and
+  (process.name : "sc.exe" or process.pe.original_file_name == "sc.exe") and
+  process.parent.name : ("cmd.exe", "wscript.exe", "rundll32.exe", "regsvr32.exe",
+                         "wmic.exe", "mshta.exe","powershell.exe", "pwsh.exe") and
+  process.args:("config", "create", "start", "delete", "stop", "pause") and
+  /* exclude SYSTEM SID - look for service creations by non-SYSTEM user */
+  not user.id : "S-1-5-18"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Windows Service
+** ID: T1543.003
+** Reference URL: https://attack.mitre.org/techniques/T1543/003/
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Windows Management Instrumentation
+** ID: T1047
+** Reference URL: https://attack.mitre.org/techniques/T1047/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
+* Sub-technique:
+** Name: PowerShell
+** ID: T1059.001
+** Reference URL: https://attack.mitre.org/techniques/T1059/001/
+* Sub-technique:
+** Name: Windows Command Shell
+** ID: T1059.003
+** Reference URL: https://attack.mitre.org/techniques/T1059/003/
+* Sub-technique:
+** Name: Visual Basic
+** ID: T1059.005
+** Reference URL: https://attack.mitre.org/techniques/T1059/005/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: System Binary Proxy Execution
+** ID: T1218
+** Reference URL: https://attack.mitre.org/techniques/T1218/
+* Sub-technique:
+** Name: Regsvr32
+** ID: T1218.010
+** Reference URL: https://attack.mitre.org/techniques/T1218/010/
+* Sub-technique:
+** Name: Rundll32
+** ID: T1218.011
+** Reference URL: https://attack.mitre.org/techniques/T1218/011/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-shared-object-created-or-changed-by-previously-unknown-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-shared-object-created-or-changed-by-previously-unknown-process.asciidoc
new file mode 100644
index 0000000000..99251fd0e3
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-shared-object-created-or-changed-by-previously-unknown-process.asciidoc
@@ -0,0 +1,185 @@
+[[prebuilt-rule-8-11-17-shared-object-created-or-changed-by-previously-unknown-process]]
+=== Shared Object Created or Changed by Previously Unknown Process
+
+This rule monitors the creation of shared object files by previously unknown processes. The creation of a shared object file involves compiling code into a dynamically linked library that can be loaded by other programs at runtime. While this process is typically used for legitimate purposes, malicious actors can leverage shared object files to execute unauthorized code, inject malicious functionality into legitimate processes, or bypass security controls. This allows malware to persist on the system, evade detection, and potentially compromise the integrity and confidentiality of the affected system and its data.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://threatpost.com/sneaky-malware-backdoors-linux/180158/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 8
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Shared Object Created or Changed by Previously Unknown Process*
+
+
+A shared object file is a compiled library file (typically with a .so extension) that can be dynamically linked to executable programs at runtime, allowing for code reuse and efficient memory usage. The creation of a shared object file involves compiling code into a dynamically linked library that can be loaded by other programs at runtime.
+
+Malicious actors can leverage shared object files to execute unauthorized code, inject malicious functionality into legitimate processes, or bypass security controls. This allows malware to persist on the system, evade detection, and potentially compromise the integrity and confidentiality of the affected system and its data.
+
+This rule monitors the creation of shared object files by previously unknown processes through the usage of the new terms rule type.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the shared object that was created or modified through OSQuery.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE path = {{file.path}}\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE path = {{file.path}}\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator that performed these actions for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type:linux and event.action:(creation or file_create_event or file_rename_event or rename) and 
+file.path:(/dev/shm/* or /usr/lib/*) and file.extension:so and process.name:* and not (
+  process.name:("dockerd" or "dpkg" or "rpm" or "snapd" or "yum" or "vmis-launcher" or "pacman" or
+  "apt-get" or "dnf" or "podman" or "platform-python") or 
+  (process.name:vmware-install.pl and file.path:/usr/lib/vmware-tools/*)
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Hijack Execution Flow
+** ID: T1574
+** Reference URL: https://attack.mitre.org/techniques/T1574/
+* Sub-technique:
+** Name: Dynamic Linker Hijacking
+** ID: T1574.006
+** Reference URL: https://attack.mitre.org/techniques/T1574/006/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-solarwinds-process-disabling-services-via-registry.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-solarwinds-process-disabling-services-via-registry.asciidoc
new file mode 100644
index 0000000000..bf36f6ca80
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-solarwinds-process-disabling-services-via-registry.asciidoc
@@ -0,0 +1,113 @@
+[[prebuilt-rule-8-11-17-solarwinds-process-disabling-services-via-registry]]
+=== SolarWinds Process Disabling Services via Registry
+
+Identifies a SolarWinds binary modifying the start type of a service to be disabled. An adversary may abuse this technique to manipulate relevant security services.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.fireeye.com/blog/threat-research/2020/12/evasive-attacker-leverages-solarwinds-supply-chain-compromises-with-sunburst-backdoor.html
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Tactic: Initial Access
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 110
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and registry.path : (
+    "HKLM\\SYSTEM\\*ControlSet*\\Services\\*\\Start",
+    "\\REGISTRY\\MACHINE\\SYSTEM\\*ControlSet*\\Services\\*\\Start"
+  ) and
+  registry.data.strings : ("4", "0x00000004") and
+  process.name : (
+      "SolarWinds.BusinessLayerHost*.exe",
+      "ConfigurationWizard*.exe",
+      "NetflowDatabaseMaintenance*.exe",
+      "NetFlowService*.exe",
+      "SolarWinds.Administration*.exe",
+      "SolarWinds.Collector.Service*.exe",
+      "SolarwindsDiagnostics*.exe")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Tools
+** ID: T1562.001
+** Reference URL: https://attack.mitre.org/techniques/T1562/001/
+* Tactic:
+** Name: Initial Access
+** ID: TA0001
+** Reference URL: https://attack.mitre.org/tactics/TA0001/
+* Technique:
+** Name: Supply Chain Compromise
+** ID: T1195
+** Reference URL: https://attack.mitre.org/techniques/T1195/
+* Sub-technique:
+** Name: Compromise Software Supply Chain
+** ID: T1195.002
+** Reference URL: https://attack.mitre.org/techniques/T1195/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device-via-airdrop.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device-via-airdrop.asciidoc
new file mode 100644
index 0000000000..4d94010407
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device-via-airdrop.asciidoc
@@ -0,0 +1,82 @@
+[[prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device-via-airdrop]]
+=== Spike in Bytes Sent to an External Device via Airdrop
+
+A machine learning job has detected high bytes of data written to an external device via Airdrop. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-2h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/ded
+* https://www.elastic.co/blog/detect-data-exfiltration-activity-with-kibanas-new-integration
+
+*Tags*: 
+
+* Use Case: Data Exfiltration Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Exfiltration
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Data Exfiltration Detection integration assets to be installed, as well as network and file events collected by integrations such as Elastic Defend and Network Packet Capture (for network events only).  
+
+
+*Data Exfiltration Detection Setup*
+
+The Data Exfiltration Detection integration detects data exfiltration activity by identifying abnormalities in network and file events. Anomalies are detected using Elastic's Anomaly Detection feature. 
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Data Exfiltration Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- File events collected by the Elastic Defend integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Data Exfiltration Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Exfiltration
+** ID: TA0010
+** Reference URL: https://attack.mitre.org/tactics/TA0010/
+* Technique:
+** Name: Exfiltration Over Other Network Medium
+** ID: T1011
+** Reference URL: https://attack.mitre.org/techniques/T1011/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device.asciidoc
new file mode 100644
index 0000000000..51b0b3b9b9
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device.asciidoc
@@ -0,0 +1,82 @@
+[[prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device]]
+=== Spike in Bytes Sent to an External Device
+
+A machine learning job has detected high bytes of data written to an external device. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-2h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/ded
+* https://www.elastic.co/blog/detect-data-exfiltration-activity-with-kibanas-new-integration
+
+*Tags*: 
+
+* Use Case: Data Exfiltration Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Exfiltration
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Data Exfiltration Detection integration assets to be installed, as well as network and file events collected by integrations such as Elastic Defend and Network Packet Capture (for network events only).  
+
+
+*Data Exfiltration Detection Setup*
+
+The Data Exfiltration Detection integration detects data exfiltration activity by identifying abnormalities in network and file events. Anomalies are detected using Elastic's Anomaly Detection feature. 
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Data Exfiltration Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- File events collected by the Elastic Defend integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Data Exfiltration Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Exfiltration
+** ID: TA0010
+** Reference URL: https://attack.mitre.org/tactics/TA0010/
+* Technique:
+** Name: Exfiltration Over Physical Medium
+** ID: T1052
+** Reference URL: https://attack.mitre.org/techniques/T1052/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-connections-made-from-a-source-ip.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-connections-made-from-a-source-ip.asciidoc
new file mode 100644
index 0000000000..9369026d8a
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-connections-made-from-a-source-ip.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-spike-in-number-of-connections-made-from-a-source-ip]]
+=== Spike in Number of Connections Made from a Source IP
+
+A machine learning job has detected a high count of destination IPs establishing an RDP connection with a single source IP. Once an attacker has gained access to one system, they might attempt to access more in the network in search of valuable assets, data, or further access points.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-12h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows RDP process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-connections-made-to-a-destination-ip.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-connections-made-to-a-destination-ip.asciidoc
new file mode 100644
index 0000000000..7320ed9ff9
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-connections-made-to-a-destination-ip.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-spike-in-number-of-connections-made-to-a-destination-ip]]
+=== Spike in Number of Connections Made to a Destination IP
+
+A machine learning job has detected a high count of source IPs establishing an RDP connection with a single destination IP. Attackers might use multiple compromised systems to attack a target to ensure redundancy in case a source IP gets detected and blocked.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-12h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows RDP process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-processes-in-an-rdp-session.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-processes-in-an-rdp-session.asciidoc
new file mode 100644
index 0000000000..ba756513a7
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-number-of-processes-in-an-rdp-session.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-spike-in-number-of-processes-in-an-rdp-session]]
+=== Spike in Number of Processes in an RDP Session
+
+A machine learning job has detected unusually high number of processes started in a single RDP session. Executing a large number of processes remotely on other machines can be an indicator of lateral movement activity.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-12h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows RDP process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-remote-file-transfers.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-remote-file-transfers.asciidoc
new file mode 100644
index 0000000000..c05202bc0f
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-spike-in-remote-file-transfers.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-spike-in-remote-file-transfers]]
+=== Spike in Remote File Transfers
+
+A machine learning job has detected an abnormal volume of remote files shared on the host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Attackers might perform multiple small transfers to match normal egress activity in the network, to evade detection.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-90m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- File events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssh-authorized-keys-file-modification.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssh-authorized-keys-file-modification.asciidoc
new file mode 100644
index 0000000000..94b5227d00
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssh-authorized-keys-file-modification.asciidoc
@@ -0,0 +1,103 @@
+[[prebuilt-rule-8-11-17-ssh-authorized-keys-file-modification]]
+=== SSH Authorized Keys File Modification
+
+The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s).
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* auditbeat-*
+* logs-endpoint.events.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* OS: macOS
+* Use Case: Threat Detection
+* Tactic: Lateral Movement
+* Tactic: Persistence
+* Data Source: Elastic Defend
+
+*Version*: 206
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.category:file and event.type:(change or creation) and
+ file.name:("authorized_keys" or "authorized_keys2" or "/etc/ssh/sshd_config" or "/root/.ssh") and
+ not process.executable:
+             (/Library/Developer/CommandLineTools/usr/bin/git or
+              /usr/local/Cellar/maven/*/libexec/bin/mvn or
+              /Library/Java/JavaVirtualMachines/jdk*.jdk/Contents/Home/bin/java or
+              /usr/bin/vim or
+              /usr/local/Cellar/coreutils/*/bin/gcat or
+              /usr/bin/bsdtar or
+              /usr/bin/nautilus or
+              /usr/bin/scp or
+              /usr/bin/touch or
+              /var/lib/docker/* or
+              /usr/bin/google_guest_agent or 
+              /opt/jc/bin/jumpcloud-agent or 
+              /opt/puppetlabs/puppet/bin/puppet or
+              /usr/bin/chef-client
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Account Manipulation
+** ID: T1098
+** Reference URL: https://attack.mitre.org/techniques/T1098/
+* Sub-technique:
+** Name: SSH Authorized Keys
+** ID: T1098.004
+** Reference URL: https://attack.mitre.org/techniques/T1098/004/
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Remote Services
+** ID: T1021
+** Reference URL: https://attack.mitre.org/techniques/T1021/
+* Sub-technique:
+** Name: SSH
+** ID: T1021.004
+** Reference URL: https://attack.mitre.org/techniques/T1021/004/
+* Technique:
+** Name: Remote Service Session Hijacking
+** ID: T1563
+** Reference URL: https://attack.mitre.org/techniques/T1563/
+* Sub-technique:
+** Name: SSH Hijacking
+** ID: T1563.001
+** Reference URL: https://attack.mitre.org/techniques/T1563/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssh-authorized-keys-file-modified-inside-a-container.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssh-authorized-keys-file-modified-inside-a-container.asciidoc
new file mode 100644
index 0000000000..355edf625f
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssh-authorized-keys-file-modified-inside-a-container.asciidoc
@@ -0,0 +1,85 @@
+[[prebuilt-rule-8-11-17-ssh-authorized-keys-file-modified-inside-a-container]]
+=== SSH Authorized Keys File Modified Inside a Container
+
+This rule detects the creation or modification of an authorized_keys or sshd_config file inside a container. The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s). Unexpected and unauthorized SSH usage inside a container can be an indicator of compromise and should be investigated.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-cloud_defend*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-6m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Data Source: Elastic Defend for Containers
+* Domain: Container
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Lateral Movement
+
+*Version*: 3
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where container.id:"*" and
+  event.type in ("change", "creation") and file.name: ("authorized_keys", "authorized_keys2", "sshd_config")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Account Manipulation
+** ID: T1098
+** Reference URL: https://attack.mitre.org/techniques/T1098/
+* Sub-technique:
+** Name: SSH Authorized Keys
+** ID: T1098.004
+** Reference URL: https://attack.mitre.org/techniques/T1098/004/
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Remote Services
+** ID: T1021
+** Reference URL: https://attack.mitre.org/techniques/T1021/
+* Sub-technique:
+** Name: SSH
+** ID: T1021.004
+** Reference URL: https://attack.mitre.org/techniques/T1021/004/
+* Technique:
+** Name: Remote Service Session Hijacking
+** ID: T1563
+** Reference URL: https://attack.mitre.org/techniques/T1563/
+* Sub-technique:
+** Name: SSH Hijacking
+** ID: T1563.001
+** Reference URL: https://attack.mitre.org/techniques/T1563/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssm-session-started-to-ec2-instance.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssm-session-started-to-ec2-instance.asciidoc
new file mode 100644
index 0000000000..ffffa98815
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-ssm-session-started-to-ec2-instance.asciidoc
@@ -0,0 +1,123 @@
+[[prebuilt-rule-8-11-17-ssm-session-started-to-ec2-instance]]
+=== SSM Session Started to EC2 Instance
+
+Identifies the first occurrence of an AWS resource establishing a session via SSM to an EC2 instance. Adversaries may use AWS Systems Manager to establish a session to an EC2 instance to execute commands on the instance. This can be used to gain access to the instance and perform actions such as privilege escalation. This rule helps detect the first occurrence of this activity for a given AWS resource.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 10m
+
+*Searches indices from*: now-60m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/systems-manager/latest/APIReference/API_StartSession.html
+* https://hackingthe.cloud/aws/post_exploitation/intercept_ssm_communications/
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: AWS SSM
+* Use Case: Threat Detection
+* Tactic: Lateral Movement
+
+*Version*: 1
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and Analysis*
+
+
+
+*Investigating SSM Session Started to EC2 Instance*
+
+
+This rule detects the first instance of an AWS resource initiating an SSM session to an EC2 instance, which could be indicative of legitimate administrative activities or potential malicious actions like command execution or lateral movement.
+
+
+*Possible Investigation Steps*
+
+
+- **Examine the Session Start Event**: Review the AWS CloudTrail log for the event.
+    - Look for the `StartSession` action and verify details such as the `user_identity.arn`, `event.action`, and the target EC2 instance (`aws.cloudtrail.flattened.request_parameters`).
+- **Verify User Identity and Role**: Check the user’s ARN and access key ID (`aws.cloudtrail.user_identity.access_key_id`).
+    - Cross-reference this with IAM to verify if the user had the necessary permissions and if their role typically requires initiating SSM sessions.
+- **Assess Geographic and IP Context**: Analyze the source IP (`source.ip`) and geographic location (`source.geo`) from which the session was initiated.
+    - Determine if these are consistent with typical user locations or if they raise suspicions of compromise or misuse.
+- **Review Session Details**: Examine details like the session ID and stream URL (`aws.cloudtrail.flattened.response_elements`) to understand the scope and nature of the session.
+    - Check if any commands executed during the session were unauthorized or out of ordinary practices.
+- **Correlate with Other Security Events**: Look for other related security events around the time of the session start to identify any pattern or broader attack vector that may involve this user or EC2 instance.
+
+
+*False Positive Analysis*
+
+
+- **Legitimate Administrative Activities**: Confirm whether the SSM session was initiated for valid administrative purposes such as system maintenance, patching, or configuration updates. Verify with the respective teams or personnel.
+
+
+*Response and Remediation*
+
+
+- **Immediate Session Review**: If the session initiation seems suspicious, review all actions taken during the session.
+    - If possible, terminate the session to prevent any potential harm.
+- **Validate and Reinforce Security Policies**: Ensure that policies around SSM session initiation are strict and adhere to the principle of least privilege.
+    - Update IAM policies if necessary to tighten controls.
+- **Incident Response Activation**: If malicious intent or actions are confirmed, activate the incident response protocol.
+    - This includes containment of the threat, eradication of the adversary’s presence, recovery of affected systems, and a thorough investigation.
+- **Enhance Monitoring and Alerts**: Improve monitoring of SSM sessions, particularly focusing on sessions that involve sensitive or critical EC2 instances.
+    - Adjust alerting mechanisms to flag unusual session initiations promptly.
+
+
+*Additional Information*
+
+
+For more in-depth understanding of managing SSM sessions and security best practices, refer to the https://docs.aws.amazon.com/systems-manager/latest/APIReference/API_StartSession.html[AWS Systems Manager documentation]. Additionally, consider the security implications and best practices outlined in https://cloud.hacktricks.xyz/pentesting-cloud/aws-security/aws-privilege-escalation/aws-ssm-privesc[AWS SSM privilege escalation techniques].
+
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset:"aws.cloudtrail" and event.provider:"ssm.amazonaws.com"
+    and event.action:"StartSession" and event.outcome:"success"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Remote Services
+** ID: T1021
+** Reference URL: https://attack.mitre.org/techniques/T1021/
+* Sub-technique:
+** Name: Cloud Services
+** ID: T1021.007
+** Reference URL: https://attack.mitre.org/techniques/T1021/007/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity-with-high-confidence.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity-with-high-confidence.asciidoc
new file mode 100644
index 0000000000..5ce5952e08
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity-with-high-confidence.asciidoc
@@ -0,0 +1,96 @@
+[[prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity-with-high-confidence]]
+=== Statistical Model Detected C2 Beaconing Activity with High Confidence
+
+A statistical model has identified command-and-control (C2) beaconing activity with high confidence. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* ml_beaconing.all
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-1h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/beaconing
+* https://www.elastic.co/security-labs/identifying-beaconing-malware-using-elastic
+
+*Tags*: 
+
+* Domain: Network
+* Use Case: C2 Beaconing Detection
+* Tactic: Command and Control
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Network Beaconing Identification integration assets to be installed, as well as network logs collected by the Elastic Defend or Network Packet Capture integrations.
+
+
+*Network Beaconing Identification Setup*
+
+The Network Beaconing Identification integration consists of a statistical framework to identify C2 beaconing activity in network logs.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Network Beaconing Identification.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Network events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] or https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the Network Beaconing Identification integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Network Beaconing Identification and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+beacon_stats.beaconing_score: 3
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Web Service
+** ID: T1102
+** Reference URL: https://attack.mitre.org/techniques/T1102/
+* Sub-technique:
+** Name: Bidirectional Communication
+** ID: T1102.002
+** Reference URL: https://attack.mitre.org/techniques/T1102/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity.asciidoc
new file mode 100644
index 0000000000..2dfad22fc4
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity.asciidoc
@@ -0,0 +1,97 @@
+[[prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity]]
+=== Statistical Model Detected C2 Beaconing Activity
+
+A statistical model has identified command-and-control (C2) beaconing activity. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* ml_beaconing.all
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-1h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/beaconing
+* https://www.elastic.co/security-labs/identifying-beaconing-malware-using-elastic
+
+*Tags*: 
+
+* Domain: Network
+* Use Case: C2 Beaconing Detection
+* Tactic: Command and Control
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Network Beaconing Identification integration assets to be installed, as well as network logs collected by the Elastic Defend or Network Packet Capture integrations.
+
+
+*Network Beaconing Identification Setup*
+
+The Network Beaconing Identification integration consists of a statistical framework to identify C2 beaconing activity in network logs.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Network Beaconing Identification.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Network events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] or https://docs.elastic.co/integrations/network_traffic[Network Packet Capture] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To add the Network Packet Capture integration to an Elastic Agent policy, refer to https://www.elastic.co/guide/en/fleet/current/add-integration-to-policy.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the Network Beaconing Identification integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Network Beaconing Identification and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+beacon_stats.is_beaconing: true and
+not process.name: ("WaAppAgent.exe" or "metricbeat.exe" or "packetbeat.exe" or "WindowsAzureGuestAgent.exe" or "HealthService.exe" or "Widgets.exe" or "lsass.exe" or "msedgewebview2.exe" or "MsMpEng.exe" or "OUTLOOK.EXE" or "msteams.exe" or "FileSyncHelper.exe" or "SearchProtocolHost.exe" or "Creative Cloud.exe" or "ms-teams.exe" or "ms-teamsupdate.exe" or "curl.exe" or "rundll32.exe" or "MsSense.exe" or "wermgr.exe" or "java" or "olk.exe" or "iexplore.exe" or "NetworkManager" or "packetbeat" or "Ssms.exe" or "NisSrv.exe" or "gamingservices.exe" or "appidcertstorecheck.exe" or "POWERPNT.EXE" or "miiserver.exe" or "Grammarly.Desktop.exe" or "SnagitEditor.exe" or "CRWindowsClientService.exe")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Web Service
+** ID: T1102
+** Reference URL: https://attack.mitre.org/techniques/T1102/
+* Sub-technique:
+** Name: Bidirectional Communication
+** ID: T1102.002
+** Reference URL: https://attack.mitre.org/techniques/T1102/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-antimalware-scan-interface-dll.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-antimalware-scan-interface-dll.asciidoc
new file mode 100644
index 0000000000..b75df4df49
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-antimalware-scan-interface-dll.asciidoc
@@ -0,0 +1,144 @@
+[[prebuilt-rule-8-11-17-suspicious-antimalware-scan-interface-dll]]
+=== Suspicious Antimalware Scan Interface DLL
+
+Identifies the creation of the Antimalware Scan Interface (AMSI) DLL in an unusual location. This may indicate an attempt to bypass AMSI by loading a rogue AMSI module instead of the legit one.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.file-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://github.com/S3cur3Th1sSh1t/Amsi-Bypass-Powershell
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 111
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Suspicious Antimalware Scan Interface DLL*
+
+
+The Windows Antimalware Scan Interface (AMSI) is a versatile interface standard that allows your applications and services to integrate with any antimalware product on a machine. AMSI integrates with multiple Windows components, ranging from User Account Control (UAC) to VBA macros and PowerShell.
+
+Attackers might copy a rogue AMSI DLL to an unusual location to prevent the process from loading the legitimate module, achieving a bypass to execute malicious code.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Identify the process that created the DLL and which account was used.
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Investigate the execution of scripts and macros after the registry modification.
+- Investigate other processes launched from the directory that the DLL was created.
+- Inspect the host for suspicious or abnormal behavior in the alert timeframe:
+  - Observe and collect information about the following activities in the alert subject host:
+    - Attempts to contact external domains and addresses.
+      - Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' `process.entity_id`.
+      - Examine the DNS cache for suspicious or anomalous entries.
+        - !{osquery{"label":"Osquery - Retrieve DNS Cache","query":"SELECT * FROM dns_cache"}}
+    - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
+    - Examine the host services for suspicious or anomalous entries.
+      - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+      - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+
+
+*False positive analysis*
+
+
+- This modification should not happen legitimately. Any potential benign true positive (B-TP) should be mapped and monitored by the security team as these modifications expose the host to malware infections.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "windows" and event.type != "deletion" and file.path != null and
+ file.name : ("amsi.dll", "amsi") and not file.path : ("?:\\Windows\\system32\\amsi.dll", "?:\\Windows\\Syswow64\\amsi.dll", "?:\\$WINDOWS.~BT\\NewOS\\Windows\\WinSXS\\*", "?:\\$WINDOWS.~BT\\NewOS\\Windows\\servicing\\LCU\\*", "?:\\$WINDOWS.~BT\\Work\\*\\*", "?:\\Windows\\SoftwareDistribution\\Download\\*")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Tools
+** ID: T1562.001
+** Reference URL: https://attack.mitre.org/techniques/T1562/001/
+* Technique:
+** Name: Hijack Execution Flow
+** ID: T1574
+** Reference URL: https://attack.mitre.org/techniques/T1574/
+* Sub-technique:
+** Name: DLL Search Order Hijacking
+** ID: T1574.001
+** Reference URL: https://attack.mitre.org/techniques/T1574/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-endpoint-security-parent-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-endpoint-security-parent-process.asciidoc
new file mode 100644
index 0000000000..f58d22752d
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-endpoint-security-parent-process.asciidoc
@@ -0,0 +1,106 @@
+[[prebuilt-rule-8-11-17-suspicious-endpoint-security-parent-process]]
+=== Suspicious Endpoint Security Parent Process
+
+A suspicious Endpoint Security parent process was detected. This may indicate a process hollowing or other form of code injection.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  process.name : ("esensor.exe", "elastic-endpoint.exe") and
+  process.parent.executable != null and
+  /* add FPs here */
+  not process.parent.executable : (
+        "?:\\Program Files\\Elastic\\*",
+        "?:\\Windows\\System32\\services.exe",
+        "?:\\Windows\\System32\\WerFault*.exe",
+        "?:\\Windows\\System32\\wermgr.exe",
+        "?:\\Windows\\explorer.exe"
+  ) and
+  not (
+    process.parent.executable : (
+        "?:\\Windows\\System32\\cmd.exe",
+        "?:\\Windows\\System32\\SecurityHealthHost.exe",
+        "?:\\Windows\\System32\\WindowsPowerShell\\v1.0\\powershell.exe"
+    ) and
+    process.args : (
+        "test", "version",
+        "top", "run",
+        "*help", "status",
+        "upgrade", "/launch",
+        "/enable"
+    )
+  )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Sub-technique:
+** Name: Match Legitimate Name or Location
+** ID: T1036.005
+** Reference URL: https://attack.mitre.org/techniques/T1036/005/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-creation-in-etc-for-persistence.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-creation-in-etc-for-persistence.asciidoc
new file mode 100644
index 0000000000..699df5c4dc
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-creation-in-etc-for-persistence.asciidoc
@@ -0,0 +1,245 @@
+[[prebuilt-rule-8-11-17-suspicious-file-creation-in-etc-for-persistence]]
+=== Suspicious File Creation in /etc for Persistence
+
+Detects the manual creation of files in specific etc directories, via user root, used by Linux malware to persist and elevate privileges on compromised systems. File creation in these directories should not be entirely common and could indicate a malicious binary or script installing persistence mechanisms for long term access.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.intezer.com/blog/incident-response/orbit-new-undetected-linux-threat/
+* https://www.intezer.com/blog/research/lightning-framework-new-linux-threat/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Threat: Orbit
+* Threat: Lightning Framework
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 114
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Suspicious File Creation in /etc for Persistence*
+
+
+The /etc/ directory in Linux is used to store system-wide configuration files and scripts.
+
+By creating or modifying specific system-wide configuration files, attackers can leverage system services to execute malicious commands or scripts at predefined intervals, ensuring their continued presence and enabling unauthorized activities.
+
+This rule monitors for the creation of the most common system-wide configuration files and scripts abused by attackers for persistence. 
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the file that was created or modified.
+- Investigate whether any other files in any of the commonly abused directories have been altered through OSQuery.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/etc/ld.so.conf.d/%' OR path LIKE '/etc/cron.d/%' OR path LIKE '/etc/sudoers.d/%'\nOR path LIKE '/etc/rc%.d/%' OR path LIKE '/etc/init.d/%' OR path LIKE '/etc/systemd/system/%' OR path LIKE\n'/usr/lib/systemd/system/%' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/etc/ld.so.conf.d/%' OR path LIKE\n'/etc/cron.d/%' OR path LIKE '/etc/sudoers.d/%' OR path LIKE '/etc/rc%.d/%' OR path LIKE '/etc/init.d/%' OR path LIKE\n'/etc/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' )\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator that performed these actions for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- Cron Job Created or Changed by Previously Unknown Process - ff10d4d8-fea7-422d-afb1-e5a2702369a9
+- Potential Persistence Through Run Control Detected - 0f4d35e4-925e-4959-ab24-911be207ee6f
+- Potential Persistence Through init.d Detected - 474fd20e-14cc-49c5-8160-d9ab4ba16c8b
+- New Systemd Timer Created - 7fb500fa-8e24-4bd1-9480-2a819352602c
+- New Systemd Service Created by Previously Unknown Process - 17b0a495-4d9f-414c-8ad0-92f018b8e001
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service/timer or restore its original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "linux" and event.type in ("creation", "file_create_event") and user.id == "0" and
+file.path : ("/etc/ld.so.conf.d/*", "/etc/cron.d/*", "/etc/sudoers.d/*", "/etc/rc.d/init.d/*", "/etc/systemd/system/*",
+"/usr/lib/systemd/system/*") and not (
+  (process.name : (
+    "chef-client", "ruby", "pacman", "packagekitd", "python*", "platform-python", "dpkg", "yum", "apt", "dnf", "rpm",
+    "systemd", "snapd", "dnf-automatic", "yum-cron", "elastic-agent", "dnfdaemon-system", "dockerd", "executor",
+    "rhn_check"
+    )
+  ) or 
+  (file.extension in ("swp", "swpx", "tmp"))
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Boot or Logon Initialization Scripts
+** ID: T1037
+** Reference URL: https://attack.mitre.org/techniques/T1037/
+* Sub-technique:
+** Name: RC Scripts
+** ID: T1037.004
+** Reference URL: https://attack.mitre.org/techniques/T1037/004/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Systemd Service
+** ID: T1543.002
+** Reference URL: https://attack.mitre.org/techniques/T1543/002/
+* Technique:
+** Name: Hijack Execution Flow
+** ID: T1574
+** Reference URL: https://attack.mitre.org/techniques/T1574/
+* Sub-technique:
+** Name: Dynamic Linker Hijacking
+** ID: T1574.006
+** Reference URL: https://attack.mitre.org/techniques/T1574/006/
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Scheduled Task/Job
+** ID: T1053
+** Reference URL: https://attack.mitre.org/techniques/T1053/
+* Sub-technique:
+** Name: Cron
+** ID: T1053.003
+** Reference URL: https://attack.mitre.org/techniques/T1053/003/
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Sudo and Sudo Caching
+** ID: T1548.003
+** Reference URL: https://attack.mitre.org/techniques/T1548/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-creation-via-kworker.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-creation-via-kworker.asciidoc
new file mode 100644
index 0000000000..92b2da135e
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-creation-via-kworker.asciidoc
@@ -0,0 +1,193 @@
+[[prebuilt-rule-8-11-17-suspicious-file-creation-via-kworker]]
+=== Suspicious File Creation via Kworker
+
+This rule monitors for a file creation event originating from a kworker parent process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Defense Evasion
+* Data Source: Elastic Defend
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Suspicious File Creation via Kworker*
+
+
+Kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks.
+
+Attackers may attempt to evade detection by masquerading as a kernel worker process.
+
+This rule monitors for suspicious file creation events through the kworker process. This is not common, and could indicate malicious behaviour.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the file that was created or modified through OSQuery.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE path = {{file.path}}\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE path = {{file.path}}\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator that performed these actions for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- Suspicious Kworker UID Elevation - 7dfaaa17-425c-4fe7-bd36-83705fde7c2b
+- Network Activity Detected via Kworker - 25d917c4-aa3c-4111-974c-286c0312ff95
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows
+the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click Add integrations.
+- In the query bar, search for Elastic Defend and select the integration to see more details about it.
+- Click Add Elastic Defend.
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either Traditional Endpoints or Cloud Workloads.
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest to select "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in New agent policy name. If other agent policies already exist, you can click the Existing hosts tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click Save and Continue.
+- To complete the integration, select Add Elastic Agent to your hosts and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "linux" and event.action in ("creation", "file_create_event") and
+  process.name : "kworker*" and not (
+    (process.name : "kworker*kcryptd*") or
+    (file.path : ("/var/log/*", "/var/crash/*", "/var/run/*", "/var/lib/systemd/coredump/*", "/var/spool/*"))
+  )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Boot or Logon Autostart Execution
+** ID: T1547
+** Reference URL: https://attack.mitre.org/techniques/T1547/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Rootkit
+** ID: T1014
+** Reference URL: https://attack.mitre.org/techniques/T1014/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-renamed-via-smb.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-renamed-via-smb.asciidoc
new file mode 100644
index 0000000000..49bdf4d129
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-file-renamed-via-smb.asciidoc
@@ -0,0 +1,138 @@
+[[prebuilt-rule-8-11-17-suspicious-file-renamed-via-smb]]
+=== Suspicious File Renamed via SMB
+
+Identifies an incoming SMB connection followed by a suspicious file rename operation. This may indicate a remote ransomware attack via the SMB protocol.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://news.sophos.com/en-us/2023/12/21/akira-again-the-ransomware-that-keeps-on-taking/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Impact
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 2
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Performance*
+
+
+- This rule may cause medium to high performance impact due to logic scoping all icoming SMB network events.
+
+
+*Possible investigation steps*
+
+
+- Investigate the source.ip address connecting to port 445 on this host.
+- Identify the user account that performed the file creation via SMB.
+- If the number of files is too high and source.ip connecting over SMB is unusual isolate the host and block the used credentials.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+
+
+*False positive analysis*
+
+
+- Remote file rename over SMB.
+
+
+*Related rules*
+
+
+- Third-party Backup Files Deleted via Unexpected Process - 11ea6bec-ebde-4d71-a8e9-784948f8e3e9
+- Volume Shadow Copy Deleted or Resized via VssAdmin - b5ea4bfe-a1b2-421f-9d47-22a75a6f2921
+- Volume Shadow Copy Deletion via PowerShell - d99a037b-c8e2-47a5-97b9-170d076827c4
+- Volume Shadow Copy Deletion via WMIC - dc9c1f74-dac3-48e3-b47f-eb79db358f57
+- Potential Ransomware Note File Dropped via SMB - 02bab13d-fb14-4d7c-b6fe-4a28874d37c5
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Consider isolating the involved host to prevent destructive behavior, which is commonly associated with this activity.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- If any other destructive action was identified on the host, it is recommended to prioritize the investigation and look for ransomware preparation and execution activities.
+- If any backups were affected:
+  - Perform data recovery locally or restore the backups from replicated copies (cloud, other servers, etc.).
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by host.id with maxspan=1s
+ [network where host.os.type == "windows" and
+  event.action == "connection_accepted" and destination.port == 445 and source.port >= 49152 and process.pid == 4 and
+  source.ip != "127.0.0.1" and source.ip != "::1"]
+ [file where host.os.type == "windows" and
+  event.action == "rename" and process.pid == 4 and user.id : ("S-1-5-21*", "S-1-12-*") and
+  file.extension != null and file.Ext.entropy >= 6 and
+  file.Ext.original.name : ("*.jpg", "*.bmp", "*.png", "*.pdf", "*.doc", "*.docx", "*.xls", "*.xlsx", "*.ppt", "*.pptx", "*.lnk") and
+  not file.extension : ("jpg", "bmp", "png", "pdf", "doc", "docx", "xls", "xlsx", "ppt", "pptx", "*.lnk")] with runs=3
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Impact
+** ID: TA0040
+** Reference URL: https://attack.mitre.org/tactics/TA0040/
+* Technique:
+** Name: Data Destruction
+** ID: T1485
+** Reference URL: https://attack.mitre.org/techniques/T1485/
+* Technique:
+** Name: Inhibit System Recovery
+** ID: T1490
+** Reference URL: https://attack.mitre.org/techniques/T1490/
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Remote Services
+** ID: T1021
+** Reference URL: https://attack.mitre.org/techniques/T1021/
+* Sub-technique:
+** Name: SMB/Windows Admin Shares
+** ID: T1021.002
+** Reference URL: https://attack.mitre.org/techniques/T1021/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-macos-ms-office-child-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-macos-ms-office-child-process.asciidoc
new file mode 100644
index 0000000000..b5ba942b78
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-macos-ms-office-child-process.asciidoc
@@ -0,0 +1,168 @@
+[[prebuilt-rule-8-11-17-suspicious-macos-ms-office-child-process]]
+=== Suspicious macOS MS Office Child Process
+
+Identifies suspicious child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, and Excel). These child processes are often launched during exploitation of Office applications or by documents with malicious macros.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://blog.malwarebytes.com/cybercrime/2017/02/microsoft-office-macro-malware-targets-macs/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: macOS
+* Use Case: Threat Detection
+* Tactic: Initial Access
+* Data Source: Elastic Defend
+
+*Version*: 207
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a macOS System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, for MacOS it is recommended to select "Traditional Endpoints".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/current/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where event.action == "exec" and host.os.type == "macos" and
+    process.parent.name: (
+      "Microsoft Word",
+      "Microsoft Outlook",
+      "Microsoft Excel",
+      "Microsoft PowerPoint",
+      "Microsoft OneNote"
+    ) and
+  process.name : (
+    "curl",
+    "nscurl",
+    "bash",
+    "sh",
+    "osascript",
+    "python*",
+    "perl*",
+    "mktemp",
+    "chmod",
+    "php",
+    "nohup",
+    "openssl",
+    "plutil",
+    "PlistBuddy",
+    "xattr",
+    "mktemp",
+    "sqlite3",
+    "funzip",
+    "popen"
+  ) and
+
+  // Filter FPs related to product version discovery and Office error reporting behavior
+  not process.args:
+    (
+      "ProductVersion",
+      "hw.model",
+      "ioreg",
+      "ProductName",
+      "ProductUserVisibleVersion",
+      "ProductBuildVersion",
+      "/Library/Application Support/Microsoft/MERP*/Microsoft Error Reporting.app/Contents/MacOS/Microsoft Error Reporting",
+      "open -a Safari *",
+      "defaults read *",
+      "sysctl hw.model*",
+      "ioreg -d2 -c IOPlatformExpertDevice *",
+      "ps aux | grep 'ToDesk_Desktop' | grep -v grep",
+      "PIPE=\"$CFFIXED_USER_HOME/.zoteroIntegrationPipe*"
+    ) and
+
+   not process.parent.executable :
+        (
+          "/Applications/ToDesk.app/Contents/MacOS/ToDesk_Service",
+          "/usr/local/Privacy-i/PISupervisor",
+          "/Library/Addigy/lan-cache",
+          "/Library/Elastic/Agent/*",
+          "/opt/jc/bin/jumpcloud-agent",
+          "/usr/sbin/networksetup"
+        ) and
+   not (process.name : "sh" and process.command_line : "*$CFFIXED_USER_HOME/.zoteroIntegrationPipe*") and
+
+   not process.Ext.effective_parent.executable : (
+        "/Applications/ToDesk.app/Contents/MacOS/ToDesk_Service",
+        "/usr/local/Privacy-i/PISupervisor",
+        "/Library/Addigy/auditor",
+        "/Library/Elastic/Agent/*",
+        "/opt/jc/bin/jumpcloud-agent",
+        "/usr/sbin/networksetup"
+      )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Initial Access
+** ID: TA0001
+** Reference URL: https://attack.mitre.org/tactics/TA0001/
+* Technique:
+** Name: Phishing
+** ID: T1566
+** Reference URL: https://attack.mitre.org/techniques/T1566/
+* Sub-technique:
+** Name: Spearphishing Attachment
+** ID: T1566.001
+** Reference URL: https://attack.mitre.org/techniques/T1566/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-microsoft-365-mail-access-by-clientappid.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-microsoft-365-mail-access-by-clientappid.asciidoc
new file mode 100644
index 0000000000..28edc77700
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-microsoft-365-mail-access-by-clientappid.asciidoc
@@ -0,0 +1,140 @@
+[[prebuilt-rule-8-11-17-suspicious-microsoft-365-mail-access-by-clientappid]]
+=== Suspicious Microsoft 365 Mail Access by ClientAppId
+
+Identifies when a Microsoft 365 Mailbox is accessed by a ClientAppId that was observed for the fist time during the last 10 days.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-o365*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-30m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-193a
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: Microsoft 365
+* Use Case: Configuration Audit
+* Tactic: Initial Access
+
+*Version*: 106
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Suspicious Microsoft 365 Mail Access by ClientAppId*
+
+
+- Verify the ClientAppId, source.ip and geolocation associated with Mail Access.
+- Verify the total number of used ClientAppId by that specific user.id.
+- Verify if the mailbox owner was on leave and just resumed working or not.
+- Verify if there are other alerts associated with the same user.id.
+- Verify the total number of connections from that ClientAppId, if it's accessing other mailboxes and with a high frequency there is a high chance it's a false positive.
+
+
+*False positive analysis*
+
+
+- Legit Microsoft or third party ClientAppId.
+- User changing of ClientAppId or new connection post an extended period of leave.
+- If the total number of accessed Mailboxes by ClientAppId is too high there is a high chance it's a false positive.
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The Office 365 Logs Fleet integration, Filebeat module, or similarly structured data is required to be compatible with this rule.
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset:o365.audit and event.provider:Exchange and event.category:web and event.action:MailItemsAccessed and event.outcome:success and 
+not o365.audit.ClientAppId : ("13937bba-652e-4c46-b222-3003f4d1ff97" or "6326e366-9d6d-4c70-b22a-34c7ea72d73d" or 
+ "a3883eba-fbe9-48bd-9ed3-dca3e0e84250" or "d3590ed6-52b3-4102-aeff-aad2292ab01c" or "27922004-5251-4030-b22d-91ecd9a37ea4" or 
+ "1fec8e78-bce4-4aaf-ab1b-5451cc387264" or "26a7ee05-5602-4d76-a7ba-eae8b7b67941" or "00000002-0000-0000-c000-000000000000" or 
+ "00000002-0000-0ff1-ce00-000000000000" or "00000003-0000-0000-c000-000000000000" or "ffcb16e8-f789-467c-8ce9-f826a080d987" or 
+ "00000003-0000-0ff1-ce00-000000000000" or "00000004-0000-0ff1-ce00-000000000000" or "00000005-0000-0ff1-ce00-000000000000" or 
+ "00000006-0000-0ff1-ce00-000000000000" or "00000007-0000-0000-c000-000000000000" or "00000007-0000-0ff1-ce00-000000000000" or 
+ "00000009-0000-0000-c000-000000000000" or "0000000c-0000-0000-c000-000000000000" or "00000015-0000-0000-c000-000000000000" or 
+ "0000001a-0000-0000-c000-000000000000" or "00b41c95-dab0-4487-9791-b9d2c32c80f2" or "022907d3-0f1b-48f7-badc-1ba6abab6d66" or 
+ "04b07795-8ddb-461a-bbee-02f9e1bf7b46" or "08e18876-6177-487e-b8b5-cf950c1e598c" or "0cb7b9ec-5336-483b-bc31-b15b5788de71" or 
+ "0cd196ee-71bf-4fd6-a57c-b491ffd4fb1e" or "0f698dd4-f011-4d23-a33e-b36416dcb1e6" or "13937bba-652e-4c46-b222-3003f4d1ff97" or 
+ "14d82eec-204b-4c2f-b7e8-296a70dab67e" or "16aeb910-ce68-41d1-9ac3-9e1673ac9575" or "1786c5ed-9644-47b2-8aa0-7201292175b6" or 
+ "17d5e35f-655b-4fb0-8ae6-86356e9a49f5" or "18fbca16-2224-45f6-85b0-f7bf2b39b3f3" or "1950a258-227b-4e31-a9cf-717495945fc2" or 
+ "1b3c667f-cde3-4090-b60b-3d2abd0117f0" or "1fec8e78-bce4-4aaf-ab1b-5451cc387264" or "20a11fe0-faa8-4df5-baf2-f965f8f9972e" or 
+ "23523755-3a2b-41ca-9315-f81f3f566a95" or "243c63a3-247d-41c5-9d83-7788c43f1c43" or "268761a2-03f3-40df-8a8b-c3db24145b6b" or 
+ "26a7ee05-5602-4d76-a7ba-eae8b7b67941" or "26abc9a8-24f0-4b11-8234-e86ede698878" or "27922004-5251-4030-b22d-91ecd9a37ea4" or 
+ "28b567f6-162c-4f54-99a0-6887f387bbcc" or "29d9ed98-a469-4536-ade2-f981bc1d605e" or "2abdc806-e091-4495-9b10-b04d93c3f040" or 
+ "2d4d3d8e-2be3-4bef-9f87-7875a61c29de" or "2d7f3606-b07d-41d1-b9d2-0d0c9296a6e8" or "3090ab82-f1c1-4cdf-af2c-5d7a6f3e2cc7" or 
+ "35d54a08-36c9-4847-9018-93934c62740c" or "37182072-3c9c-4f6a-a4b3-b3f91cacffce" or "38049638-cc2c-4cde-abe4-4479d721ed44" or 
+ "3c896ded-22c5-450f-91f6-3d1ef0848f6e" or "4345a7b9-9a63-4910-a426-35363201d503" or "45a330b1-b1ec-4cc1-9161-9f03992aa49f" or 
+ "47629505-c2b6-4a80-adb1-9b3a3d233b7b" or "4765445b-32c6-49b0-83e6-1d93765276ca" or "497effe9-df71-4043-a8bb-14cf78c4b63b" or 
+ "4b233688-031c-404b-9a80-a4f3f2351f90" or "4d5c2d63-cf83-4365-853c-925fd1a64357" or "51be292c-a17e-4f17-9a7e-4b661fb16dd2" or 
+ "5572c4c0-d078-44ce-b81c-6cbf8d3ed39e" or "5e3ce6c0-2b1f-4285-8d4b-75ee78787346" or "60c8bde5-3167-4f92-8fdb-059f6176dc0f" or 
+ "61109738-7d2b-4a0b-9fe3-660b1ff83505" or "62256cef-54c0-4cb4-bcac-4c67989bdc40" or "6253bca8-faf2-4587-8f2f-b056d80998a7" or 
+ "65d91a3d-ab74-42e6-8a2f-0add61688c74" or "66a88757-258c-4c72-893c-3e8bed4d6899" or "67e3df25-268a-4324-a550-0de1c7f97287" or 
+ "69893ee3-dd10-4b1c-832d-4870354be3d8" or "74658136-14ec-4630-ad9b-26e160ff0fc6" or "74bcdadc-2fdc-4bb3-8459-76d06952a0e9" or 
+ "797f4846-ba00-4fd7-ba43-dac1f8f63013" or "7ab7862c-4c57-491e-8a45-d52a7e023983" or "7ae974c5-1af7-4923-af3a-fb1fd14dcb7e" or 
+ "7b7531ad-5926-4f2d-8a1d-38495ad33e17" or "80ccca67-54bd-44ab-8625-4b79c4dc7775" or "835b2a73-6e10-4aa5-a979-21dfda45231c" or 
+ "871c010f-5e61-4fb1-83ac-98610a7e9110" or "89bee1f7-5e6e-4d8a-9f3d-ecd601259da7" or "8edd93e1-2103-40b4-bd70-6e34e586362d" or 
+ "905fcf26-4eb7-48a0-9ff0-8dcc7194b5ba" or "91ca2ca5-3b3e-41dd-ab65-809fa3dffffa" or "93625bc8-bfe2-437a-97e0-3d0060024faa" or 
+ "93d53678-613d-4013-afc1-62e9e444a0a5" or "944f0bd1-117b-4b1c-af26-804ed95e767e" or "94c63fef-13a3-47bc-8074-75af8c65887a" or 
+ "95de633a-083e-42f5-b444-a4295d8e9314" or "97cb1f73-50df-47d1-8fb0-0271f2728514" or "98db8bd6-0cc0-4e67-9de5-f187f1cd1b41" or 
+ "99b904fd-a1fe-455c-b86c-2f9fb1da7687" or "9ea1ad79-fdb6-4f9a-8bc3-2b70f96e34c7" or "a3475900-ccec-4a69-98f5-a65cd5dc5306" or 
+ "a3b79187-70b2-4139-83f9-6016c58cd27b" or "a57aca87-cbc0-4f3c-8b9e-dc095fdc8978" or "a970bac6-63fe-4ec5-8884-8536862c42d4" or 
+ "a9b49b65-0a12-430b-9540-c80b3332c127" or "ab9b8c07-8f02-4f72-87fa-80105867a763" or "ae8e128e-080f-4086-b0e3-4c19301ada69" or 
+ "b23dd4db-9142-4734-867f-3577f640ad0c" or "b4bddae8-ab25-483e-8670-df09b9f1d0ea" or "b669c6ea-1adf-453f-b8bc-6d526592b419" or 
+ "b6e69c34-5f1f-4c34-8cdf-7fea120b8670" or "bb2a2e3a-c5e7-4f0a-88e0-8e01fd3fc1f4" or "bdd48c81-3a58-4ea9-849c-ebea7f6b6360" or 
+ "c1c74fed-04c9-4704-80dc-9f79a2e515cb" or "c35cb2ba-f88b-4d15-aa9d-37bd443522e1" or "c44b4083-3bb0-49c1-b47d-974e53cbdf3c" or 
+ "c9a559d2-7aab-4f13-a6ed-e7e9c52aec87" or "cc15fd57-2c6c-4117-a88c-83b1d56b4bbe" or "cf36b471-5b44-428c-9ce7-313bf84528de" or 
+ "cf53fce8-def6-4aeb-8d30-b158e7b1cf83" or "d176f6e7-38e5-40c9-8a78-3998aab820e7" or "d3590ed6-52b3-4102-aeff-aad2292ab01c" or 
+ "d73f4b35-55c9-48c7-8b10-651f6f2acb2e" or "d9b8ec3a-1e4e-4e08-b3c2-5baf00c0fcb0" or "de8bc8b5-d9f9-48b1-a8ad-b748da725064" or 
+ "dfe74da8-9279-44ec-8fb2-2aed9e1c73d0" or "e1ef36fd-b883-4dbf-97f0-9ece4b576fc6" or "e64aa8bc-8eb4-40e2-898b-cf261a25954f" or 
+ "e9f49c6b-5ce5-44c8-925d-015017e9f7ad" or "ee272b19-4411-433f-8f28-5c13cb6fd407" or "f5eaa862-7f08-448c-9c4e-f4047d4d4521" or 
+ "fb78d390-0c51-40cd-8e17-fdbfab77341b" or "fc0f3af4-6835-4174-b806-f7db311fd2f3" or "fdf9885b-dd37-42bf-82e5-c3129ef5a302")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Initial Access
+** ID: TA0001
+** Reference URL: https://attack.mitre.org/tactics/TA0001/
+* Technique:
+** Name: Valid Accounts
+** ID: T1078
+** Reference URL: https://attack.mitre.org/techniques/T1078/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-ms-outlook-child-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-ms-outlook-child-process.asciidoc
new file mode 100644
index 0000000000..63f0396564
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-ms-outlook-child-process.asciidoc
@@ -0,0 +1,181 @@
+[[prebuilt-rule-8-11-17-suspicious-ms-outlook-child-process]]
+=== Suspicious MS Outlook Child Process
+
+Identifies suspicious child processes of Microsoft Outlook. These child processes are often associated with spear phishing activity.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Initial Access
+* Tactic: Defense Evasion
+* Tactic: Execution
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: SentinelOne
+
+*Version*: 213
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Suspicious MS Outlook Child Process*
+
+
+Microsoft Outlook is an email client that provides contact, email calendar, and task management features. Outlook is widely used, either standalone or as part of the Office suite.
+
+This rule looks for suspicious processes spawned by MS Outlook, which can be the result of the execution of malicious documents and/or exploitation for initial access.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Retrieve recently opened files received via email and opened by the user that could cause this behavior. Common locations include but are not limited to, the Downloads and Document folders and the folder configured at the email client.
+- Determine if the collected files are malicious:
+  - Use a private sandboxed malware analysis system to perform analysis.
+    - Observe and collect information about the following activities:
+      - Attempts to contact external domains and addresses.
+      - File and registry access, modification, and creation activities.
+      - Service creation and launch activities.
+      - Scheduled task creation.
+  - Use the PowerShell Get-FileHash cmdlet to get the files' SHA-256 hash values.
+    - Search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+  - If the malicious file was delivered via phishing:
+    - Block the email sender from sending future emails.
+    - Block the malicious web pages.
+    - Remove emails from the sender from mailboxes.
+    - Consider improvements to the security awareness program.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  process.parent.name : "outlook.exe" and
+  process.name : ("Microsoft.Workflow.Compiler.exe", "arp.exe", "atbroker.exe", "bginfo.exe", "bitsadmin.exe",
+                  "cdb.exe", "certutil.exe", "cmd.exe", "cmstp.exe", "cscript.exe", "csi.exe", "dnx.exe", "dsget.exe",
+                  "dsquery.exe", "forfiles.exe", "fsi.exe", "ftp.exe", "gpresult.exe", "hostname.exe", "ieexec.exe",
+                  "iexpress.exe", "installutil.exe", "ipconfig.exe", "mshta.exe", "msxsl.exe", "nbtstat.exe", "net.exe",
+                  "net1.exe", "netsh.exe", "netstat.exe", "nltest.exe", "odbcconf.exe", "ping.exe", "powershell.exe",
+                  "pwsh.exe", "qprocess.exe", "quser.exe", "qwinsta.exe", "rcsi.exe", "reg.exe", "regasm.exe",
+                  "regsvcs.exe", "regsvr32.exe", "sc.exe", "schtasks.exe", "systeminfo.exe", "tasklist.exe",
+                  "tracert.exe", "whoami.exe", "wmic.exe", "wscript.exe", "xwizard.exe")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Initial Access
+** ID: TA0001
+** Reference URL: https://attack.mitre.org/tactics/TA0001/
+* Technique:
+** Name: Phishing
+** ID: T1566
+** Reference URL: https://attack.mitre.org/techniques/T1566/
+* Sub-technique:
+** Name: Spearphishing Attachment
+** ID: T1566.001
+** Reference URL: https://attack.mitre.org/techniques/T1566/001/
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
+* Sub-technique:
+** Name: PowerShell
+** ID: T1059.001
+** Reference URL: https://attack.mitre.org/techniques/T1059/001/
+* Sub-technique:
+** Name: Windows Command Shell
+** ID: T1059.003
+** Reference URL: https://attack.mitre.org/techniques/T1059/003/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: System Binary Proxy Execution
+** ID: T1218
+** Reference URL: https://attack.mitre.org/techniques/T1218/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-network-activity-to-the-internet-by-previously-unknown-executable.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-network-activity-to-the-internet-by-previously-unknown-executable.asciidoc
new file mode 100644
index 0000000000..3efbff5837
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-network-activity-to-the-internet-by-previously-unknown-executable.asciidoc
@@ -0,0 +1,241 @@
+[[prebuilt-rule-8-11-17-suspicious-network-activity-to-the-internet-by-previously-unknown-executable]]
+=== Suspicious Network Activity to the Internet by Previously Unknown Executable
+
+This rule monitors for network connectivity to the internet from a previously unknown executable located in a suspicious directory. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to establish connections to unknown or suspicious destinations such as a command and control server. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* auditbeat-*
+* filebeat-*
+* packetbeat-*
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-59m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Command and Control
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 9
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Suspicious Network Activity to the Internet by Previously Unknown Executable*
+
+
+After being installed, malware will often call out to its command and control server to receive further instructions by its operators.
+
+This rule leverages the new terms rule type to detect previously unknown processes, initiating network connections to external IP-addresses. 
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible investigation steps*
+
+
+- Identify any signs of suspicious network activity or anomalies that may indicate malicious behavior. This could include unexpected traffic patterns or unusual network behavior.
+  - Investigate listening ports and open sockets to look for potential malicious processes, reverse shells or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+- Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+  - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+  - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+  - !{osquery{"label":"Osquery - Retrieve Process Info","query":"SELECT name, cmdline, parent, path, uid FROM processes"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+
+
+*Related rules*
+
+
+- Network Activity Detected via cat - afd04601-12fc-4149-9b78-9c3f8fe45d39
+
+
+*False positive analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors, such as reverse shells, reverse proxies, or droppers, that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from one of the following integrations:
+- Elastic Defend
+- Auditbeat
+- Filebeat
+- Packetbeat
+
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows
+the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest to select "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+*Auditbeat Setup*
+
+Auditbeat is a lightweight shipper that you can install on your servers to audit the activities of users and processes on your systems. For example, you can use Auditbeat to collect and centralize audit events from the Linux Audit Framework. You can also use Auditbeat to detect changes to critical files, like binaries and configuration files, and identify potential security policy violations.
+
+
+*The following steps should be executed in order to add the Auditbeat on a Linux System:*
+
+- Elastic provides repositories available for APT and YUM-based distributions. Note that we provide binary packages, but no source packages.
+- To install the APT and YUM repositories follow the setup instructions in this https://www.elastic.co/guide/en/beats/auditbeat/current/setup-repositories.html[helper guide].
+- To run Auditbeat on Docker follow the setup instructions in the https://www.elastic.co/guide/en/beats/auditbeat/current/running-on-docker.html[helper guide].
+- To run Auditbeat on Kubernetes follow the setup instructions in the https://www.elastic.co/guide/en/beats/auditbeat/current/running-on-kubernetes.html[helper guide].
+- For complete “Setup and Run Auditbeat” information refer to the https://www.elastic.co/guide/en/beats/auditbeat/current/setting-up-and-running.html[helper guide].
+
+
+*Filebeat Setup*
+
+Filebeat is a lightweight shipper for forwarding and centralizing log data. Installed as an agent on your servers, Filebeat monitors the log files or locations that you specify, collects log events, and forwards them either to Elasticsearch or Logstash for indexing.
+
+
+*The following steps should be executed in order to add the Filebeat on a Linux System:*
+
+- Elastic provides repositories available for APT and YUM-based distributions. Note that we provide binary packages, but no source packages.
+- To install the APT and YUM repositories follow the setup instructions in this https://www.elastic.co/guide/en/beats/filebeat/current/setup-repositories.html[helper guide].
+- To run Filebeat on Docker follow the setup instructions in the https://www.elastic.co/guide/en/beats/filebeat/current/running-on-docker.html[helper guide].
+- To run Filebeat on Kubernetes follow the setup instructions in the https://www.elastic.co/guide/en/beats/filebeat/current/running-on-kubernetes.html[helper guide].
+- For quick start information for Filebeat refer to the https://www.elastic.co/guide/en/beats/filebeat/8.11/filebeat-installation-configuration.html[helper guide].
+- For complete “Setup and Run Filebeat” information refer to the https://www.elastic.co/guide/en/beats/filebeat/current/setting-up-and-running.html[helper guide].
+
+
+*Packetbeat Setup*
+
+Packetbeat is a real-time network packet analyzer that you can use for application monitoring, performance analytics, and threat detection. Packetbeat works by capturing the network traffic between your application servers, decoding the application layer protocols (HTTP, MySQL, Redis, and so on), correlating the requests with the responses, and recording the interesting fields for each transaction.
+
+
+*The following steps should be executed in order to add the Packetbeat on a  Linux System:*
+
+- Elastic provides repositories available for APT and YUM-based distributions. Note that we provide binary packages, but no source packages.
+- To install the APT and YUM repositories follow the setup instructions in this https://www.elastic.co/guide/en/beats/packetbeat/current/setup-repositories.html[helper guide].
+- To run Packetbeat on Docker follow the setup instructions in the https://www.elastic.co/guide/en/beats/packetbeat/current/running-on-docker.html[helper guide].
+- For quick start information for Packetbeat refer to the https://www.elastic.co/guide/en/beats/packetbeat/current/packetbeat-installation-configuration.html[helper guide].
+- For complete “Setup and Run Packetbeat” information refer to the https://www.elastic.co/guide/en/beats/packetbeat/current/setting-up-and-running.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type:linux and event.category:network and event.action:(connection_attempted or ipv4_connection_attempt_event) and 
+process.executable:(
+  (/etc/crontab or /etc/rc.local or ./* or /boot/* or /dev/shm/* or /etc/cron.*/* or /etc/init.d/* or /etc/rc*.d/* or 
+   /etc/update-motd.d/* or /home/*/.* or /run/* or /srv/* or /tmp/* or /usr/lib/update-notifier/* or /var/tmp/* or
+   /var/log/*
+  ) and not (/tmp/newroot/* or /tmp/snap.rootfs*)
+ ) and 
+source.ip:(10.0.0.0/8 or 127.0.0.0/8 or 172.16.0.0/12 or 192.168.0.0/16) and 
+not process.name:(
+ apt or chrome or curl or dnf or dockerd or dpkg or firefox-bin or java or kite-update or kited or node or rpm or
+ saml2aws or wget or yum or ansible* or aws* or php* or pip* or python* or steam* or terraform*
+) and 
+not destination.ip:(
+   10.0.0.0/8 or 100.64.0.0/10 or 127.0.0.0/8 or 169.254.0.0/16 or 172.16.0.0/12 or 192.0.0.0/24 or 192.0.0.0/29 or 
+   192.0.0.10/32 or 192.0.0.170/32 or 192.0.0.171/32 or 192.0.0.8/32 or 192.0.0.9/32 or 192.0.2.0/24 or 
+   192.168.0.0/16 or 192.175.48.0/24 or 192.31.196.0/24 or 192.52.193.0/24 or 192.88.99.0/24 or 198.18.0.0/15 or 
+   198.51.100.0/24 or 203.0.113.0/24 or 224.0.0.0/4 or 240.0.0.0/4 or "::1" or "FE80::/10" or "FF00::/8" or 0.0.0.0
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Application Layer Protocol
+** ID: T1071
+** Reference URL: https://attack.mitre.org/techniques/T1071/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-process-spawned-from-motd-detected.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-process-spawned-from-motd-detected.asciidoc
new file mode 100644
index 0000000000..fd0c5e6d4e
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-process-spawned-from-motd-detected.asciidoc
@@ -0,0 +1,201 @@
+[[prebuilt-rule-8-11-17-suspicious-process-spawned-from-motd-detected]]
+=== Suspicious Process Spawned from MOTD Detected
+
+Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" and "/usr/lib/update-notifier/" directories. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. This rule detects the execution of potentially malicious processes through the MOTD utility.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://pberba.github.io/security/2022/02/06/linux-threat-hunting-for-persistence-initialization-scripts-and-shell-configuration/#10-boot-or-logon-initialization-scripts-motd
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 9
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Suspicious Process Spawned from MOTD Detected*
+
+
+The message-of-the-day (MOTD) is used to display a customizable system-wide message or information to users upon login in Linux.
+
+Attackers can abuse message-of-the-day (motd) files to run scripts, commands or malicious software every time a user connects to a system over SSH or a serial connection, by creating a new file within the `/etc/update-motd.d/` or `/usr/lib/update-notifier/` directory. Files in these directories will automatically run with root privileges when they are made executable.
+
+This rule identifies the execution of potentially malicious processes from a MOTD script, which is not likely to occur as default benign behavior. 
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the file that was created or modified from which the suspicious process was executed.
+  - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
+- Investigate whether any other files in the `/etc/update-motd.d/` or `/usr/lib/update-notifier/` directories have been altered.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE '/usr/lib/update-notifier/%')"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE\n'/usr/lib/update-notifier/%')\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services, and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+
+
+*Related Rules*
+
+
+- Potential Persistence Through MOTD File Creation Detected - 96d11d31-9a79-480f-8401-da28b194608f
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Any activity that triggered the alert and is not inherently malicious must be monitored by the security team.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the MOTD files or restore them to the original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where event.type == "start" and host.os.type == "linux" and event.action : ("exec", "exec_event") and
+  process.parent.executable : ("/etc/update-motd.d/*", "/usr/lib/update-notifier/*") and (
+  (process.name in ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish") and (
+    (process.args : ("-i", "-l")) or (process.parent.name == "socat" and process.parent.args : "*exec*"))) or
+  (process.name : ("nc", "ncat", "netcat", "nc.openbsd") and process.args_count >= 3 and 
+    not process.args : ("-*z*", "-*l*")) or
+  (process.name : "python*" and process.args : "-c" and process.args : (
+     "*import*pty*spawn*", "*import*subprocess*call*"
+  )) or
+  (process.name : "perl*" and process.args : "-e" and process.args : "*socket*" and process.args : (
+     "*exec*", "*system*"
+  )) or
+  (process.name : "ruby*" and process.args : ("-e", "-rsocket") and process.args : (
+     "*TCPSocket.new*", "*TCPSocket.open*"
+  )) or
+  (process.name : "lua*" and process.args : "-e" and process.args : "*socket.tcp*" and process.args : (
+     "*io.popen*", "*os.execute*"
+  )) or
+  (process.name : "php*" and process.args : "-r" and process.args : "*fsockopen*" and process.args : "*/bin/*sh*") or 
+  (process.name : ("awk", "gawk", "mawk", "nawk") and process.args : "*/inet/tcp/*") or 
+  (process.name in ("openssl", "telnet"))
+) and 
+not (
+  (process.parent.args : "--force") or
+  (process.args : ("/usr/games/lolcat", "/usr/bin/screenfetch")) or
+  (process.parent.name == "system-crash-notification")
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Boot or Logon Initialization Scripts
+** ID: T1037
+** Reference URL: https://attack.mitre.org/techniques/T1037/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-screenconnect-client-child-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-screenconnect-client-child-process.asciidoc
new file mode 100644
index 0000000000..90890e600b
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-screenconnect-client-child-process.asciidoc
@@ -0,0 +1,88 @@
+[[prebuilt-rule-8-11-17-suspicious-screenconnect-client-child-process]]
+=== Suspicious ScreenConnect Client Child Process
+
+Identifies suspicious processes being spawned by the ScreenConnect client processes. This activity may indicate execution abusing unauthorized access to the ScreenConnect remote access software.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.process-*
+* winlogbeat-*
+* logs-windows.sysmon_operational-*
+* logs-system.security*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.huntress.com/blog/slashandgrab-screen-connect-post-exploitation-in-the-wild-cve-2024-1709-cve-2024-1708
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Command and Control
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 103
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  process.parent.name :
+                ("ScreenConnect.ClientService.exe",
+                 "ScreenConnect.WindowsClient.exe",
+                 "ScreenConnect.WindowsBackstageShell.exe",
+                 "ScreenConnect.WindowsFileManager.exe") and
+  (
+   (process.name : "powershell.exe" and
+    process.args : ("-enc", "-ec", "-e", "*downloadstring*", "*Reflection.Assembly*", "*http*")) or
+   (process.name : "cmd.exe" and process.args : "/c") or
+   (process.name : "net.exe" and process.args : "/add") or
+   (process.name : "schtasks.exe" and process.args : ("/create", "-create")) or
+   (process.name : "sc.exe" and process.args : "create") or
+   (process.name : "rundll32.exe" and not process.args : "url.dll,FileProtocolHandler") or
+   (process.name : "msiexec.exe" and process.args : ("/i", "-i") and
+    process.args : ("/q", "/quiet", "/qn", "-q", "-quiet", "-qn", "-Q+")) or
+   process.name : ("mshta.exe", "certutil.exe", "bistadmin.exe", "certreq.exe", "wscript.exe", "cscript.exe", "curl.exe",
+                   "ssh.exe", "scp.exe", "wevtutil.exe", "wget.exe", "wmic.exe")
+   )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Command and Control
+** ID: TA0011
+** Reference URL: https://attack.mitre.org/tactics/TA0011/
+* Technique:
+** Name: Remote Access Software
+** ID: T1219
+** Reference URL: https://attack.mitre.org/techniques/T1219/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-service-was-installed-in-the-system.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-service-was-installed-in-the-system.asciidoc
new file mode 100644
index 0000000000..0c6aab4149
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-service-was-installed-in-the-system.asciidoc
@@ -0,0 +1,134 @@
+[[prebuilt-rule-8-11-17-suspicious-service-was-installed-in-the-system]]
+=== Suspicious Service was Installed in the System
+
+Identifies the creation of a new Windows service with suspicious Service command values. Windows services typically run as SYSTEM and can be used for privilege escalation and persistence.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-system.*
+* logs-windows.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Resources: Investigation Guide
+
+*Version*: 9
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Suspicious Service was Installed in the System*
+
+
+Attackers may create new services to execute system shells and other command execution utilities to elevate their privileges from administrator to SYSTEM. They can also configure services to execute these utilities with persistence payloads.
+
+This rule looks for suspicious services being created with suspicious traits compatible with the above behavior.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify how the service was created or modified. Look for registry changes events or Windows events related to service activities (for example, 4697 and/or 7045).
+  - Examine the created and existent services, the executables or drivers referenced, and command line arguments for suspicious entries.
+    - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+    - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+    - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+    - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+    - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+  - Retrieve the referenced files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+
+
+
+*False positive analysis*
+
+
+- Certain services such as PSEXECSVC may happen legitimately. The security team should address any potential benign true positive (B-TP) by excluding the relevant FP by pattern.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+any where
+  (event.code : "4697" and
+   (winlog.event_data.ServiceFileName : 
+           ("*COMSPEC*", "*\\127.0.0.1*", "*Admin$*", "*powershell*", "*rundll32*", "*cmd.exe*", "*PSEXESVC*", 
+            "*echo*", "*RemComSvc*", "*.bat*", "*.cmd*", "*certutil*", "*vssadmin*", "*certmgr*", "*bitsadmin*", 
+            "*\\Users\\*", "*\\Windows\\Temp\\*", "*\\Windows\\Tasks\\*", "*\\PerfLogs\\*", "*\\Windows\\Debug\\*",
+            "*regsvr32*", "*msbuild*") or
+   winlog.event_data.ServiceFileName regex~ """%systemroot%\\[a-z0-9]+\.exe""")) or
+
+  (event.code : "7045" and
+   winlog.event_data.ImagePath : (
+       "*COMSPEC*", "*\\127.0.0.1*", "*Admin$*", "*powershell*", "*rundll32*", "*cmd.exe*", "*PSEXESVC*",
+       "*echo*", "*RemComSvc*", "*.bat*", "*.cmd*", "*certutil*", "*vssadmin*", "*certmgr*", "*bitsadmin*",
+       "*\\Users\\*", "*\\Windows\\Temp\\*", "*\\Windows\\Tasks\\*", "*\\PerfLogs\\*", "*\\Windows\\Debug\\*",
+       "*regsvr32*", "*msbuild*"))
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Windows Service
+** ID: T1543.003
+** Reference URL: https://attack.mitre.org/techniques/T1543/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-web-browser-sensitive-file-access.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-web-browser-sensitive-file-access.asciidoc
new file mode 100644
index 0000000000..50b286caf7
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-web-browser-sensitive-file-access.asciidoc
@@ -0,0 +1,115 @@
+[[prebuilt-rule-8-11-17-suspicious-web-browser-sensitive-file-access]]
+=== Suspicious Web Browser Sensitive File Access
+
+Identifies the access or file open of web browser sensitive files by an untrusted/unsigned process or osascript. Adversaries may acquire credentials from web browsers by reading files specific to the target browser.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.file-*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://securelist.com/calisto-trojan-for-macos/86543/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: macOS
+* Use Case: Threat Detection
+* Tactic: Credential Access
+* Data Source: Elastic Defend
+
+*Version*: 208
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a macOS System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, for MacOS it is recommended to select "Traditional Endpoints".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/current/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where event.action == "open" and host.os.type == "macos" and process.executable != null and
+ file.name : ("cookies.sqlite", 
+              "key?.db", 
+              "logins.json", 
+              "Cookies", 
+              "Cookies.binarycookies", 
+              "Login Data") and 
+ ((process.code_signature.trusted == false or process.code_signature.exists == false) or process.name : "osascript") and 
+ not process.code_signature.signing_id : "org.mozilla.firefox" and
+ not process.Ext.effective_parent.executable : "/Library/Elastic/Endpoint/elastic-endpoint.app/Contents/MacOS/elastic-endpoint"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Credential Access
+** ID: TA0006
+** Reference URL: https://attack.mitre.org/tactics/TA0006/
+* Technique:
+** Name: Steal Web Session Cookie
+** ID: T1539
+** Reference URL: https://attack.mitre.org/techniques/T1539/
+* Technique:
+** Name: Credentials from Password Stores
+** ID: T1555
+** Reference URL: https://attack.mitre.org/techniques/T1555/
+* Sub-technique:
+** Name: Credentials from Web Browsers
+** ID: T1555.003
+** Reference URL: https://attack.mitre.org/techniques/T1555/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-werfault-child-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-werfault-child-process.asciidoc
new file mode 100644
index 0000000000..bad912bf9e
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-werfault-child-process.asciidoc
@@ -0,0 +1,117 @@
+[[prebuilt-rule-8-11-17-suspicious-werfault-child-process]]
+=== Suspicious WerFault Child Process
+
+A suspicious WerFault child process was detected, which may indicate an attempt to run via the SilentProcessExit registry key manipulation. Verify process details such as command line, network connections and file writes.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.hexacorn.com/blog/2019/09/19/silentprocessexit-quick-look-under-the-hood/
+* https://www.hexacorn.com/blog/2019/09/20/werfault-command-line-switches-v0-1/
+* https://github.com/sbousseaden/EVTX-ATTACK-SAMPLES/blob/master/Persistence/persistence_SilentProcessExit_ImageHijack_sysmon_13_1.evtx
+* http://web.archive.org/web/20230530011556/https://blog.menasec.net/2021/01/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Tactic: Persistence
+* Tactic: Privilege Escalation
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: SentinelOne
+
+*Version*: 214
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+
+  process.parent.name : "WerFault.exe" and
+
+  /* args -s and -t used to execute a process via SilentProcessExit mechanism */
+  (process.parent.args : "-s" and process.parent.args : "-t" and process.parent.args : "-c") and
+
+  not process.executable : ("?:\\Windows\\SysWOW64\\Initcrypt.exe", "?:\\Program Files (x86)\\Heimdal\\Heimdal.Guard.exe")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Event Triggered Execution
+** ID: T1546
+** Reference URL: https://attack.mitre.org/techniques/T1546/
+* Sub-technique:
+** Name: Image File Execution Options Injection
+** ID: T1546.012
+** Reference URL: https://attack.mitre.org/techniques/T1546/012/
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Event Triggered Execution
+** ID: T1546
+** Reference URL: https://attack.mitre.org/techniques/T1546/
+* Sub-technique:
+** Name: Image File Execution Options Injection
+** ID: T1546.012
+** Reference URL: https://attack.mitre.org/techniques/T1546/012/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-which-enumeration.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-which-enumeration.asciidoc
new file mode 100644
index 0000000000..03029c4cc2
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-which-enumeration.asciidoc
@@ -0,0 +1,68 @@
+[[prebuilt-rule-8-11-17-suspicious-which-enumeration]]
+=== Suspicious which Enumeration
+
+This rule monitors for the usage of the which command with an unusual amount of process arguments. Attackers may leverage the which command to enumerate the system for useful installed utilities that may be used after compromising a system to escalate privileges or move latteraly across the network.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+* endgame-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Discovery
+* Data Source: Elastic Defend
+* Data Source: Elastic Endgame
+
+*Version*: 6
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "linux" and event.type == "start" and event.action in ("exec", "exec_event") and 
+process.name == "which" and process.args_count >= 10 and not process.parent.name == "jem" and 
+not process.args == "--tty-only"
+
+/* potential tuning if rule would turn out to be noisy
+and process.args in ("nmap", "nc", "ncat", "netcat", nc.traditional", "gcc", "g++", "socat") and 
+process.parent.name in ("bash", "dash", "ash", "sh", "tcsh", "csh", "zsh", "ksh", "fish")
+*/
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Discovery
+** ID: TA0007
+** Reference URL: https://attack.mitre.org/tactics/TA0007/
+* Technique:
+** Name: System Information Discovery
+** ID: T1082
+** Reference URL: https://attack.mitre.org/techniques/T1082/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-host.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-host.asciidoc
new file mode 100644
index 0000000000..2daf3a7af7
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-host.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-host]]
+=== Suspicious Windows Process Cluster Spawned by a Host
+
+A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same host name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-45m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/problemchild
+* https://www.elastic.co/security-labs/detecting-living-off-the-land-attacks-with-new-elastic-integration
+
+*Tags*: 
+
+* Use Case: Living off the Land Attack Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Defense Evasion
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Living off the Land (LotL) Attack Detection integration assets to be installed, as well as Windows process events collected by integrations such as Elastic Defend or Winlogbeat.  
+
+
+*LotL Attack Detection Setup*
+
+The LotL Attack Detection integration detects living-off-the-land activity in Windows process events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for LotL Attack Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration or Winlogbeat(https://www.elastic.co/guide/en/beats/winlogbeat/current/_winlogbeat_overview.html).
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To set up and run Winlogbeat, follow https://www.elastic.co/guide/en/beats/winlogbeat/current/winlogbeat-installation-configuration.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the LotL Attack Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-parent-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-parent-process.asciidoc
new file mode 100644
index 0000000000..6772420f46
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-parent-process.asciidoc
@@ -0,0 +1,85 @@
+[[prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-parent-process]]
+=== Suspicious Windows Process Cluster Spawned by a Parent Process
+
+A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same parent process name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-45m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/problemchild
+* https://www.elastic.co/security-labs/detecting-living-off-the-land-attacks-with-new-elastic-integration
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Living off the Land Attack Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Defense Evasion
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Living off the Land (LotL) Attack Detection integration assets to be installed, as well as Windows process events collected by integrations such as Elastic Defend or Winlogbeat.  
+
+
+*LotL Attack Detection Setup*
+
+The LotL Attack Detection integration detects living-off-the-land activity in Windows process events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for LotL Attack Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration or Winlogbeat(https://www.elastic.co/guide/en/beats/winlogbeat/current/_winlogbeat_overview.html).
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To set up and run Winlogbeat, follow https://www.elastic.co/guide/en/beats/winlogbeat/current/winlogbeat-installation-configuration.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the LotL Attack Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-user.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-user.asciidoc
new file mode 100644
index 0000000000..5cff38a1c5
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-user.asciidoc
@@ -0,0 +1,85 @@
+[[prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-user]]
+=== Suspicious Windows Process Cluster Spawned by a User
+
+A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same user name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-45m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/problemchild
+* https://www.elastic.co/security-labs/detecting-living-off-the-land-attacks-with-new-elastic-integration
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Living off the Land Attack Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Defense Evasion
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Living off the Land (LotL) Attack Detection integration assets to be installed, as well as Windows process events collected by integrations such as Elastic Defend or Winlogbeat.  
+
+
+*LotL Attack Detection Setup*
+
+The LotL Attack Detection integration detects living-off-the-land activity in Windows process events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for LotL Attack Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration or Winlogbeat(https://www.elastic.co/guide/en/beats/winlogbeat/current/_winlogbeat_overview.html).
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To set up and run Winlogbeat, follow https://www.elastic.co/guide/en/beats/winlogbeat/current/winlogbeat-installation-configuration.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the LotL Attack Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-zoom-child-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-zoom-child-process.asciidoc
new file mode 100644
index 0000000000..7dee6e8757
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-suspicious-zoom-child-process.asciidoc
@@ -0,0 +1,146 @@
+[[prebuilt-rule-8-11-17-suspicious-zoom-child-process]]
+=== Suspicious Zoom Child Process
+
+A suspicious Zoom child process was detected, which may indicate an attempt to run unnoticed. Verify process details such as command line, network connections, file writes and associated file signature details as well.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Tactic: Execution
+* Data Source: Elastic Endgame
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+* Data Source: SentinelOne
+
+*Version*: 212
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Suspicious Zoom Child Process*
+
+
+By examining the specific traits of Windows binaries -- such as process trees, command lines, network connections, registry modifications, and so on -- it's possible to establish a baseline of normal activity. Deviations from this baseline can indicate malicious activity, such as masquerading, and deserve further investigation.
+
+This rule identifies a potential malicious process masquerading as `Zoom.exe` or exploiting a vulnerability in the application causing it to execute code.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Investigate any abnormal behavior by the subject process such as network connections, registry or file modifications, and any spawned child processes.
+- Examine the command line of the child process to determine which commands or scripts were executed.
+- Examine the host for derived artifacts that indicate suspicious activities:
+  - Analyze the process executable using a private sandboxed analysis system.
+  - Observe and collect information about the following activities in both the sandbox and the alert subject host:
+    - Attempts to contact external domains and addresses.
+      - Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' `process.entity_id`.
+      - Examine the DNS cache for suspicious or anomalous entries.
+        - !{osquery{"label":"Osquery - Retrieve DNS Cache","query":"SELECT * FROM dns_cache"}}
+    - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
+    - Examine the host services for suspicious or anomalous entries.
+      - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+      - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+  - Retrieve the files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+ process.parent.name : "Zoom.exe" and process.name : ("cmd.exe", "powershell.exe", "pwsh.exe", "powershell_ise.exe")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Technique:
+** Name: Process Injection
+** ID: T1055
+** Reference URL: https://attack.mitre.org/techniques/T1055/
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Exploitation for Client Execution
+** ID: T1203
+** Reference URL: https://attack.mitre.org/techniques/T1203/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-system-binary-copied-and-or-moved-to-suspicious-directory.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-system-binary-copied-and-or-moved-to-suspicious-directory.asciidoc
new file mode 100644
index 0000000000..d7ff81ad49
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-system-binary-copied-and-or-moved-to-suspicious-directory.asciidoc
@@ -0,0 +1,130 @@
+[[prebuilt-rule-8-11-17-system-binary-copied-and-or-moved-to-suspicious-directory]]
+=== System Binary Copied and/or Moved to Suspicious Directory
+
+This rule monitors for the copying or moving of a system binary to a suspicious directory. Adversaries may copy/move and rename system binaries to evade detection. Copying a system binary to a different location should not occur often, so if it does, the activity should be investigated.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Data Source: Elastic Defend
+
+*Version*: 8
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by host.id, process.entity_id with maxspan=1s
+  [process where host.os.type == "linux" and event.type == "start" and event.action == "exec" and 
+   process.name in ("cp", "mv") and process.args : (
+   // Shells
+   "/bin/*sh", "/usr/bin/*sh", 
+
+   // Interpreters
+   "/bin/python*", "/usr/bin/python*", "/bin/php*", "/usr/bin/php*", "/bin/ruby*", "/usr/bin/ruby*", "/bin/perl*",
+   "/usr/bin/perl*", "/bin/lua*", "/usr/bin/lua*", "/bin/java*", "/usr/bin/java*", 
+
+   // Compilers
+   "/bin/gcc*", "/usr/bin/gcc*", "/bin/g++*", "/usr/bin/g++*", "/bin/cc", "/usr/bin/cc",
+
+   // Suspicious utilities
+   "/bin/nc", "/usr/bin/nc", "/bin/ncat", "/usr/bin/ncat", "/bin/netcat", "/usr/bin/netcat", "/bin/nc.openbsd",
+   "/usr/bin/nc.openbsd", "/bin/*awk", "/usr/bin/*awk", "/bin/socat", "/usr/bin/socat", "/bin/openssl",
+   "/usr/bin/openssl", "/bin/telnet", "/usr/bin/telnet", "/bin/mkfifo", "/usr/bin/mkfifo", "/bin/mknod",
+   "/usr/bin/mknod", "/bin/ping*", "/usr/bin/ping*", "/bin/nmap", "/usr/bin/nmap",
+
+   // System utilities
+   "/bin/ls", "/usr/bin/ls", "/bin/cat", "/usr/bin/cat", "/bin/sudo", "/usr/bin/sudo", "/bin/curl", "/usr/bin/curl",
+   "/bin/wget", "/usr/bin/wget", "/bin/tmux", "/usr/bin/tmux", "/bin/screen", "/usr/bin/screen", "/bin/ssh",
+   "/usr/bin/ssh", "/bin/ftp", "/usr/bin/ftp"
+  ) and not process.parent.name in ("dracut-install", "apticron", "generate-from-dir", "platform-python")]
+  [file where host.os.type == "linux" and event.action == "creation" and file.path : (
+    "/dev/shm/*", "/run/shm/*", "/tmp/*", "/var/tmp/*", "/run/*", "/var/run/*", "/var/www/*", "/proc/*/fd/*"
+  ) and not file.path : ("/tmp/rear*", "/var/tmp/rear*", "/var/tmp/dracut*", "/var/tmp/mkinitramfs*")]
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Sub-technique:
+** Name: Rename System Utilities
+** ID: T1036.003
+** Reference URL: https://attack.mitre.org/techniques/T1036/003/
+* Technique:
+** Name: Hide Artifacts
+** ID: T1564
+** Reference URL: https://attack.mitre.org/techniques/T1564/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-system-shells-via-services.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-system-shells-via-services.asciidoc
new file mode 100644
index 0000000000..a3f473236e
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-system-shells-via-services.asciidoc
@@ -0,0 +1,147 @@
+[[prebuilt-rule-8-11-17-system-shells-via-services]]
+=== System Shells via Services
+
+Windows services typically run as SYSTEM and can be used as a privilege escalation opportunity. Malware or penetration testers may run a shell as a service to gain SYSTEM permissions.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Execution
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: SentinelOne
+
+*Version*: 212
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating System Shells via Services*
+
+
+Attackers may configure existing services or create new ones to execute system shells to elevate their privileges from administrator to SYSTEM. They can also configure services to execute these shells with persistence payloads.
+
+This rule looks for system shells being spawned by `services.exe`, which is compatible with the above behavior.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify how the service was created or modified. Look for registry changes events or Windows events related to service activities (for example, 4697 and/or 7045).
+  - Examine the created and existent services, the executables or drivers referenced, and command line arguments for suspicious entries.
+    - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+    - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+    - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+  - Retrieve the referenced files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+- Check for commands executed under the spawned shell.
+
+
+*False positive analysis*
+
+
+- This activity should not happen legitimately. The security team should address any potential benign true positive (B-TP), as this configuration can put the user and the domain at risk.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service or restore it to the original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  process.parent.name : "services.exe" and
+  process.name : ("cmd.exe", "powershell.exe", "pwsh.exe", "powershell_ise.exe") and
+
+  /* Third party FP's */
+  not process.args : "NVDisplay.ContainerLocalSystem"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Windows Service
+** ID: T1543.003
+** Reference URL: https://attack.mitre.org/techniques/T1543/003/
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
+* Sub-technique:
+** Name: PowerShell
+** ID: T1059.001
+** Reference URL: https://attack.mitre.org/techniques/T1059/001/
+* Sub-technique:
+** Name: Windows Command Shell
+** ID: T1059.003
+** Reference URL: https://attack.mitre.org/techniques/T1059/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-systemd-service-started-by-unusual-parent-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-systemd-service-started-by-unusual-parent-process.asciidoc
new file mode 100644
index 0000000000..81056c82ef
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-systemd-service-started-by-unusual-parent-process.asciidoc
@@ -0,0 +1,217 @@
+[[prebuilt-rule-8-11-17-systemd-service-started-by-unusual-parent-process]]
+=== Systemd Service Started by Unusual Parent Process
+
+Systemctl is a process used in Linux systems to manage systemd processes through service configuration files. Malicious actors can leverage systemd services to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/springtail-kimsuky-backdoor-espionage
+* https://pberba.github.io/security/2022/01/30/linux-threat-hunting-for-persistence-systemd-timers-cron/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Privilege Escalation
+* Data Source: Elastic Defend
+
+*Version*: 1
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Systemd Service Started by Unusual Parent Process*
+
+
+Systemd service files are configuration files in Linux systems used to define and manage systemd services.
+
+Malicious actors can leverage systemd service files to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection.
+
+This rule monitors the execution of the systemctl binary to start, enable or reenable a systemd service, potentially indicating the creation of a persistence mechanism.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the currently enabled systemd services through the following command `sudo systemctl list-unit-files`.
+- Investigate whether any other files in any of the available systemd directories have been altered through OSQuery.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (\npath LIKE '/etc/systemd/system/%' OR \npath LIKE '/usr/local/lib/systemd/system/%' OR \npath LIKE '/lib/systemd/system/%' OR\npath LIKE '/usr/lib/systemd/system/%' OR\npath LIKE '/home/user/.config/systemd/user/%'\n)\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (\npath LIKE '/etc/systemd/system/%' OR \npath LIKE '/usr/local/lib/systemd/system/%' OR \npath LIKE '/lib/systemd/system/%' OR\npath LIKE '/usr/lib/systemd/system/%' OR\npath LIKE '/home/{{user.name}}/.config/systemd/user/%'\n)\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator who uses systemd services for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- New Systemd Service Created by Previously Unknown Process - 17b0a495-4d9f-414c-8ad0-92f018b8e001
+- Potential Persistence Through Run Control Detected - 0f4d35e4-925e-4959-ab24-911be207ee6f
+- Potential Persistence Through init.d Detected - 474fd20e-14cc-49c5-8160-d9ab4ba16c8b
+- New Systemd Timer Created - 7fb500fa-8e24-4bd1-9480-2a819352602c
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service/timer or restore its original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type:linux and event.category:process and event.type:start and event.action:exec and
+process.executable:/usr/bin/systemctl and process.args:(enable or reenable or start) and 
+process.entry_leader.entry_meta.type:* and
+not (
+  process.entry_leader.entry_meta.type:(container or init or unknown) or
+  process.parent.pid:1 or
+  process.parent.executable:(
+    /bin/adduser or /bin/dnf or /bin/dnf-automatic or /bin/dockerd or /bin/dpkg or /bin/microdnf or /bin/pacman or
+    /bin/podman or /bin/rpm or /bin/snapd or /bin/sudo or /bin/useradd or /bin/yum or /usr/bin/dnf or
+    /usr/bin/dnf-automatic or /usr/bin/dockerd or /usr/bin/dpkg or /usr/bin/microdnf or /usr/bin/pacman or
+    /usr/bin/podman or /usr/bin/rpm or /usr/bin/snapd or /usr/bin/sudo or /usr/bin/yum or /usr/sbin/adduser or
+    /usr/sbin/invoke-rc.d or /usr/sbin/useradd or /var/lib/dpkg/*
+  ) or
+  process.args_count >= 5
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Systemd Service
+** ID: T1543.002
+** Reference URL: https://attack.mitre.org/techniques/T1543/002/
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Systemd Service
+** ID: T1543.002
+** Reference URL: https://attack.mitre.org/techniques/T1543/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-third-party-backup-files-deleted-via-unexpected-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-third-party-backup-files-deleted-via-unexpected-process.asciidoc
new file mode 100644
index 0000000000..65a3a81ecb
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-third-party-backup-files-deleted-via-unexpected-process.asciidoc
@@ -0,0 +1,164 @@
+[[prebuilt-rule-8-11-17-third-party-backup-files-deleted-via-unexpected-process]]
+=== Third-party Backup Files Deleted via Unexpected Process
+
+Identifies the deletion of backup files, saved using third-party software, by a process outside of the backup suite. Adversaries may delete Backup files to ensure that recovery from a ransomware attack is less likely.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.file-*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.advintel.io/post/backup-removal-solutions-from-conti-ransomware-with-love
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Impact
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 113
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Third-party Backup Files Deleted via Unexpected Process*
+
+
+Backups are a significant obstacle for any ransomware operation. They allow the victim to resume business by performing data recovery, making them a valuable target.
+
+Attackers can delete backups from the host and gain access to backup servers to remove centralized backups for the environment, ensuring that victims have no alternatives to paying the ransom.
+
+This rule identifies file deletions performed by a process that does not belong to the backup suite and aims to delete Veritas or Veeam backups.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Check if any files on the host machine have been encrypted.
+
+
+*False positive analysis*
+
+
+- This rule can be triggered by the manual removal of backup files and by removal using other third-party tools that are not from the backup suite. Exceptions can be added for specific accounts and executables, preferably tied together.
+
+
+*Related rules*
+
+
+- Deleting Backup Catalogs with Wbadmin - 581add16-df76-42bb-af8e-c979bfb39a59
+- Volume Shadow Copy Deleted or Resized via VssAdmin - b5ea4bfe-a1b2-421f-9d47-22a75a6f2921
+- Volume Shadow Copy Deletion via PowerShell - d99a037b-c8e2-47a5-97b9-170d076827c4
+- Volume Shadow Copy Deletion via WMIC - dc9c1f74-dac3-48e3-b47f-eb79db358f57
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Consider isolating the involved host to prevent destructive behavior, which is commonly associated with this activity.
+- Perform data recovery locally or restore the backups from replicated copies (Cloud, other servers, etc.).
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+file where host.os.type == "windows" and event.type == "deletion" and
+  (
+    /* Veeam Related Backup Files */
+    (
+      file.extension : ("VBK", "VIB", "VBM") and
+      not (
+        process.executable : ("?:\\Windows\\*", "?:\\Program Files\\*", "?:\\Program Files (x86)\\*") and
+        (process.code_signature.trusted == true and process.code_signature.subject_name : ("Veeam Software Group GmbH", "Veeam Software AG"))
+      )
+    ) or
+    /* Veritas Backup Exec Related Backup File */
+    (
+      file.extension : "BKF" and
+        not process.executable : (
+          "?:\\Program Files\\Veritas\\Backup Exec\\*",
+          "?:\\Program Files (x86)\\Veritas\\Backup Exec\\*"
+        )
+    )
+  ) and
+  not (
+    process.name : ("MSExchangeMailboxAssistants.exe", "Microsoft.PowerBI.EnterpriseGateway.exe") and
+      (process.code_signature.subject_name : "Microsoft Corporation" and process.code_signature.trusted == true)
+  ) and
+  not file.path : (
+    "?:\\ProgramData\\Trend Micro\\*",
+    "?:\\Program Files (x86)\\Trend Micro\\*",
+    "?:\\$RECYCLE.BIN\\*"
+  )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Impact
+** ID: TA0040
+** Reference URL: https://attack.mitre.org/tactics/TA0040/
+* Technique:
+** Name: Data Destruction
+** ID: T1485
+** Reference URL: https://attack.mitre.org/techniques/T1485/
+* Technique:
+** Name: Inhibit System Recovery
+** ID: T1490
+** Reference URL: https://attack.mitre.org/techniques/T1490/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uac-bypass-attempt-via-windows-directory-masquerading.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uac-bypass-attempt-via-windows-directory-masquerading.asciidoc
new file mode 100644
index 0000000000..8fc2b72133
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uac-bypass-attempt-via-windows-directory-masquerading.asciidoc
@@ -0,0 +1,174 @@
+[[prebuilt-rule-8-11-17-uac-bypass-attempt-via-windows-directory-masquerading]]
+=== UAC Bypass Attempt via Windows Directory Masquerading
+
+Identifies an attempt to bypass User Account Control (UAC) by masquerading as a Microsoft trusted Windows directory. Attackers may bypass UAC to stealthily execute code with elevated permissions.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://medium.com/tenable-techblog/uac-bypass-by-mocking-trusted-directories-24a96675f6e
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Privilege Escalation
+* Tactic: Defense Evasion
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+
+*Version*: 113
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating UAC Bypass Attempt via Windows Directory Masquerading*
+
+
+Windows User Account Control (UAC) allows a program to elevate its privileges (tracked as low to high integrity levels) to perform a task under administrator-level permissions, possibly by prompting the user for confirmation. UAC can deny an operation under high-integrity enforcement, or allow the user to perform the action if they are in the local administrators group and enter an administrator password when prompted.
+
+For more information about the UAC and how it works, check the https://docs.microsoft.com/en-us/windows/security/identity-protection/user-account-control/how-user-account-control-works[official Microsoft docs page].
+
+This rule identifies an attempt to bypass User Account Control (UAC) by masquerading as a Microsoft trusted Windows directory. Attackers may bypass UAC to stealthily execute code with elevated permissions.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Inspect the host for suspicious or abnormal behavior in the alert timeframe.
+- Investigate any abnormal behavior by the subject process such as network connections, registry or file modifications, and any spawned child processes.
+- Examine the host for derived artifacts that indicate suspicious activities:
+  - Analyze any suspicious spawned processes using a private sandboxed analysis system.
+  - Observe and collect information about the following activities in both the sandbox and the alert subject host:
+    - Attempts to contact external domains and addresses.
+      - Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' `process.entity_id`.
+      - Examine the DNS cache for suspicious or anomalous entries.
+        - !{osquery{"label":"Osquery - Retrieve DNS Cache","query":"SELECT * FROM dns_cache"}}
+    - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
+    - Examine the host services for suspicious or anomalous entries.
+      - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+      - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+  - Retrieve the files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Investigate potentially compromised accounts. Analysts can do this by searching for login events (for example, 4624) to the target host after the registry modification.
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  process.args : ("C:\\Windows \\system32\\*.exe", "C:\\Windows \\SysWOW64\\*.exe")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Bypass User Account Control
+** ID: T1548.002
+** Reference URL: https://attack.mitre.org/techniques/T1548/002/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Sub-technique:
+** Name: Match Legitimate Name or Location
+** ID: T1036.005
+** Reference URL: https://attack.mitre.org/techniques/T1036/005/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Bypass User Account Control
+** ID: T1548.002
+** Reference URL: https://attack.mitre.org/techniques/T1548/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uac-bypass-via-windows-firewall-snap-in-hijack.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uac-bypass-via-windows-firewall-snap-in-hijack.asciidoc
new file mode 100644
index 0000000000..8146a619f6
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uac-bypass-via-windows-firewall-snap-in-hijack.asciidoc
@@ -0,0 +1,177 @@
+[[prebuilt-rule-8-11-17-uac-bypass-via-windows-firewall-snap-in-hijack]]
+=== UAC Bypass via Windows Firewall Snap-In Hijack
+
+Identifies attempts to bypass User Account Control (UAC) by hijacking the Microsoft Management Console (MMC) Windows Firewall snap-in. Attackers bypass UAC to stealthily execute code with elevated permissions.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://github.com/AzAgarampur/byeintegrity-uac
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Privilege Escalation
+* Tactic: Defense Evasion
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating UAC Bypass via Windows Firewall Snap-In Hijack*
+
+
+Windows User Account Control (UAC) allows a program to elevate its privileges (tracked as low to high integrity levels) to perform a task under administrator-level permissions, possibly by prompting the user for confirmation. UAC can deny an operation under high-integrity enforcement, or allow the user to perform the action if they are in the local administrators group and enter an administrator password when prompted.
+
+For more information about the UAC and how it works, check the https://docs.microsoft.com/en-us/windows/security/identity-protection/user-account-control/how-user-account-control-works[official Microsoft docs page].
+
+This rule identifies attempts to bypass User Account Control (UAC) by hijacking the Microsoft Management Console (MMC) Windows Firewall snap-in. Attackers bypass UAC to stealthily execute code with elevated permissions.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Inspect the host for suspicious or abnormal behavior in the alert timeframe.
+- Investigate any abnormal behavior by the subject process such as network connections, registry or file modifications, and any spawned child processes.
+- Examine the host for derived artifacts that indicate suspicious activities:
+  - Analyze any suspicious spawned processes using a private sandboxed analysis system.
+  - Observe and collect information about the following activities in both the sandbox and the alert subject host:
+    - Attempts to contact external domains and addresses.
+      - Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' `process.entity_id`.
+      - Examine the DNS cache for suspicious or anomalous entries.
+        - !{osquery{"label":"Osquery - Retrieve DNS Cache","query":"SELECT * FROM dns_cache"}}
+    - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
+    - Examine the host services for suspicious or anomalous entries.
+      - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+      - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+  - Retrieve the files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Investigate potentially compromised accounts. Analysts can do this by searching for login events (for example, 4624) to the target host after the registry modification.
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Benign true positives (B-TPs) can be added as exceptions if necessary.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+ process.parent.name == "mmc.exe" and
+ /* process.Ext.token.integrity_level_name == "high" can be added in future for tuning */
+ /* args of the Windows Firewall SnapIn */
+  process.parent.args == "WF.msc" and process.name != "WerFault.exe"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Bypass User Account Control
+** ID: T1548.002
+** Reference URL: https://attack.mitre.org/techniques/T1548/002/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: System Binary Proxy Execution
+** ID: T1218
+** Reference URL: https://attack.mitre.org/techniques/T1218/
+* Sub-technique:
+** Name: MMC
+** ID: T1218.014
+** Reference URL: https://attack.mitre.org/techniques/T1218/014/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Bypass User Account Control
+** ID: T1548.002
+** Reference URL: https://attack.mitre.org/techniques/T1548/002/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uncommon-registry-persistence-change.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uncommon-registry-persistence-change.asciidoc
new file mode 100644
index 0000000000..ecfb42db5d
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-uncommon-registry-persistence-change.asciidoc
@@ -0,0 +1,142 @@
+[[prebuilt-rule-8-11-17-uncommon-registry-persistence-change]]
+=== Uncommon Registry Persistence Change
+
+Detects changes to registry persistence keys that are not commonly used or modified by legitimate programs. This could be an indication of an adversary's attempt to persist in a stealthy manner.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.registry-*
+* logs-windows.sysmon_operational-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.microsoftpressstore.com/articles/article.aspx?p=2762082&seqNum=2
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 108
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and event.type in ("creation", "change") and
+ length(registry.data.strings) > 0 and
+ registry.path : (
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Terminal Server\\Install\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Run\\*",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Terminal Server\\Install\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Runonce\\*",
+      "HKEY_USERS\\*\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Windows\\Load",
+      "HKEY_USERS\\*\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Windows\\Run",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Windows\\IconServiceLib",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Winlogon\\Shell",
+      "HKEY_USERS\\*\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Winlogon\\Shell",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Winlogon\\AppSetup",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Winlogon\\Taskman",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Winlogon\\Userinit",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Winlogon\\VmApplet",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\Explorer\\Run\\*",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\Shell",
+      "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows\\System\\Scripts\\Logoff\\Script",
+      "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows\\System\\Scripts\\Logon\\Script",
+      "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows\\System\\Scripts\\Shutdown\\Script",
+      "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows\\System\\Scripts\\Startup\\Script",
+      "HKEY_USERS\\*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\Explorer\\Run\\*",
+      "HKEY_USERS\\*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\Shell",
+      "HKEY_USERS\\*\\SOFTWARE\\Policies\\Microsoft\\Windows\\System\\Scripts\\Logoff\\Script",
+      "HKEY_USERS\\*\\SOFTWARE\\Policies\\Microsoft\\Windows\\System\\Scripts\\Logon\\Script",
+      "HKEY_USERS\\*\\SOFTWARE\\Policies\\Microsoft\\Windows\\System\\Scripts\\Shutdown\\Script",
+      "HKEY_USERS\\*\\SOFTWARE\\Policies\\Microsoft\\Windows\\System\\Scripts\\Startup\\Script",
+      "HKLM\\SOFTWARE\\Microsoft\\Active Setup\\Installed Components\\*\\ShellComponent",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows CE Services\\AutoStartOnConnect\\MicrosoftActiveSync",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows CE Services\\AutoStartOnDisconnect\\MicrosoftActiveSync",
+      "HKLM\\SOFTWARE\\Microsoft\\Ctf\\LangBarAddin\\*\\FilePath",
+      "HKLM\\SOFTWARE\\Microsoft\\Internet Explorer\\Extensions\\*\\Exec",
+      "HKLM\\SOFTWARE\\Microsoft\\Internet Explorer\\Extensions\\*\\Script",
+      "HKLM\\SOFTWARE\\Microsoft\\Command Processor\\Autorun",
+      "HKEY_USERS\\*\\SOFTWARE\\Microsoft\\Ctf\\LangBarAddin\\*\\FilePath",
+      "HKEY_USERS\\*\\SOFTWARE\\Microsoft\\Internet Explorer\\Extensions\\*\\Exec",
+      "HKEY_USERS\\*\\SOFTWARE\\Microsoft\\Internet Explorer\\Extensions\\*\\Script",
+      "HKEY_USERS\\*\\SOFTWARE\\Microsoft\\Command Processor\\Autorun",
+      "HKEY_USERS\\*\\Control Panel\\Desktop\\scrnsave.exe",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options\\*\\VerifierDlls",
+      "HKLM\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\Winlogon\\GpExtensions\\*\\DllName",
+      "HKLM\\SYSTEM\\ControlSet*\\Control\\SafeBoot\\AlternateShell",
+      "HKLM\\SYSTEM\\ControlSet*\\Control\\Terminal Server\\Wds\\rdpwd\\StartupPrograms",
+      "HKLM\\SYSTEM\\ControlSet*\\Control\\Terminal Server\\WinStations\\RDP-Tcp\\InitialProgram",
+      "HKLM\\SYSTEM\\ControlSet*\\Control\\Session Manager\\BootExecute",
+      "HKLM\\SYSTEM\\ControlSet*\\Control\\Session Manager\\SetupExecute",
+      "HKLM\\SYSTEM\\ControlSet*\\Control\\Session Manager\\Execute",
+      "HKLM\\SYSTEM\\ControlSet*\\Control\\Session Manager\\S0InitialCommand",
+      "HKLM\\SYSTEM\\ControlSet*\\Control\\ServiceControlManagerExtension",
+      "HKLM\\SYSTEM\\ControlSet*\\Control\\BootVerificationProgram\\ImagePath",
+      "HKLM\\SYSTEM\\Setup\\CmdLine",
+      "HKEY_USERS\\*\\Environment\\UserInitMprLogonScript") and
+
+ not registry.data.strings : ("C:\\Windows\\system32\\userinit.exe", "cmd.exe", "C:\\Program Files (x86)\\*.exe",
+                              "C:\\Program Files\\*.exe") and
+ not (process.name : "rundll32.exe" and registry.path : "*\\Software\\Microsoft\\Internet Explorer\\Extensions\\*\\Script") and
+ not process.executable : ("C:\\Windows\\System32\\msiexec.exe",
+                           "C:\\Windows\\SysWOW64\\msiexec.exe",
+                           "C:\\ProgramData\\Microsoft\\Windows Defender\\Platform\\*\\MsMpEng.exe",
+                           "C:\\Program Files\\*.exe",
+                           "C:\\Program Files (x86)\\*.exe")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Event Triggered Execution
+** ID: T1546
+** Reference URL: https://attack.mitre.org/techniques/T1546/
+* Sub-technique:
+** Name: Screensaver
+** ID: T1546.002
+** Reference URL: https://attack.mitre.org/techniques/T1546/002/
+* Technique:
+** Name: Boot or Logon Autostart Execution
+** ID: T1547
+** Reference URL: https://attack.mitre.org/techniques/T1547/
+* Sub-technique:
+** Name: Registry Run Keys / Startup Folder
+** ID: T1547.001
+** Reference URL: https://attack.mitre.org/techniques/T1547/001/
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-untrusted-driver-loaded.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-untrusted-driver-loaded.asciidoc
new file mode 100644
index 0000000000..986ad87737
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-untrusted-driver-loaded.asciidoc
@@ -0,0 +1,144 @@
+[[prebuilt-rule-8-11-17-untrusted-driver-loaded]]
+=== Untrusted Driver Loaded
+
+Identifies attempt to load an untrusted driver. Adversaries may modify code signing policies to enable execution of unsigned or self-signed code.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.library-*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://github.com/hfiref0x/TDL
+* https://docs.microsoft.com/en-us/previous-versions/windows/hardware/design/dn653559(v=vs.85)?redirectedfrom=MSDN
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+
+*Version*: 9
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Untrusted Driver Loaded*
+
+
+Microsoft created the Windows Driver Signature Enforcement (DSE) security feature to prevent drivers with invalid signatures from loading and executing into the kernel (ring 0). DSE aims to protect systems by blocking attackers from loading malicious drivers on targets. 
+
+This protection is essential for maintaining system security. However, attackers or administrators can disable DSE and load untrusted drivers, which can put the system at risk. Therefore, it's important to keep this feature enabled and only load drivers from trusted sources to ensure system integrity and security.
+
+This rule identifies an attempt to load an untrusted driver, which effectively means that DSE was disabled or bypassed. This can indicate that the system was compromised.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Examine the driver loaded to identify potentially suspicious characteristics. The following actions can help you gain context:
+  - Identify the path that the driver was loaded from. If you're using Elastic Defend, path information can be found in the `dll.path` field.
+  - Examine the file creation and modification timestamps:
+    - On Elastic Defend, those can be found in the `dll.Ext.relative_file_creation_time` and `dll.Ext.relative_file_name_modify_time` fields. The values are in seconds.
+    - Search for file creation events sharing the same file name as the `dll.name` field and identify the process responsible for the operation.
+      - Investigate any other abnormal behavior by the subject process, such as network connections, registry or file modifications, and any spawned child processes.
+  - Use the driver SHA-256 (`dll.hash.sha256` field) hash value to search for the existence and reputation in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+- Use Osquery to investigate the drivers loaded into the system.
+  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+- Identify the driver's `Device Name` and `Service Name`.
+- Check for alerts from the rules specified in the `Related Rules` section.
+
+
+*False positive analysis*
+
+
+- This activity should not happen legitimately. The security team should address any potential benign true positive (B-TP), as this configuration can put the user and the domain at risk.
+
+
+*Related Rules*
+
+
+- First Time Seen Driver Loaded - df0fd41e-5590-4965-ad5e-cd079ec22fa9
+- Code Signing Policy Modification Through Registry - da7733b1-fe08-487e-b536-0a04c6d8b0cd
+- Code Signing Policy Modification Through Built-in tools - b43570de-a908-4f7f-8bdb-b2df6ffd8c80
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Disable and uninstall all suspicious drivers found in the system. This can be done via Device Manager. (Note that this step may require you to boot the system into Safe Mode.)
+- Remove the related services and registry keys found in the system. Note that the service will probably not stop if the driver is still installed.
+  - This can be done via PowerShell `Remove-Service` cmdlet.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Ensure that the Driver Signature Enforcement is enabled on the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+driver where host.os.type == "windows" and process.pid == 4 and
+  dll.code_signature.trusted != true and 
+  not dll.code_signature.status : ("errorExpired", "errorRevoked", "errorCode_endpoint:*")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Sub-technique:
+** Name: Invalid Code Signature
+** ID: T1036.001
+** Reference URL: https://attack.mitre.org/techniques/T1036/001/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-network-activity-from-a-windows-system-binary.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-network-activity-from-a-windows-system-binary.asciidoc
new file mode 100644
index 0000000000..21b919e7c8
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-network-activity-from-a-windows-system-binary.asciidoc
@@ -0,0 +1,204 @@
+[[prebuilt-rule-8-11-17-unusual-network-activity-from-a-windows-system-binary]]
+=== Unusual Network Activity from a Windows System Binary
+
+Identifies network activity from unexpected system applications. This may indicate adversarial activity as these applications are often leveraged by adversaries to execute code and evade detection.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.process-*
+* logs-endpoint.events.network-*
+* winlogbeat-*
+* logs-windows.sysmon_operational-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Resources: Investigation Guide
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Unusual Network Activity from a Windows System Binary*
+
+
+Attackers can abuse certain trusted developer utilities to proxy the execution of malicious payloads. Since these utilities are usually signed, they can bypass the security controls that were put in place to prevent or detect direct execution.
+
+This rule identifies network connections established by trusted developer utilities, which can indicate abuse to execute payloads or process masquerading.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Investigate abnormal behaviors observed by the subject process, such as registry or file modifications, and any spawned child processes.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Examine the host for derived artifacts that indicate suspicious activities:
+  - Analyze the process executable using a private sandboxed analysis system.
+  - Observe and collect information about the following activities in both the sandbox and the alert subject host:
+    - Attempts to contact external domains and addresses.
+      - Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' `process.entity_id`.
+      - Examine the DNS cache for suspicious or anomalous entries.
+        - !{osquery{"label":"Osquery - Retrieve DNS Cache","query":"SELECT * FROM dns_cache"}}
+    - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
+    - Examine the host services for suspicious or anomalous entries.
+      - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+      - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+  - Retrieve the files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+
+
+*False positive analysis*
+
+
+- As trusted developer utilities have dual-use purposes, alerts derived from this rule are not essentially malicious. If these utilities are contacting internal or known trusted domains, review their security and consider creating exceptions if the domain is safe.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+  - If the malicious file was delivered via phishing:
+    - Block the email sender from sending future emails.
+    - Block the malicious web pages.
+    - Remove emails from the sender from mailboxes.
+    - Consider improvements to the security awareness program.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by process.entity_id with maxspan=5m
+  [process where host.os.type == "windows" and event.type == "start" and
+
+     /* known applocker bypasses */
+     (process.name : "bginfo.exe" or
+      process.name : "cdb.exe" or
+      process.name : "control.exe" or
+      process.name : "cmstp.exe" or
+      process.name : "csi.exe" or
+      process.name : "dnx.exe" or
+      process.name : "fsi.exe" or
+      process.name : "ieexec.exe" or
+      process.name : "iexpress.exe" or
+      process.name : "installutil.exe" or
+      process.name : "Microsoft.Workflow.Compiler.exe" or
+      process.name : "MSBuild.exe" or
+      process.name : "msdt.exe" or
+      process.name : "mshta.exe" or
+      process.name : "msiexec.exe" or
+      process.name : "msxsl.exe" or
+      process.name : "odbcconf.exe" or
+      process.name : "rcsi.exe" or
+      process.name : "regsvr32.exe" or
+      process.name : "xwizard.exe")]
+  [network where
+     (process.name : "bginfo.exe" or
+      process.name : "cdb.exe" or
+      process.name : "control.exe" or
+      process.name : "cmstp.exe" or
+      process.name : "csi.exe" or
+      process.name : "dnx.exe" or
+      process.name : "fsi.exe" or
+      process.name : "ieexec.exe" or
+      process.name : "iexpress.exe" or
+      process.name : "installutil.exe" or
+      process.name : "Microsoft.Workflow.Compiler.exe" or
+      (
+        process.name : "msbuild.exe" and
+          destination.ip != "127.0.0.1"
+      ) or
+      process.name : "msdt.exe" or
+      process.name : "mshta.exe" or
+      (
+        process.name : "msiexec.exe" and not
+        dns.question.name : (
+           "ocsp.digicert.com", "ocsp.verisign.com", "ocsp.comodoca.com", "ocsp.entrust.net", "ocsp.usertrust.com",
+           "ocsp.godaddy.com", "ocsp.camerfirma.com", "ocsp.globalsign.com", "ocsp.sectigo.com", "*.local"
+        ) and
+        /* Localhost, DigiCert and Comodo CA IP addresses */
+        not cidrmatch(destination.ip, "127.0.0.1", "192.229.211.108/32", "192.229.221.95/32",
+                      "152.195.38.76/32", "104.18.14.101/32")
+      ) or
+      process.name : "msxsl.exe" or
+      process.name : "odbcconf.exe" or
+      process.name : "rcsi.exe" or
+      process.name : "regsvr32.exe" or
+      process.name : "xwizard.exe")]
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Sub-technique:
+** Name: Match Legitimate Name or Location
+** ID: T1036.005
+** Reference URL: https://attack.mitre.org/techniques/T1036/005/
+* Technique:
+** Name: Trusted Developer Utilities Proxy Execution
+** ID: T1127
+** Reference URL: https://attack.mitre.org/techniques/T1127/
+* Sub-technique:
+** Name: MSBuild
+** ID: T1127.001
+** Reference URL: https://attack.mitre.org/techniques/T1127/001/
+* Sub-technique:
+** Name: Mshta
+** ID: T1218.005
+** Reference URL: https://attack.mitre.org/techniques/T1218/005/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-parent-process-for-cmd-exe.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-parent-process-for-cmd-exe.asciidoc
new file mode 100644
index 0000000000..eab3a14e6d
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-parent-process-for-cmd-exe.asciidoc
@@ -0,0 +1,106 @@
+[[prebuilt-rule-8-11-17-unusual-parent-process-for-cmd-exe]]
+=== Unusual Parent Process for cmd.exe
+
+Identifies a suspicious parent child process relationship with cmd.exe descending from an unusual process.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Execution
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+* Data Source: SentinelOne
+
+*Version*: 212
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  process.name : "cmd.exe" and
+  process.parent.name : ("lsass.exe",
+                         "csrss.exe",
+                         "epad.exe",
+                         "regsvr32.exe",
+                         "dllhost.exe",
+                         "LogonUI.exe",
+                         "wermgr.exe",
+                         "spoolsv.exe",
+                         "jucheck.exe",
+                         "jusched.exe",
+                         "ctfmon.exe",
+                         "taskhostw.exe",
+                         "GoogleUpdate.exe",
+                         "sppsvc.exe",
+                         "sihost.exe",
+                         "slui.exe",
+                         "SIHClient.exe",
+                         "SearchIndexer.exe",
+                         "SearchProtocolHost.exe",
+                         "FlashPlayerUpdateService.exe",
+                         "WerFault.exe",
+                         "WUDFHost.exe",
+                         "unsecapp.exe",
+                         "wlanext.exe" ) and
+  not (process.parent.name : "dllhost.exe" and process.parent.args : "/Processid:{CA8C87C1-929D-45BA-94DB-EF8E6CB346AD}")
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-for-a-windows-host.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-for-a-windows-host.asciidoc
new file mode 100644
index 0000000000..dfb7c0cc61
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-for-a-windows-host.asciidoc
@@ -0,0 +1,133 @@
+[[prebuilt-rule-8-11-17-unusual-process-for-a-windows-host]]
+=== Unusual Process For a Windows Host
+
+Identifies rare processes that do not usually run on individual hosts, which can indicate execution of unauthorized services, malware, or persistence mechanisms. Processes are considered rare when they only run occasionally as compared with other processes running on the host.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-45m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Persistence
+* Resources: Investigation Guide
+
+*Version*: 108
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Unusual Process For a Windows Host*
+
+
+Searching for abnormal Windows processes is a good methodology to find potentially malicious activity within a network. Understanding what is commonly run within an environment and developing baselines for legitimate activity can help uncover potential malware and suspicious behaviors.
+
+This rule uses a machine learning job to detect a Windows process that is rare and unusual for an individual Windows host in your environment.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+  - If the parent process is a legitimate system utility or service, this could be related to software updates or system management. If the parent process is something user-facing like an Office application, this process could be more suspicious.
+  - Investigate the process metadata — such as the digital signature, directory, etc. — to obtain more context that can indicate whether the executable is associated with an expected software vendor or package.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Consider the user as identified by the `user.name` field. Is this program part of an expected workflow for the user who ran this program on this host?
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Validate if the activity has a consistent cadence (for example, if it runs monthly or quarterly), as it could be part of a monthly or quarterly business process.
+- Examine the arguments and working directory of the process. These may provide indications as to the source of the program or the nature of the tasks it is performing.
+- Examine the host for derived artifacts that indicate suspicious activities:
+  - Analyze the process executable using a private sandboxed analysis system.
+  - Observe and collect information about the following activities in both the sandbox and the alert subject host:
+    - Attempts to contact external domains and addresses.
+      - Use the Elastic Defend network events to determine domains and addresses contacted by the subject process by filtering by the process' `process.entity_id`.
+      - Examine the DNS cache for suspicious or anomalous entries.
+        - !{osquery{"label":"Osquery - Retrieve DNS Cache","query":"SELECT * FROM dns_cache"}}
+    - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
+    - Examine the host services for suspicious or anomalous entries.
+      - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
+      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+      - !{osquery{"label":"Retrieve Service Unisgned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
+  - Retrieve the files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- Unusual Process For a Windows Host - 6d448b96-c922-4adb-b51c-b767f1ea5b76
+- Unusual Windows Path Activity - 445a342e-03fb-42d0-8656-0367eb2dead5
+- Unusual Windows Process Calling the Metadata Service - abae61a8-c560-4dbd-acca-1e1438bff36b
+
+
+*Response and Remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Windows Service
+** ID: T1543.003
+** Reference URL: https://attack.mitre.org/techniques/T1543/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-host.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-host.asciidoc
new file mode 100644
index 0000000000..a819a6655b
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-host.asciidoc
@@ -0,0 +1,85 @@
+[[prebuilt-rule-8-11-17-unusual-process-spawned-by-a-host]]
+=== Unusual Process Spawned by a Host
+
+A machine learning job has detected a suspicious Windows process. This process has been classified as suspicious in two ways. It was predicted to be suspicious by the ProblemChild supervised ML model, and it was found to be an unusual process, on a host that does not commonly manifest malicious activity. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-45m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/problemchild
+* https://www.elastic.co/security-labs/detecting-living-off-the-land-attacks-with-new-elastic-integration
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Living off the Land Attack Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Defense Evasion
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Living off the Land (LotL) Attack Detection integration assets to be installed, as well as Windows process events collected by integrations such as Elastic Defend or Winlogbeat.  
+
+
+*LotL Attack Detection Setup*
+
+The LotL Attack Detection integration detects living-off-the-land activity in Windows process events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for LotL Attack Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration or Winlogbeat(https://www.elastic.co/guide/en/beats/winlogbeat/current/_winlogbeat_overview.html).
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To set up and run Winlogbeat, follow https://www.elastic.co/guide/en/beats/winlogbeat/current/winlogbeat-installation-configuration.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the LotL Attack Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: System Binary Proxy Execution
+** ID: T1218
+** Reference URL: https://attack.mitre.org/techniques/T1218/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-parent-process.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-parent-process.asciidoc
new file mode 100644
index 0000000000..214e55d801
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-parent-process.asciidoc
@@ -0,0 +1,85 @@
+[[prebuilt-rule-8-11-17-unusual-process-spawned-by-a-parent-process]]
+=== Unusual Process Spawned by a Parent Process
+
+A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be an unusual child process name, for the parent process, by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-45m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/problemchild
+* https://www.elastic.co/security-labs/detecting-living-off-the-land-attacks-with-new-elastic-integration
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Living off the Land Attack Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Defense Evasion
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Living off the Land (LotL) Attack Detection integration assets to be installed, as well as Windows process events collected by integrations such as Elastic Defend or Winlogbeat.  
+
+
+*LotL Attack Detection Setup*
+
+The LotL Attack Detection integration detects living-off-the-land activity in Windows process events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for LotL Attack Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration or Winlogbeat(https://www.elastic.co/guide/en/beats/winlogbeat/current/_winlogbeat_overview.html).
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To set up and run Winlogbeat, follow https://www.elastic.co/guide/en/beats/winlogbeat/current/winlogbeat-installation-configuration.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the LotL Attack Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-user.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-user.asciidoc
new file mode 100644
index 0000000000..9d1ef1e31e
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-spawned-by-a-user.asciidoc
@@ -0,0 +1,85 @@
+[[prebuilt-rule-8-11-17-unusual-process-spawned-by-a-user]]
+=== Unusual Process Spawned by a User
+
+A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be suspicious given that its user context is unusual and does not commonly manifest malicious activity,by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-45m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/problemchild
+* https://www.elastic.co/security-labs/detecting-living-off-the-land-attacks-with-new-elastic-integration
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Living off the Land Attack Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Defense Evasion
+
+*Version*: 5
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Living off the Land (LotL) Attack Detection integration assets to be installed, as well as Windows process events collected by integrations such as Elastic Defend or Winlogbeat.  
+
+
+*LotL Attack Detection Setup*
+
+The LotL Attack Detection integration detects living-off-the-land activity in Windows process events.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for LotL Attack Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration or Winlogbeat(https://www.elastic.co/guide/en/beats/winlogbeat/current/_winlogbeat_overview.html).
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+- To set up and run Winlogbeat, follow https://www.elastic.co/guide/en/beats/winlogbeat/current/winlogbeat-installation-configuration.html[this] guide.
+
+
+*The following steps should be executed to install assets associated with the LotL Attack Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-writing-data-to-an-external-device.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-writing-data-to-an-external-device.asciidoc
new file mode 100644
index 0000000000..f96ebc857b
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-process-writing-data-to-an-external-device.asciidoc
@@ -0,0 +1,82 @@
+[[prebuilt-rule-8-11-17-unusual-process-writing-data-to-an-external-device]]
+=== Unusual Process Writing Data to an External Device
+
+A machine learning job has detected a rare process writing data to an external device. Malicious actors often use benign-looking processes to mask their data exfiltration activities. The discovery of such a process that has no legitimate reason to write data to external devices can indicate exfiltration.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-2h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/ded
+* https://www.elastic.co/blog/detect-data-exfiltration-activity-with-kibanas-new-integration
+
+*Tags*: 
+
+* Use Case: Data Exfiltration Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Exfiltration
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Data Exfiltration Detection integration assets to be installed, as well as network and file events collected by integrations such as Elastic Defend and Network Packet Capture (for network events only).  
+
+
+*Data Exfiltration Detection Setup*
+
+The Data Exfiltration Detection integration detects data exfiltration activity by identifying abnormalities in network and file events. Anomalies are detected using Elastic's Anomaly Detection feature. 
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Data Exfiltration Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- File events collected by the Elastic Defend integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Data Exfiltration Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Exfiltration
+** ID: TA0010
+** Reference URL: https://attack.mitre.org/tactics/TA0010/
+* Technique:
+** Name: Exfiltration Over Physical Medium
+** ID: T1052
+** Reference URL: https://attack.mitre.org/techniques/T1052/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-directory.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-directory.asciidoc
new file mode 100644
index 0000000000..4cbeb212a8
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-directory.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-unusual-remote-file-directory]]
+=== Unusual Remote File Directory
+
+An anomaly detection job has detected a remote file transfer on an unusual directory indicating a potential lateral movement activity on the host. Many Security solutions monitor well-known directories for suspicious activities, so attackers might use less common directories to bypass monitoring.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-90m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- File events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-extension.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-extension.asciidoc
new file mode 100644
index 0000000000..96f82e54e7
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-extension.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-unusual-remote-file-extension]]
+=== Unusual Remote File Extension
+
+An anomaly detection job has detected a remote file transfer with a rare extension, which could indicate potential lateral movement activity on the host.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-90m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- File events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-size.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-size.asciidoc
new file mode 100644
index 0000000000..5a7245818c
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-remote-file-size.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-unusual-remote-file-size]]
+=== Unusual Remote File Size
+
+A machine learning job has detected an unusually high file size shared by a remote host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Instead of multiple small transfers that can raise alarms, attackers might choose to bundle data into a single large file transfer.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-90m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- File events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-time-or-day-for-an-rdp-session.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-time-or-day-for-an-rdp-session.asciidoc
new file mode 100644
index 0000000000..b43b354f2a
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-unusual-time-or-day-for-an-rdp-session.asciidoc
@@ -0,0 +1,83 @@
+[[prebuilt-rule-8-11-17-unusual-time-or-day-for-an-rdp-session]]
+=== Unusual Time or Day for an RDP Session
+
+A machine learning job has detected an RDP session started at an usual time or weekday. An RDP session at an unusual time could be followed by other suspicious activities, so catching this is a good first step in detecting a larger attack.
+
+*Rule type*: machine_learning
+
+*Rule indices*: None
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 15m
+
+*Searches indices from*: now-12h ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.elastic.co/guide/en/security/current/prebuilt-ml-jobs.html
+* https://docs.elastic.co/en/integrations/lmd
+* https://www.elastic.co/blog/detecting-lateral-movement-activity-a-new-kibana-integration
+* https://www.elastic.co/blog/remote-desktop-protocol-connections-elastic-security
+
+*Tags*: 
+
+* Use Case: Lateral Movement Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Lateral Movement
+
+*Version*: 4
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The rule requires the Lateral Movement Detection integration assets to be installed, as well as file and Windows RDP process events collected by the Elastic Defend integration.  
+
+
+*Lateral Movement Detection Setup*
+
+The Lateral Movement Detection integration detects lateral movement activity by identifying abnormalities in file and Windows RDP events. Anomalies are detected using Elastic's Anomaly Detection feature.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Lateral Movement Detection.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+- Windows RDP process events collected by the https://docs.elastic.co/en/integrations/endpoint[Elastic Defend] integration.
+- To install Elastic Defend, refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[documentation].
+
+
+*The following steps should be executed to install assets associated with the Lateral Movement Detection integration:*
+
+- Go to the Kibana homepage. Under Management, click Integrations.
+- In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Exploitation of Remote Services
+** ID: T1210
+** Reference URL: https://attack.mitre.org/techniques/T1210/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-web-shell-detection-script-process-child-of-common-web-processes.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-web-shell-detection-script-process-child-of-common-web-processes.asciidoc
new file mode 100644
index 0000000000..8c23cc0a8e
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-web-shell-detection-script-process-child-of-common-web-processes.asciidoc
@@ -0,0 +1,192 @@
+[[prebuilt-rule-8-11-17-web-shell-detection-script-process-child-of-common-web-processes]]
+=== Web Shell Detection: Script Process Child of Common Web Processes
+
+Identifies suspicious commands executed via a web server, which may suggest a vulnerability and remote shell access.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-windows.*
+* endgame-*
+* logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.microsoft.com/security/blog/2020/02/04/ghost-in-the-shell-investigating-web-shell-attacks/
+* https://www.elastic.co/security-labs/elastic-response-to-the-the-spring4shell-vulnerability-cve-2022-22965
+* https://www.elastic.co/security-labs/hunting-for-persistence-using-elastic-security-part-1
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Initial Access
+* Tactic: Execution
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: SentinelOne
+
+*Version*: 213
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Web Shell Detection: Script Process Child of Common Web Processes*
+
+
+Adversaries may backdoor web servers with web shells to establish persistent access to systems. A web shell is a web script that is placed on an openly accessible web server to allow an adversary to use the web server as a gateway into a network. A web shell may provide a set of functions to execute or a command-line interface on the system that hosts the web server.
+
+This rule detects a web server process spawning script and command-line interface programs, potentially indicating attackers executing commands using the web shell.
+
+
+*Possible investigation steps*
+
+
+- Investigate abnormal behaviors observed by the subject process such as network connections, registry or file modifications, and any other spawned child processes.
+- Examine the command line to determine which commands or scripts were executed.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
+- If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+  - Use a private sandboxed malware analysis system to perform analysis.
+    - Observe and collect information about the following activities:
+      - Attempts to contact external domains and addresses.
+      - File and registry access, modification, and creation activities.
+      - Service creation and launch activities.
+      - Scheduled task creation.
+  - Use the PowerShell Get-FileHash cmdlet to get the files' SHA-256 hash values.
+    - Search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
+
+
+*False positive analysis*
+
+
+- This activity is unlikely to happen legitimately. Any activity that triggered the alert and is not inherently malicious must be monitored by the security team.
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Remove and block malicious artifacts identified during triage.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+process where host.os.type == "windows" and event.type == "start" and
+  process.parent.name : ("w3wp.exe", "httpd.exe", "nginx.exe", "php.exe", "php-cgi.exe", "tomcat.exe") and
+  process.name : ("cmd.exe", "cscript.exe", "powershell.exe", "pwsh.exe", "powershell_ise.exe", "wmic.exe", "wscript.exe") and
+  not
+  (
+    process.parent.name : ("php.exe", "httpd.exe") and process.name : "cmd.exe" and
+    process.command_line : (
+      "cmd.exe /c mode CON",
+      "cmd.exe /s /c \"mode CON\"",
+      "cmd.exe /c \"mode\"",
+      "cmd.exe /s /c \"tput colors 2>&1\""
+    )
+  )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Server Software Component
+** ID: T1505
+** Reference URL: https://attack.mitre.org/techniques/T1505/
+* Sub-technique:
+** Name: Web Shell
+** ID: T1505.003
+** Reference URL: https://attack.mitre.org/techniques/T1505/003/
+* Tactic:
+** Name: Initial Access
+** ID: TA0001
+** Reference URL: https://attack.mitre.org/tactics/TA0001/
+* Technique:
+** Name: Exploit Public-Facing Application
+** ID: T1190
+** Reference URL: https://attack.mitre.org/techniques/T1190/
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
+* Sub-technique:
+** Name: PowerShell
+** ID: T1059.001
+** Reference URL: https://attack.mitre.org/techniques/T1059/001/
+* Sub-technique:
+** Name: Windows Command Shell
+** ID: T1059.003
+** Reference URL: https://attack.mitre.org/techniques/T1059/003/
+* Sub-technique:
+** Name: Visual Basic
+** ID: T1059.005
+** Reference URL: https://attack.mitre.org/techniques/T1059/005/
+* Technique:
+** Name: Windows Management Instrumentation
+** ID: T1047
+** Reference URL: https://attack.mitre.org/techniques/T1047/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-defender-disabled-via-registry-modification.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-defender-disabled-via-registry-modification.asciidoc
new file mode 100644
index 0000000000..0360d4b592
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-defender-disabled-via-registry-modification.asciidoc
@@ -0,0 +1,170 @@
+[[prebuilt-rule-8-11-17-windows-defender-disabled-via-registry-modification]]
+=== Windows Defender Disabled via Registry Modification
+
+Identifies modifications to the Windows Defender registry settings to disable the service or set the service to be started manually.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* logs-endpoint.events.registry-*
+* endgame-*
+* logs-windows.sysmon_operational-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://thedfirreport.com/2020/12/13/defender-control/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+* Resources: Investigation Guide
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 112
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Windows Defender Disabled via Registry Modification*
+
+
+Microsoft Windows Defender is an antivirus product built into Microsoft Windows, which makes it popular across multiple environments. Disabling it is a common step in threat actor playbooks.
+
+This rule monitors the registry for configurations that disable Windows Defender or the start of its service.
+
+
+*Possible investigation steps*
+
+
+- Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Identify the user account that performed the action and whether it should perform this kind of action.
+- Contact the account owner and confirm whether they are aware of this activity.
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Check if this operation was approved and performed according to the organization's change management policy.
+
+
+*False positive analysis*
+
+
+- This mechanism can be used legitimately. Analysts can dismiss the alert if the administrator is aware of the activity, the configuration is justified (for example, it is being used to deploy other security solutions or troubleshooting), and no other suspicious activity has been observed.
+
+
+*Related rules*
+
+
+- Disabling Windows Defender Security Settings via PowerShell - c8cccb06-faf2-4cd5-886e-2c9636cfcb87
+- Microsoft Windows Defender Tampering - fe794edd-487f-4a90-b285-3ee54f2af2d3
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved hosts to prevent further post-compromise behavior.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Re-enable Windows Defender and restore the service configurations to automatic start.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Review the privileges assigned to the user to ensure that the least privilege principle is being followed.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Using the incident response data, update logging and audit policies to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+If enabling an EQL rule on a non-elastic-agent index (such as beats) for versions <8.2,
+events will not define `event.ingested` and default fallback for EQL rules was not added until version 8.2.
+Hence for this rule to work effectively, users will need to add a custom ingest pipeline to populate
+`event.ingested` to @timestamp.
+For more details on adding a custom ingest pipeline refer - https://www.elastic.co/guide/en/fleet/current/data-streams-pipeline-tutorial.html
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+registry where host.os.type == "windows" and event.type in ("creation", "change") and
+  (
+    (
+      registry.path: (
+        "HKLM\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\DisableAntiSpyware",
+        "\\REGISTRY\\MACHINE\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\DisableAntiSpyware"
+      ) and
+      registry.data.strings: ("1", "0x00000001")
+   ) or
+   (
+      registry.path: (
+        "HKLM\\System\\*ControlSet*\\Services\\WinDefend\\Start",
+        "\\REGISTRY\\MACHINE\\System\\*ControlSet*\\Services\\WinDefend\\Start"
+      ) and
+      registry.data.strings in ("3", "4", "0x00000003", "0x00000004")
+   )
+  ) and
+
+  not
+    (
+      process.executable : (
+          "?:\\WINDOWS\\system32\\services.exe",
+          "?:\\Windows\\System32\\svchost.exe",
+          "?:\\Program Files (x86)\\Trend Micro\\Security Agent\\NTRmv.exe"
+      ) and user.id : "S-1-5-18"
+    )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Tools
+** ID: T1562.001
+** Reference URL: https://attack.mitre.org/techniques/T1562/001/
+* Sub-technique:
+** Name: Indicator Blocking
+** ID: T1562.006
+** Reference URL: https://attack.mitre.org/techniques/T1562/006/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-script-interpreter-executing-process-via-wmi.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-script-interpreter-executing-process-via-wmi.asciidoc
new file mode 100644
index 0000000000..f15fc6c2da
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-script-interpreter-executing-process-via-wmi.asciidoc
@@ -0,0 +1,114 @@
+[[prebuilt-rule-8-11-17-windows-script-interpreter-executing-process-via-wmi]]
+=== Windows Script Interpreter Executing Process via WMI
+
+Identifies use of the built-in Windows script interpreters (cscript.exe or wscript.exe) being used to execute a process via Windows Management Instrumentation (WMI). This may be indicative of malicious activity.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-endpoint.events.process-*
+* logs-endpoint.events.library-*
+* logs-windows.sysmon_operational-*
+* endgame-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Initial Access
+* Tactic: Execution
+* Data Source: Elastic Endgame
+* Data Source: Elastic Defend
+* Data Source: Sysmon
+
+*Version*: 110
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+sequence by host.id with maxspan = 5s
+    [any where host.os.type == "windows" and 
+     (event.category : ("library", "driver") or (event.category == "process" and event.action : "Image loaded*")) and
+     (?dll.name : "wmiutils.dll" or file.name : "wmiutils.dll") and process.name : ("wscript.exe", "cscript.exe")]
+    [process where host.os.type == "windows" and event.type == "start" and
+     process.parent.name : "wmiprvse.exe" and
+     user.domain != "NT AUTHORITY" and
+     (process.pe.original_file_name :
+        (
+          "cscript.exe",
+          "wscript.exe",
+          "PowerShell.EXE",
+          "Cmd.Exe",
+          "MSHTA.EXE",
+          "RUNDLL32.EXE",
+          "REGSVR32.EXE",
+          "MSBuild.exe",
+          "InstallUtil.exe",
+          "RegAsm.exe",
+          "RegSvcs.exe",
+          "msxsl.exe",
+          "CONTROL.EXE",
+          "EXPLORER.EXE",
+          "Microsoft.Workflow.Compiler.exe",
+          "msiexec.exe"
+        ) or
+      process.executable : ("C:\\Users\\*.exe", "C:\\ProgramData\\*.exe")
+     )
+    ]
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Initial Access
+** ID: TA0001
+** Reference URL: https://attack.mitre.org/tactics/TA0001/
+* Technique:
+** Name: Phishing
+** ID: T1566
+** Reference URL: https://attack.mitre.org/techniques/T1566/
+* Sub-technique:
+** Name: Spearphishing Attachment
+** ID: T1566.001
+** Reference URL: https://attack.mitre.org/techniques/T1566/001/
+* Tactic:
+** Name: Execution
+** ID: TA0002
+** Reference URL: https://attack.mitre.org/tactics/TA0002/
+* Technique:
+** Name: Windows Management Instrumentation
+** ID: T1047
+** Reference URL: https://attack.mitre.org/techniques/T1047/
+* Technique:
+** Name: Command and Scripting Interpreter
+** ID: T1059
+** Reference URL: https://attack.mitre.org/techniques/T1059/
+* Sub-technique:
+** Name: Visual Basic
+** ID: T1059.005
+** Reference URL: https://attack.mitre.org/techniques/T1059/005/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-service-installed-via-an-unusual-client.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-service-installed-via-an-unusual-client.asciidoc
new file mode 100644
index 0000000000..7bd9ae4de7
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rule-8-11-17-windows-service-installed-via-an-unusual-client.asciidoc
@@ -0,0 +1,98 @@
+[[prebuilt-rule-8-11-17-windows-service-installed-via-an-unusual-client]]
+=== Windows Service Installed via an Unusual Client
+
+Identifies the creation of a Windows service by an unusual client process. Services may be created with administrator privileges but are executed under SYSTEM privileges, so an adversary may also use a service to escalate privileges from administrator to SYSTEM.
+
+*Rule type*: eql
+
+*Rule indices*: 
+
+* winlogbeat-*
+* logs-system.*
+* logs-windows.*
+
+*Severity*: high
+
+*Risk score*: 73
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://www.x86matthew.com/view_post?id=create_svc_rpc
+* https://docs.microsoft.com/en-us/windows/security/threat-protection/auditing/event-4697
+* https://github.com/atc-project/atomic-threat-coverage/blob/master/Atomic_Threat_Coverage/Logging_Policies/LP_0100_windows_audit_security_system_extension.md
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Windows
+* Use Case: Threat Detection
+* Tactic: Privilege Escalation
+
+*Version*: 109
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+The 'Audit Security System Extension' logging policy must be configured for (Success)
+Steps to implement the logging policy with Advanced Audit Configuration:
+
+```
+Computer Configuration >
+Policies >
+Windows Settings >
+Security Settings >
+Advanced Audit Policies Configuration >
+Audit Policies >
+System >
+Audit Security System Extension (Success)
+```
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+configuration where host.os.type == "windows" and
+  event.action == "service-installed" and
+  (winlog.event_data.ClientProcessId == "0" or winlog.event_data.ParentProcessId == "0") and
+  not winlog.event_data.ServiceFileName : (
+    "?:\\Windows\\VeeamVssSupport\\VeeamGuestHelper.exe",
+    "?:\\Windows\\VeeamLogShipper\\VeeamLogShipper.exe",
+    "%SystemRoot%\\system32\\Drivers\\Crowdstrike\\*-CsInstallerService.exe",
+    "\"%windir%\\AdminArsenal\\PDQInventory-Scanner\\service-1\\PDQInventory-Scanner-1.exe\" "
+  )
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Windows Service
+** ID: T1543.003
+** Reference URL: https://attack.mitre.org/techniques/T1543/003/
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rules-8-11-17-appendix.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rules-8-11-17-appendix.asciidoc
new file mode 100644
index 0000000000..5aa5ab6a9b
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rules-8-11-17-appendix.asciidoc
@@ -0,0 +1,133 @@
+["appendix",role="exclude",id="prebuilt-rule-8-11-17-prebuilt-rules-8-11-17-appendix"]
+= Downloadable rule update v8.11.17
+
+This section lists all updates associated with version 8.11.17 of the Fleet integration *Prebuilt Security Detection Rules*.
+
+
+include::prebuilt-rule-8-11-17-aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc[]
+include::prebuilt-rule-8-11-17-insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc[]
+include::prebuilt-rule-8-11-17-ssm-session-started-to-ec2-instance.asciidoc[]
+include::prebuilt-rule-8-11-17-systemd-service-started-by-unusual-parent-process.asciidoc[]
+include::prebuilt-rule-8-11-17-ssh-authorized-keys-file-modification.asciidoc[]
+include::prebuilt-rule-8-11-17-aws-ec2-admin-credential-fetch-via-assumed-role.asciidoc[]
+include::prebuilt-rule-8-11-17-first-time-seen-aws-secret-value-accessed-in-secrets-manager.asciidoc[]
+include::prebuilt-rule-8-11-17-route53-resolver-query-log-configuration-deleted.asciidoc[]
+include::prebuilt-rule-8-11-17-ec2-ami-shared-with-another-account.asciidoc[]
+include::prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity.asciidoc[]
+include::prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity-with-high-confidence.asciidoc[]
+include::prebuilt-rule-8-11-17-ssh-authorized-keys-file-modified-inside-a-container.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-iso-code.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-ip-address.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-destination-port.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-region.asciidoc[]
+include::prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device.asciidoc[]
+include::prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device-via-airdrop.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-process-writing-data-to-an-external-device.asciidoc[]
+include::prebuilt-rule-8-11-17-machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-dga-activity.asciidoc[]
+include::prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-with-a-high-dga-probability-score.asciidoc[]
+include::prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain.asciidoc[]
+include::prebuilt-rule-8-11-17-github-protected-branch-settings-changed.asciidoc[]
+include::prebuilt-rule-8-11-17-high-mean-of-process-arguments-in-an-rdp-session.asciidoc[]
+include::prebuilt-rule-8-11-17-high-mean-of-rdp-session-duration.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-remote-file-size.asciidoc[]
+include::prebuilt-rule-8-11-17-high-variance-in-rdp-session-duration.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-remote-file-directory.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-remote-file-extension.asciidoc[]
+include::prebuilt-rule-8-11-17-spike-in-number-of-connections-made-from-a-source-ip.asciidoc[]
+include::prebuilt-rule-8-11-17-spike-in-number-of-connections-made-to-a-destination-ip.asciidoc[]
+include::prebuilt-rule-8-11-17-spike-in-number-of-processes-in-an-rdp-session.asciidoc[]
+include::prebuilt-rule-8-11-17-spike-in-remote-file-transfers.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-time-or-day-for-an-rdp-session.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-microsoft-365-mail-access-by-clientappid.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-process-spawned-by-a-host.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-process-spawned-by-a-parent-process.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-process-spawned-by-a-user.asciidoc[]
+include::prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity.asciidoc[]
+include::prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-host.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-parent-process.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-user.asciidoc[]
+include::prebuilt-rule-8-11-17-network-activity-detected-via-kworker.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-network-activity-to-the-internet-by-previously-unknown-executable.asciidoc[]
+include::prebuilt-rule-8-11-17-system-binary-copied-and-or-moved-to-suspicious-directory.asciidoc[]
+include::prebuilt-rule-8-11-17-attempt-to-clear-kernel-ring-buffer.asciidoc[]
+include::prebuilt-rule-8-11-17-executable-masquerading-as-kernel-process.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-which-enumeration.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-reverse-shell-via-child.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-reverse-shell.asciidoc[]
+include::prebuilt-rule-8-11-17-chkconfig-service-add.asciidoc[]
+include::prebuilt-rule-8-11-17-cron-job-created-or-changed-by-previously-unknown-process.asciidoc[]
+include::prebuilt-rule-8-11-17-dynamic-linker-copy.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-file-creation-in-etc-for-persistence.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-persistence-through-init-d-detected.asciidoc[]
+include::prebuilt-rule-8-11-17-persistence-via-kde-autostart-script-or-desktop-file-modification.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-file-creation-via-kworker.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-linux-backdoor-user-account-creation.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-persistence-through-motd-file-creation-detected.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-process-spawned-from-motd-detected.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-persistence-through-run-control-detected.asciidoc[]
+include::prebuilt-rule-8-11-17-shared-object-created-or-changed-by-previously-unknown-process.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-suspicious-file-edit.asciidoc[]
+include::prebuilt-rule-8-11-17-new-systemd-timer-created.asciidoc[]
+include::prebuilt-rule-8-11-17-new-systemd-service-created-by-previously-unknown-process.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-buffer-overflow-attack-detected.asciidoc[]
+include::prebuilt-rule-8-11-17-prompt-for-credentials-with-osascript.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-web-browser-sensitive-file-access.asciidoc[]
+include::prebuilt-rule-8-11-17-quarantine-attrib-removed-by-unsigned-or-untrusted-process.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-macos-ms-office-child-process.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-process-for-a-windows-host.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-network-sweep-detected.asciidoc[]
+include::prebuilt-rule-8-11-17-exporting-exchange-mailbox-via-powershell.asciidoc[]
+include::prebuilt-rule-8-11-17-encrypting-files-with-winrar-or-7z.asciidoc[]
+include::prebuilt-rule-8-11-17-port-forwarding-rule-addition.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-remote-desktop-tunneling-detected.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-screenconnect-client-child-process.asciidoc[]
+include::prebuilt-rule-8-11-17-creation-or-modification-of-domain-backup-dpapi-private-key.asciidoc[]
+include::prebuilt-rule-8-11-17-kirbi-file-creation.asciidoc[]
+include::prebuilt-rule-8-11-17-mimikatz-memssp-log-file-detected.asciidoc[]
+include::prebuilt-rule-8-11-17-adding-hidden-file-attribute-via-attrib.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-antimalware-scan-interface-dll.asciidoc[]
+include::prebuilt-rule-8-11-17-modification-of-amsienable-registry-key.asciidoc[]
+include::prebuilt-rule-8-11-17-code-signing-policy-modification-through-built-in-tools.asciidoc[]
+include::prebuilt-rule-8-11-17-code-signing-policy-modification-through-registry.asciidoc[]
+include::prebuilt-rule-8-11-17-windows-defender-disabled-via-registry-modification.asciidoc[]
+include::prebuilt-rule-8-11-17-powershell-script-block-logging-disabled.asciidoc[]
+include::prebuilt-rule-8-11-17-dns-over-https-enabled-via-registry.asciidoc[]
+include::prebuilt-rule-8-11-17-encoded-executable-stored-in-the-registry.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-endpoint-security-parent-process.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-werfault-child-process.asciidoc[]
+include::prebuilt-rule-8-11-17-microsoft-windows-defender-tampering.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-network-activity-from-a-windows-system-binary.asciidoc[]
+include::prebuilt-rule-8-11-17-local-account-tokenfilter-policy-disabled.asciidoc[]
+include::prebuilt-rule-8-11-17-solarwinds-process-disabling-services-via-registry.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-zoom-child-process.asciidoc[]
+include::prebuilt-rule-8-11-17-untrusted-driver-loaded.asciidoc[]
+include::prebuilt-rule-8-11-17-adfind-command-activity.asciidoc[]
+include::prebuilt-rule-8-11-17-enumerating-domain-trusts-via-dsquery-exe.asciidoc[]
+include::prebuilt-rule-8-11-17-enumerating-domain-trusts-via-nltest-exe.asciidoc[]
+include::prebuilt-rule-8-11-17-unusual-parent-process-for-cmd-exe.asciidoc[]
+include::prebuilt-rule-8-11-17-delayed-execution-via-ping.asciidoc[]
+include::prebuilt-rule-8-11-17-enumeration-command-spawned-via-wmiprvse.asciidoc[]
+include::prebuilt-rule-8-11-17-third-party-backup-files-deleted-via-unexpected-process.asciidoc[]
+include::prebuilt-rule-8-11-17-deleting-backup-catalogs-with-wbadmin.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-ransomware-behavior-high-count-of-readme-files-by-system.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-file-renamed-via-smb.asciidoc[]
+include::prebuilt-rule-8-11-17-potential-ransomware-note-file-dropped-via-smb.asciidoc[]
+include::prebuilt-rule-8-11-17-windows-script-interpreter-executing-process-via-wmi.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-ms-outlook-child-process.asciidoc[]
+include::prebuilt-rule-8-11-17-adobe-hijack-persistence.asciidoc[]
+include::prebuilt-rule-8-11-17-registry-persistence-via-appcert-dll.asciidoc[]
+include::prebuilt-rule-8-11-17-persistence-via-scheduled-job-creation.asciidoc[]
+include::prebuilt-rule-8-11-17-uncommon-registry-persistence-change.asciidoc[]
+include::prebuilt-rule-8-11-17-account-password-reset-remotely.asciidoc[]
+include::prebuilt-rule-8-11-17-suspicious-service-was-installed-in-the-system.asciidoc[]
+include::prebuilt-rule-8-11-17-system-shells-via-services.asciidoc[]
+include::prebuilt-rule-8-11-17-persistence-via-bits-job-notify-cmdline.asciidoc[]
+include::prebuilt-rule-8-11-17-web-shell-detection-script-process-child-of-common-web-processes.asciidoc[]
+include::prebuilt-rule-8-11-17-disabling-user-account-control-via-registry-modification.asciidoc[]
+include::prebuilt-rule-8-11-17-first-time-seen-driver-loaded.asciidoc[]
+include::prebuilt-rule-8-11-17-service-control-spawned-via-script-interpreter.asciidoc[]
+include::prebuilt-rule-8-11-17-uac-bypass-attempt-via-windows-directory-masquerading.asciidoc[]
+include::prebuilt-rule-8-11-17-uac-bypass-via-windows-firewall-snap-in-hijack.asciidoc[]
+include::prebuilt-rule-8-11-17-windows-service-installed-via-an-unusual-client.asciidoc[]
diff --git a/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rules-8-11-17-summary.asciidoc b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rules-8-11-17-summary.asciidoc
new file mode 100644
index 0000000000..ff8dde7c07
--- /dev/null
+++ b/docs/detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rules-8-11-17-summary.asciidoc
@@ -0,0 +1,266 @@
+[[prebuilt-rule-8-11-17-prebuilt-rules-8-11-17-summary]]
+[role="xpack"]
+== Update v8.11.17
+
+This section lists all updates associated with version 8.11.17 of the Fleet integration *Prebuilt Security Detection Rules*.
+
+
+[width="100%",options="header"]
+|==============================================
+|Rule |Description |Status |Version
+
+|<<prebuilt-rule-8-11-17-aws-s3-bucket-expiration-lifecycle-configuration-added, AWS S3 Bucket Expiration Lifecycle Configuration Added>> | Identifies an expiration lifecycle configuration added to an S3 bucket. Lifecycle configurations can be used to manage objects in a bucket, including setting expiration policies. This rule detects when a lifecycle configuration is added to an S3 bucket, which could indicate that objects in the bucket will be automatically deleted after a specified period of time. This could be used to evade detection by deleting objects that contain evidence of malicious activity. | new | 1 
+
+|<<prebuilt-rule-8-11-17-insecure-aws-ec2-vpc-security-group-ingress-rule-added, Insecure AWS EC2 VPC Security Group Ingress Rule Added>> | Identifies when a specified inbound (ingress) rule is added or adjusted for a VPC security group in AWS EC2. This rule detects when a security group rule is added that allows traffic from any IP address or from a specific IP address to common remote access ports, such as 22 (SSH) or 3389 (RDP). Adversaries may add these rules to allow remote access to VPC instances from any location, increasing the attack surface and potentially exposing the instances to unauthorized access. | new | 1 
+
+|<<prebuilt-rule-8-11-17-ssm-session-started-to-ec2-instance, SSM Session Started to EC2 Instance>> | Identifies the first occurrence of an AWS resource establishing a session via SSM to an EC2 instance. Adversaries may use AWS Systems Manager to establish a session to an EC2 instance to execute commands on the instance. This can be used to gain access to the instance and perform actions such as privilege escalation. This rule helps detect the first occurrence of this activity for a given AWS resource. | new | 1 
+
+|<<prebuilt-rule-8-11-17-systemd-service-started-by-unusual-parent-process, Systemd Service Started by Unusual Parent Process>> | Systemctl is a process used in Linux systems to manage systemd processes through service configuration files. Malicious actors can leverage systemd services to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection. | new | 1 
+
+|<<prebuilt-rule-8-11-17-ssh-authorized-keys-file-modification, SSH Authorized Keys File Modification>> | The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s). | update | 206 
+
+|<<prebuilt-rule-8-11-17-aws-ec2-admin-credential-fetch-via-assumed-role, AWS EC2 Admin Credential Fetch via Assumed Role>> | Identifies the first occurrence of a user identity in AWS using `GetPassword` for the administrator password of an EC2 instance with an assumed role. Adversaries may use this API call to escalate privileges or move laterally within EC2 instances. | update | 3 
+
+|<<prebuilt-rule-8-11-17-first-time-seen-aws-secret-value-accessed-in-secrets-manager, First Time Seen AWS Secret Value Accessed in Secrets Manager>> | An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service may attempt to leverage the compromised service to access secrets in AWS Secrets Manager. This rule looks for the first time a specific user identity has programmatically retrieved a specific secret value from Secrets Manager using the `GetSecretValue` action. This rule assumes that AWS services such as Lambda functions and EC2 instances are setup with IAM role's assigned that have the necessary permissions to access the secrets in Secrets Manager. An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service would rely on the compromised service's IAM role to access the secrets in Secrets Manager. | update | 311 
+
+|<<prebuilt-rule-8-11-17-route53-resolver-query-log-configuration-deleted, Route53 Resolver Query Log Configuration Deleted>> | Identifies when a Route53 Resolver Query Log Configuration is deleted. When a Route53 Resolver query log configuration is deleted, Resolver stops logging DNS queries and responses for the specified configuration. Adversaries may delete query log configurations to evade detection or cover their tracks. | update | 2 
+
+|<<prebuilt-rule-8-11-17-ec2-ami-shared-with-another-account, EC2 AMI Shared with Another Account>> | Identifies an AWS Amazon Machine Image (AMI) being shared with another AWS account. Adversaries with access may share an AMI with an external AWS account as a means of data exfiltration. AMIs can contain secrets, bash histories, code artifacts, and other sensitive data that adversaries may abuse if shared with unauthorized accounts. AMIs can be made publicly available accidentally as well. | update | 2 
+
+|<<prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity, Statistical Model Detected C2 Beaconing Activity>> | A statistical model has identified command-and-control (C2) beaconing activity. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network. | update | 5 
+
+|<<prebuilt-rule-8-11-17-statistical-model-detected-c2-beaconing-activity-with-high-confidence, Statistical Model Detected C2 Beaconing Activity with High Confidence>> | A statistical model has identified command-and-control (C2) beaconing activity with high confidence. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network. | update | 5 
+
+|<<prebuilt-rule-8-11-17-ssh-authorized-keys-file-modified-inside-a-container, SSH Authorized Keys File Modified Inside a Container>> | This rule detects the creation or modification of an authorized_keys or sshd_config file inside a container. The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s). Unexpected and unauthorized SSH usage inside a container can be an indicator of compromise and should be investigated. | update | 3 
+
+|<<prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-iso-code, Potential Data Exfiltration Activity to an Unusual ISO Code>> | A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. | update | 4 
+
+|<<prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-ip-address, Potential Data Exfiltration Activity to an Unusual IP Address>> | A machine learning job has detected data exfiltration to a particular geo-location (by IP address). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. | update | 4 
+
+|<<prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-destination-port, Potential Data Exfiltration Activity to an Unusual Destination Port>> | A machine learning job has detected data exfiltration to a particular destination port. Data transfer patterns that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. | update | 4 
+
+|<<prebuilt-rule-8-11-17-potential-data-exfiltration-activity-to-an-unusual-region, Potential Data Exfiltration Activity to an Unusual Region>> | A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. | update | 4 
+
+|<<prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device, Spike in Bytes Sent to an External Device>> | A machine learning job has detected high bytes of data written to an external device. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities. | update | 4 
+
+|<<prebuilt-rule-8-11-17-spike-in-bytes-sent-to-an-external-device-via-airdrop, Spike in Bytes Sent to an External Device via Airdrop>> | A machine learning job has detected high bytes of data written to an external device via Airdrop. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities. | update | 4 
+
+|<<prebuilt-rule-8-11-17-unusual-process-writing-data-to-an-external-device, Unusual Process Writing Data to an External Device>> | A machine learning job has detected a rare process writing data to an external device. Malicious actors often use benign-looking processes to mask their data exfiltration activities. The discovery of such a process that has no legitimate reason to write data to external devices can indicate exfiltration. | update | 4 
+
+|<<prebuilt-rule-8-11-17-machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain, Machine Learning Detected DGA activity using a known SUNBURST DNS domain>> | A supervised machine learning model has identified a DNS question name that used by the SUNBURST malware and is predicted to be the result of a Domain Generation Algorithm. | update | 4 
+
+|<<prebuilt-rule-8-11-17-potential-dga-activity, Potential DGA Activity>> | A population analysis machine learning job detected potential DGA (domain generation algorithm) activity. Such activity is often used by malware command and control (C2) channels. This machine learning job looks for a source IP address making DNS requests that have an aggregate high probability of being DGA activity. | update | 4 
+
+|<<prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-with-a-high-dga-probability-score, Machine Learning Detected a DNS Request With a High DGA Probability Score>> | A supervised machine learning model has identified a DNS question name with a high probability of sourcing from a Domain Generation Algorithm (DGA), which could indicate command and control network activity. | update | 4 
+
+|<<prebuilt-rule-8-11-17-machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain, Machine Learning Detected a DNS Request Predicted to be a DGA Domain>> | A supervised machine learning model has identified a DNS question name that is predicted to be the result of a Domain Generation Algorithm (DGA), which could indicate command and control network activity. | update | 4 
+
+|<<prebuilt-rule-8-11-17-github-protected-branch-settings-changed, GitHub Protected Branch Settings Changed>> | This rule detects setting modifications for protected branches of a GitHub repository. Branch protection rules can be used to enforce certain workflows or requirements before a contributor can push changes to a branch in your repository. Changes to these protected branch settings should be investigated and verified as legitimate activity. Unauthorized changes could be used to lower your organization's security posture and leave you exposed for future attacks. | update | 3 
+
+|<<prebuilt-rule-8-11-17-high-mean-of-process-arguments-in-an-rdp-session, High Mean of Process Arguments in an RDP Session>> | A machine learning job has detected unusually high number of process arguments in an RDP session. Executing sophisticated attacks such as lateral movement can involve the use of complex commands, obfuscation mechanisms, redirection and piping, which in turn increases the number of arguments in a command. | update | 4 
+
+|<<prebuilt-rule-8-11-17-high-mean-of-rdp-session-duration, High Mean of RDP Session Duration>> | A machine learning job has detected unusually high mean of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine. | update | 4 
+
+|<<prebuilt-rule-8-11-17-unusual-remote-file-size, Unusual Remote File Size>> | A machine learning job has detected an unusually high file size shared by a remote host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Instead of multiple small transfers that can raise alarms, attackers might choose to bundle data into a single large file transfer. | update | 4 
+
+|<<prebuilt-rule-8-11-17-high-variance-in-rdp-session-duration, High Variance in RDP Session Duration>> | A machine learning job has detected unusually high variance of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine. | update | 4 
+
+|<<prebuilt-rule-8-11-17-unusual-remote-file-directory, Unusual Remote File Directory>> | An anomaly detection job has detected a remote file transfer on an unusual directory indicating a potential lateral movement activity on the host. Many Security solutions monitor well-known directories for suspicious activities, so attackers might use less common directories to bypass monitoring. | update | 4 
+
+|<<prebuilt-rule-8-11-17-unusual-remote-file-extension, Unusual Remote File Extension>> | An anomaly detection job has detected a remote file transfer with a rare extension, which could indicate potential lateral movement activity on the host. | update | 4 
+
+|<<prebuilt-rule-8-11-17-spike-in-number-of-connections-made-from-a-source-ip, Spike in Number of Connections Made from a Source IP>> | A machine learning job has detected a high count of destination IPs establishing an RDP connection with a single source IP. Once an attacker has gained access to one system, they might attempt to access more in the network in search of valuable assets, data, or further access points. | update | 4 
+
+|<<prebuilt-rule-8-11-17-spike-in-number-of-connections-made-to-a-destination-ip, Spike in Number of Connections Made to a Destination IP>> | A machine learning job has detected a high count of source IPs establishing an RDP connection with a single destination IP. Attackers might use multiple compromised systems to attack a target to ensure redundancy in case a source IP gets detected and blocked. | update | 4 
+
+|<<prebuilt-rule-8-11-17-spike-in-number-of-processes-in-an-rdp-session, Spike in Number of Processes in an RDP Session>> | A machine learning job has detected unusually high number of processes started in a single RDP session. Executing a large number of processes remotely on other machines can be an indicator of lateral movement activity. | update | 4 
+
+|<<prebuilt-rule-8-11-17-spike-in-remote-file-transfers, Spike in Remote File Transfers>> | A machine learning job has detected an abnormal volume of remote files shared on the host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Attackers might perform multiple small transfers to match normal egress activity in the network, to evade detection. | update | 4 
+
+|<<prebuilt-rule-8-11-17-unusual-time-or-day-for-an-rdp-session, Unusual Time or Day for an RDP Session>> | A machine learning job has detected an RDP session started at an usual time or weekday. An RDP session at an unusual time could be followed by other suspicious activities, so catching this is a good first step in detecting a larger attack. | update | 4 
+
+|<<prebuilt-rule-8-11-17-suspicious-microsoft-365-mail-access-by-clientappid, Suspicious Microsoft 365 Mail Access by ClientAppId>> | Identifies when a Microsoft 365 Mailbox is accessed by a ClientAppId that was observed for the fist time during the last 10 days. | update | 106 
+
+|<<prebuilt-rule-8-11-17-unusual-process-spawned-by-a-host, Unusual Process Spawned by a Host>> | A machine learning job has detected a suspicious Windows process. This process has been classified as suspicious in two ways. It was predicted to be suspicious by the ProblemChild supervised ML model, and it was found to be an unusual process, on a host that does not commonly manifest malicious activity. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. | update | 5 
+
+|<<prebuilt-rule-8-11-17-unusual-process-spawned-by-a-parent-process, Unusual Process Spawned by a Parent Process>> | A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be an unusual child process name, for the parent process, by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. | update | 5 
+
+|<<prebuilt-rule-8-11-17-unusual-process-spawned-by-a-user, Unusual Process Spawned by a User>> | A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be suspicious given that its user context is unusual and does not commonly manifest malicious activity,by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. | update | 5 
+
+|<<prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity, Machine Learning Detected a Suspicious Windows Event Predicted to be Malicious Activity>> | A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious. | update | 5 
+
+|<<prebuilt-rule-8-11-17-machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score, Machine Learning Detected a Suspicious Windows Event with a High Malicious Probability Score>> | A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious. | update | 5 
+
+|<<prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-host, Suspicious Windows Process Cluster Spawned by a Host>> | A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same host name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. | update | 5 
+
+|<<prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-parent-process, Suspicious Windows Process Cluster Spawned by a Parent Process>> | A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same parent process name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. | update | 5 
+
+|<<prebuilt-rule-8-11-17-suspicious-windows-process-cluster-spawned-by-a-user, Suspicious Windows Process Cluster Spawned by a User>> | A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same user name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. | update | 5 
+
+|<<prebuilt-rule-8-11-17-network-activity-detected-via-kworker, Network Activity Detected via Kworker>> | This rule monitors for network connections from a kworker process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process. | update | 5 
+
+|<<prebuilt-rule-8-11-17-suspicious-network-activity-to-the-internet-by-previously-unknown-executable, Suspicious Network Activity to the Internet by Previously Unknown Executable>> | This rule monitors for network connectivity to the internet from a previously unknown executable located in a suspicious directory. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to establish connections to unknown or suspicious destinations such as a command and control server. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise. | update | 9 
+
+|<<prebuilt-rule-8-11-17-system-binary-copied-and-or-moved-to-suspicious-directory, System Binary Copied and/or Moved to Suspicious Directory>> | This rule monitors for the copying or moving of a system binary to a suspicious directory. Adversaries may copy/move and rename system binaries to evade detection. Copying a system binary to a different location should not occur often, so if it does, the activity should be investigated. | update | 8 
+
+|<<prebuilt-rule-8-11-17-attempt-to-clear-kernel-ring-buffer, Attempt to Clear Kernel Ring Buffer>> | Monitors for the deletion of the kernel ring buffer events through dmesg. Attackers may clear kernel ring buffer events to evade detection after installing a Linux kernel module (LKM). | update | 5 
+
+|<<prebuilt-rule-8-11-17-executable-masquerading-as-kernel-process, Executable Masquerading as Kernel Process>> | Monitors for kernel processes with associated process executable fields that are not empty. Unix kernel processes such as kthreadd and kworker typically do not have process.executable fields associated to them. Attackers may attempt to hide their malicious programs by masquerading as legitimate kernel processes. | update | 3 
+
+|<<prebuilt-rule-8-11-17-suspicious-which-enumeration, Suspicious which Enumeration>> | This rule monitors for the usage of the which command with an unusual amount of process arguments. Attackers may leverage the which command to enumerate the system for useful installed utilities that may be used after compromising a system to escalate privileges or move latteraly across the network. | update | 6 
+
+|<<prebuilt-rule-8-11-17-potential-reverse-shell-via-child, Potential Reverse Shell via Child>> | This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a network event that is followed by the creation of a shell process with suspicious command line arguments. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system. | update | 3 
+
+|<<prebuilt-rule-8-11-17-potential-reverse-shell, Potential Reverse Shell>> | This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a parent-child relationship where a network event is followed by the creation of a shell process. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system. | update | 9 
+
+|<<prebuilt-rule-8-11-17-chkconfig-service-add, Chkconfig Service Add>> | Detects the use of the chkconfig binary to manually add a service for management by chkconfig. Threat actors may utilize this technique to maintain persistence on a system. When a new service is added, chkconfig ensures that the service has either a start or a kill entry in every runlevel and when the system is rebooted the service file added will run providing long-term persistence. | update | 112 
+
+|<<prebuilt-rule-8-11-17-cron-job-created-or-changed-by-previously-unknown-process, Cron Job Created or Changed by Previously Unknown Process>> | Linux cron jobs are scheduled tasks that can be leveraged by malicious actors for persistence, privilege escalation and command execution. By creating or modifying cron job configurations, attackers can execute malicious commands or scripts at predefined intervals, ensuring their continued presence and enabling unauthorized activities. | update | 10 
+
+|<<prebuilt-rule-8-11-17-dynamic-linker-copy, Dynamic Linker Copy>> | Detects the copying of the Linux dynamic loader binary and subsequent file creation for the purpose of creating a backup copy. This technique was seen recently being utilized by Linux malware prior to patching the dynamic loader in order to inject and preload a malicious shared object file. This activity should never occur and if it does then it should be considered highly suspicious or malicious. | update | 109 
+
+|<<prebuilt-rule-8-11-17-suspicious-file-creation-in-etc-for-persistence, Suspicious File Creation in /etc for Persistence>> | Detects the manual creation of files in specific etc directories, via user root, used by Linux malware to persist and elevate privileges on compromised systems. File creation in these directories should not be entirely common and could indicate a malicious binary or script installing persistence mechanisms for long term access. | update | 114 
+
+|<<prebuilt-rule-8-11-17-potential-persistence-through-init-d-detected, Potential Persistence Through init.d Detected>> | Files that are placed in the /etc/init.d/ directory in Unix can be used to start custom applications, services, scripts or commands during start-up. Init.d has been mostly replaced in favor of Systemd. However, the "systemd-sysv-generator" can convert init.d files to service unit files that run at boot. Adversaries may add or alter files located in the /etc/init.d/ directory to execute malicious code upon boot in order to gain persistence on the system. | update | 10 
+
+|<<prebuilt-rule-8-11-17-persistence-via-kde-autostart-script-or-desktop-file-modification, Persistence via KDE AutoStart Script or Desktop File Modification>> | Identifies the creation or modification of a K Desktop Environment (KDE) AutoStart script or desktop file that will execute upon each user logon. Adversaries may abuse this method for persistence. | update | 111 
+
+|<<prebuilt-rule-8-11-17-suspicious-file-creation-via-kworker, Suspicious File Creation via Kworker>> | This rule monitors for a file creation event originating from a kworker parent process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process. | update | 4 
+
+|<<prebuilt-rule-8-11-17-potential-linux-backdoor-user-account-creation, Potential Linux Backdoor User Account Creation>> | Identifies the attempt to create a new backdoor user by setting the user's UID to 0. Attackers may alter a user's UID to 0 to establish persistence on a system. | update | 7 
+
+|<<prebuilt-rule-8-11-17-potential-persistence-through-motd-file-creation-detected, Potential Persistence Through MOTD File Creation Detected>> | Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" and "/usr/lib/update-notifier/" directories. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. This rule detects the creation of potentially malicious files within the default MOTD file directories. | update | 10 
+
+|<<prebuilt-rule-8-11-17-suspicious-process-spawned-from-motd-detected, Suspicious Process Spawned from MOTD Detected>> | Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" and "/usr/lib/update-notifier/" directories. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. This rule detects the execution of potentially malicious processes through the MOTD utility. | update | 9 
+
+|<<prebuilt-rule-8-11-17-potential-persistence-through-run-control-detected, Potential Persistence Through Run Control Detected>> | This rule monitors the creation/alteration of the rc.local file by a previously unknown process executable through the use of the new terms rule type. The /etc/rc.local file is used to start custom applications, services, scripts or commands during start-up. The rc.local file has mostly been replaced by Systemd. However, through the "systemd-rc-local-generator", rc.local files can be converted to services that run at boot. Adversaries may alter rc.local to execute malicious code at start-up, and gain persistence onto the system. | update | 111 
+
+|<<prebuilt-rule-8-11-17-shared-object-created-or-changed-by-previously-unknown-process, Shared Object Created or Changed by Previously Unknown Process>> | This rule monitors the creation of shared object files by previously unknown processes. The creation of a shared object file involves compiling code into a dynamically linked library that can be loaded by other programs at runtime. While this process is typically used for legitimate purposes, malicious actors can leverage shared object files to execute unauthorized code, inject malicious functionality into legitimate processes, or bypass security controls. This allows malware to persist on the system, evade detection, and potentially compromise the integrity and confidentiality of the affected system and its data. | update | 8 
+
+|<<prebuilt-rule-8-11-17-potential-suspicious-file-edit, Potential Suspicious File Edit>> | This rule monitors for the potential edit of a suspicious file. In Linux, when editing a file through an editor, a temporary .swp file is created. By monitoring for the creation of this .swp file, we can detect potential file edits of suspicious files. The execution of this rule is not a clear sign of the file being edited, as just opening the file through an editor will trigger this event. Attackers may alter any of the files added in this rule to establish persistence, escalate privileges or perform reconnaisance on the system. | update | 5 
+
+|<<prebuilt-rule-8-11-17-new-systemd-timer-created, New Systemd Timer Created>> | Detects the creation of a systemd timer within any of the default systemd timer directories. Systemd timers can be used by an attacker to gain persistence, by scheduling the execution of a command or script. Similarly to cron/at, systemd timers can be set up to execute on boot time, or on a specific point in time, which allows attackers to regain access in case the connection to the infected asset was lost. | update | 10 
+
+|<<prebuilt-rule-8-11-17-new-systemd-service-created-by-previously-unknown-process, New Systemd Service Created by Previously Unknown Process>> | Systemd service files are configuration files in Linux systems used to define and manage system services. Malicious actors can leverage systemd service files to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection. | update | 10 
+
+|<<prebuilt-rule-8-11-17-potential-buffer-overflow-attack-detected, Potential Buffer Overflow Attack Detected>> | Detects potential buffer overflow attacks by querying the "Segfault Detected" pre-built rule signal index, through a threshold rule, with a minimum number of 100 segfault alerts in a short timespan. A large amount of segfaults in a short time interval could indicate application exploitation attempts. | update | 3 
+
+|<<prebuilt-rule-8-11-17-prompt-for-credentials-with-osascript, Prompt for Credentials with OSASCRIPT>> | Identifies the use of osascript to execute scripts via standard input that may prompt a user with a rogue dialog for credentials. | update | 208 
+
+|<<prebuilt-rule-8-11-17-suspicious-web-browser-sensitive-file-access, Suspicious Web Browser Sensitive File Access>> | Identifies the access or file open of web browser sensitive files by an untrusted/unsigned process or osascript. Adversaries may acquire credentials from web browsers by reading files specific to the target browser. | update | 208 
+
+|<<prebuilt-rule-8-11-17-quarantine-attrib-removed-by-unsigned-or-untrusted-process, Quarantine Attrib Removed by Unsigned or Untrusted Process>> | Detects deletion of the quarantine attribute by an unusual process (xattr). In macOS, when applications or programs are downloaded from the internet, there is a quarantine flag set on the file. This attribute is read by Apple's Gatekeeper defense program at execution time. An adversary may disable this attribute to evade defenses. | update | 109 
+
+|<<prebuilt-rule-8-11-17-suspicious-macos-ms-office-child-process, Suspicious macOS MS Office Child Process>> | Identifies suspicious child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, and Excel). These child processes are often launched during exploitation of Office applications or by documents with malicious macros. | update | 207 
+
+|<<prebuilt-rule-8-11-17-unusual-process-for-a-windows-host, Unusual Process For a Windows Host>> | Identifies rare processes that do not usually run on individual hosts, which can indicate execution of unauthorized services, malware, or persistence mechanisms. Processes are considered rare when they only run occasionally as compared with other processes running on the host. | update | 108 
+
+|<<prebuilt-rule-8-11-17-potential-network-sweep-detected, Potential Network Sweep Detected>> | This rule identifies a potential network sweep. A network sweep is a method used by attackers to scan a target network, identifying active hosts, open ports, and available services to gather information on vulnerabilities and weaknesses. This reconnaissance helps them plan subsequent attacks and exploit potential entry points for unauthorized access, data theft, or other malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination hosts on commonly used network services. | update | 6 
+
+|<<prebuilt-rule-8-11-17-exporting-exchange-mailbox-via-powershell, Exporting Exchange Mailbox via PowerShell>> | Identifies the use of the Exchange PowerShell cmdlet, New-MailBoxExportRequest, to export the contents of a primary mailbox or archive to a .pst file. Adversaries may target user email to collect sensitive information. | update | 213 
+
+|<<prebuilt-rule-8-11-17-encrypting-files-with-winrar-or-7z, Encrypting Files with WinRar or 7z>> | Identifies use of WinRar or 7z to create an encrypted files. Adversaries will often compress and encrypt data in preparation for exfiltration. | update | 112 
+
+|<<prebuilt-rule-8-11-17-port-forwarding-rule-addition, Port Forwarding Rule Addition>> | Identifies the creation of a new port forwarding rule. An adversary may abuse this technique to bypass network segmentation restrictions. | update | 212 
+
+|<<prebuilt-rule-8-11-17-potential-remote-desktop-tunneling-detected, Potential Remote Desktop Tunneling Detected>> | Identifies potential use of an SSH utility to establish RDP over a reverse SSH Tunnel. This can be used by attackers to enable routing of network packets that would otherwise not reach their intended destination. | update | 212 
+
+|<<prebuilt-rule-8-11-17-suspicious-screenconnect-client-child-process, Suspicious ScreenConnect Client Child Process>> | Identifies suspicious processes being spawned by the ScreenConnect client processes. This activity may indicate execution abusing unauthorized access to the ScreenConnect remote access software. | update | 103 
+
+|<<prebuilt-rule-8-11-17-creation-or-modification-of-domain-backup-dpapi-private-key, Creation or Modification of Domain Backup DPAPI private key>> | Identifies the creation or modification of Domain Backup private keys. Adversaries may extract the Data Protection API (DPAPI) domain backup key from a Domain Controller (DC) to be able to decrypt any domain user master key file. | update | 210 
+
+|<<prebuilt-rule-8-11-17-kirbi-file-creation, Kirbi File Creation>> | Identifies the creation of .kirbi files. The creation of this kind of file is an indicator of an attacker running Kerberos ticket dump utilities, such as Mimikatz, and precedes attacks such as Pass-The-Ticket (PTT), which allows the attacker to impersonate users using Kerberos tickets. | update | 107 
+
+|<<prebuilt-rule-8-11-17-mimikatz-memssp-log-file-detected, Mimikatz Memssp Log File Detected>> | Identifies the password log file from the default Mimikatz memssp module. | update | 211 
+
+|<<prebuilt-rule-8-11-17-adding-hidden-file-attribute-via-attrib, Adding Hidden File Attribute via Attrib>> | Adversaries can add the 'hidden' attribute to files to hide them from the user in an attempt to evade detection. | update | 112 
+
+|<<prebuilt-rule-8-11-17-suspicious-antimalware-scan-interface-dll, Suspicious Antimalware Scan Interface DLL>> | Identifies the creation of the Antimalware Scan Interface (AMSI) DLL in an unusual location. This may indicate an attempt to bypass AMSI by loading a rogue AMSI module instead of the legit one. | update | 111 
+
+|<<prebuilt-rule-8-11-17-modification-of-amsienable-registry-key, Modification of AmsiEnable Registry Key>> | Identifies modifications of the AmsiEnable registry key to 0, which disables the Antimalware Scan Interface (AMSI). An adversary can modify this key to disable AMSI protections. | update | 111 
+
+|<<prebuilt-rule-8-11-17-code-signing-policy-modification-through-built-in-tools, Code Signing Policy Modification Through Built-in tools>> | Identifies attempts to disable/modify the code signing policy through system native utilities. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code. | update | 8 
+
+|<<prebuilt-rule-8-11-17-code-signing-policy-modification-through-registry, Code Signing Policy Modification Through Registry>> | Identifies attempts to disable the code signing policy through the registry. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code. | update | 10 
+
+|<<prebuilt-rule-8-11-17-windows-defender-disabled-via-registry-modification, Windows Defender Disabled via Registry Modification>> | Identifies modifications to the Windows Defender registry settings to disable the service or set the service to be started manually. | update | 112 
+
+|<<prebuilt-rule-8-11-17-powershell-script-block-logging-disabled, PowerShell Script Block Logging Disabled>> | Identifies attempts to disable PowerShell Script Block Logging via registry modification. Attackers may disable this logging to conceal their activities in the host and evade detection. | update | 110 
+
+|<<prebuilt-rule-8-11-17-dns-over-https-enabled-via-registry, DNS-over-HTTPS Enabled via Registry>> | Identifies when a user enables DNS-over-HTTPS. This can be used to hide internet activity or the process of exfiltrating data. With this enabled, an organization will lose visibility into data such as query type, response, and originating IP, which are used to determine bad actors. | update | 110 
+
+|<<prebuilt-rule-8-11-17-encoded-executable-stored-in-the-registry, Encoded Executable Stored in the Registry>> | Identifies registry write modifications to hide an encoded portable executable. This could be indicative of adversary defense evasion by avoiding the storing of malicious content directly on disk. | update | 209 
+
+|<<prebuilt-rule-8-11-17-suspicious-endpoint-security-parent-process, Suspicious Endpoint Security Parent Process>> | A suspicious Endpoint Security parent process was detected. This may indicate a process hollowing or other form of code injection. | update | 112 
+
+|<<prebuilt-rule-8-11-17-suspicious-werfault-child-process, Suspicious WerFault Child Process>> | A suspicious WerFault child process was detected, which may indicate an attempt to run via the SilentProcessExit registry key manipulation. Verify process details such as command line, network connections and file writes. | update | 214 
+
+|<<prebuilt-rule-8-11-17-microsoft-windows-defender-tampering, Microsoft Windows Defender Tampering>> | Identifies when one or more features on Microsoft Defender are disabled. Adversaries may disable or tamper with Microsoft Defender features to evade detection and conceal malicious behavior. | update | 111 
+
+|<<prebuilt-rule-8-11-17-unusual-network-activity-from-a-windows-system-binary, Unusual Network Activity from a Windows System Binary>> | Identifies network activity from unexpected system applications. This may indicate adversarial activity as these applications are often leveraged by adversaries to execute code and evade detection. | update | 112 
+
+|<<prebuilt-rule-8-11-17-local-account-tokenfilter-policy-disabled, Local Account TokenFilter Policy Disabled>> | Identifies registry modification to the LocalAccountTokenFilterPolicy policy. If this value exists (which doesn't by default) and is set to 1, then remote connections from all local members of Administrators are granted full high-integrity tokens during negotiation. | update | 110 
+
+|<<prebuilt-rule-8-11-17-solarwinds-process-disabling-services-via-registry, SolarWinds Process Disabling Services via Registry>> | Identifies a SolarWinds binary modifying the start type of a service to be disabled. An adversary may abuse this technique to manipulate relevant security services. | update | 110 
+
+|<<prebuilt-rule-8-11-17-suspicious-zoom-child-process, Suspicious Zoom Child Process>> | A suspicious Zoom child process was detected, which may indicate an attempt to run unnoticed. Verify process details such as command line, network connections, file writes and associated file signature details as well. | update | 212 
+
+|<<prebuilt-rule-8-11-17-untrusted-driver-loaded, Untrusted Driver Loaded>> | Identifies attempt to load an untrusted driver. Adversaries may modify code signing policies to enable execution of unsigned or self-signed code. | update | 9 
+
+|<<prebuilt-rule-8-11-17-adfind-command-activity, AdFind Command Activity>> | This rule detects the Active Directory query tool, AdFind.exe. AdFind has legitimate purposes, but it is frequently leveraged by threat actors to perform post-exploitation Active Directory reconnaissance. The AdFind tool has been observed in Trickbot, Ryuk, Maze, and FIN6 campaigns. For Winlogbeat, this rule requires Sysmon. | update | 112 
+
+|<<prebuilt-rule-8-11-17-enumerating-domain-trusts-via-dsquery-exe, Enumerating Domain Trusts via DSQUERY.EXE>> | Identifies the use of dsquery.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate trust relationships that may be used for Lateral Movement opportunities in Windows multi-domain forest environments. | update | 8 
+
+|<<prebuilt-rule-8-11-17-enumerating-domain-trusts-via-nltest-exe, Enumerating Domain Trusts via NLTEST.EXE>> | Identifies the use of nltest.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate domain trusts and gain insight into trust relationships, as well as the state of Domain Controller (DC) replication in a Microsoft Windows NT Domain. | update | 111 
+
+|<<prebuilt-rule-8-11-17-unusual-parent-process-for-cmd-exe, Unusual Parent Process for cmd.exe>> | Identifies a suspicious parent child process relationship with cmd.exe descending from an unusual process. | update | 212 
+
+|<<prebuilt-rule-8-11-17-delayed-execution-via-ping, Delayed Execution via Ping>> | Identifies the execution of commonly abused Windows utilities via a delayed Ping execution. This behavior is often observed during malware installation and is consistent with an attacker attempting to evade detection. | update | 3 
+
+|<<prebuilt-rule-8-11-17-enumeration-command-spawned-via-wmiprvse, Enumeration Command Spawned via WMIPrvSE>> | Identifies native Windows host and network enumeration commands spawned by the Windows Management Instrumentation Provider Service (WMIPrvSE). | update | 112 
+
+|<<prebuilt-rule-8-11-17-third-party-backup-files-deleted-via-unexpected-process, Third-party Backup Files Deleted via Unexpected Process>> | Identifies the deletion of backup files, saved using third-party software, by a process outside of the backup suite. Adversaries may delete Backup files to ensure that recovery from a ransomware attack is less likely. | update | 113 
+
+|<<prebuilt-rule-8-11-17-deleting-backup-catalogs-with-wbadmin, Deleting Backup Catalogs with Wbadmin>> | Identifies use of the wbadmin.exe to delete the backup catalog. Ransomware and other malware may do this to prevent system recovery. | update | 112 
+
+|<<prebuilt-rule-8-11-17-potential-ransomware-behavior-high-count-of-readme-files-by-system, Potential Ransomware Behavior - High count of Readme files by System>> | This rule identifies a high number (20) of file creation event by the System virtual process from the same host and with same file name containing keywords similar to ransomware note files and all within a short time period. | update | 2 
+
+|<<prebuilt-rule-8-11-17-suspicious-file-renamed-via-smb, Suspicious File Renamed via SMB>> | Identifies an incoming SMB connection followed by a suspicious file rename operation. This may indicate a remote ransomware attack via the SMB protocol. | update | 2 
+
+|<<prebuilt-rule-8-11-17-potential-ransomware-note-file-dropped-via-smb, Potential Ransomware Note File Dropped via SMB>> | Identifies an incoming SMB connection followed by the creation of a file with a name similar to ransomware note files. This may indicate a remote ransomware attack via the SMB protocol. | update | 2 
+
+|<<prebuilt-rule-8-11-17-windows-script-interpreter-executing-process-via-wmi, Windows Script Interpreter Executing Process via WMI>> | Identifies use of the built-in Windows script interpreters (cscript.exe or wscript.exe) being used to execute a process via Windows Management Instrumentation (WMI). This may be indicative of malicious activity. | update | 110 
+
+|<<prebuilt-rule-8-11-17-suspicious-ms-outlook-child-process, Suspicious MS Outlook Child Process>> | Identifies suspicious child processes of Microsoft Outlook. These child processes are often associated with spear phishing activity. | update | 213 
+
+|<<prebuilt-rule-8-11-17-adobe-hijack-persistence, Adobe Hijack Persistence>> | Detects writing executable files that will be automatically launched by Adobe on launch. | update | 213 
+
+|<<prebuilt-rule-8-11-17-registry-persistence-via-appcert-dll, Registry Persistence via AppCert DLL>> | Detects attempts to maintain persistence by creating registry keys using AppCert DLLs. AppCert DLLs are loaded by every process using the common API functions to create processes. | update | 210 
+
+|<<prebuilt-rule-8-11-17-persistence-via-scheduled-job-creation, Persistence via Scheduled Job Creation>> | A job can be used to schedule programs or scripts to be executed at a specified date and time. Adversaries may abuse task scheduling functionality to facilitate initial or recurring execution of malicious code. | update | 210 
+
+|<<prebuilt-rule-8-11-17-uncommon-registry-persistence-change, Uncommon Registry Persistence Change>> | Detects changes to registry persistence keys that are not commonly used or modified by legitimate programs. This could be an indication of an adversary's attempt to persist in a stealthy manner. | update | 108 
+
+|<<prebuilt-rule-8-11-17-account-password-reset-remotely, Account Password Reset Remotely>> | Identifies an attempt to reset a potentially privileged account password remotely. Adversaries may manipulate account passwords to maintain access or evade password duration policies and preserve compromised credentials. | update | 115 
+
+|<<prebuilt-rule-8-11-17-suspicious-service-was-installed-in-the-system, Suspicious Service was Installed in the System>> | Identifies the creation of a new Windows service with suspicious Service command values. Windows services typically run as SYSTEM and can be used for privilege escalation and persistence. | update | 9 
+
+|<<prebuilt-rule-8-11-17-system-shells-via-services, System Shells via Services>> | Windows services typically run as SYSTEM and can be used as a privilege escalation opportunity. Malware or penetration testers may run a shell as a service to gain SYSTEM permissions. | update | 212 
+
+|<<prebuilt-rule-8-11-17-persistence-via-bits-job-notify-cmdline, Persistence via BITS Job Notify Cmdline>> | An adversary can use the Background Intelligent Transfer Service (BITS) SetNotifyCmdLine method to execute a program that runs after a job finishes transferring data or after a job enters a specified state in order to persist on a system. | update | 209 
+
+|<<prebuilt-rule-8-11-17-web-shell-detection-script-process-child-of-common-web-processes, Web Shell Detection: Script Process Child of Common Web Processes>> | Identifies suspicious commands executed via a web server, which may suggest a vulnerability and remote shell access. | update | 213 
+
+|<<prebuilt-rule-8-11-17-disabling-user-account-control-via-registry-modification, Disabling User Account Control via Registry Modification>> | User Account Control (UAC) can help mitigate the impact of malware on Windows hosts. With UAC, apps and tasks always run in the security context of a non-administrator account, unless an administrator specifically authorizes administrator-level access to the system. This rule identifies registry value changes to bypass User Access Control (UAC) protection. | update | 111 
+
+|<<prebuilt-rule-8-11-17-first-time-seen-driver-loaded, First Time Seen Driver Loaded>> | Identifies the load of a driver with an original file name and signature values that were observed for the first time during the last 30 days. This rule type can help baseline drivers installation within your environment. | update | 8 
+
+|<<prebuilt-rule-8-11-17-service-control-spawned-via-script-interpreter, Service Control Spawned via Script Interpreter>> | Identifies Service Control (sc.exe) spawning from script interpreter processes to create, modify, or start services. This can potentially indicate an attempt to elevate privileges or maintain persistence. | update | 109 
+
+|<<prebuilt-rule-8-11-17-uac-bypass-attempt-via-windows-directory-masquerading, UAC Bypass Attempt via Windows Directory Masquerading>> | Identifies an attempt to bypass User Account Control (UAC) by masquerading as a Microsoft trusted Windows directory. Attackers may bypass UAC to stealthily execute code with elevated permissions. | update | 113 
+
+|<<prebuilt-rule-8-11-17-uac-bypass-via-windows-firewall-snap-in-hijack, UAC Bypass via Windows Firewall Snap-In Hijack>> | Identifies attempts to bypass User Account Control (UAC) by hijacking the Microsoft Management Console (MMC) Windows Firewall snap-in. Attackers bypass UAC to stealthily execute code with elevated permissions. | update | 112 
+
+|<<prebuilt-rule-8-11-17-windows-service-installed-via-an-unusual-client, Windows Service Installed via an Unusual Client>> | Identifies the creation of a Windows service by an unusual client process. Services may be created with administrator privileges but are executed under SYSTEM privileges, so an adversary may also use a service to escalate privileges from administrator to SYSTEM. | update | 109 
+
+|==============================================
diff --git a/docs/detections/prebuilt-rules/prebuilt-rules-downloadable-updates.asciidoc b/docs/detections/prebuilt-rules/prebuilt-rules-downloadable-updates.asciidoc
index aaa288f8b4..482fb86879 100644
--- a/docs/detections/prebuilt-rules/prebuilt-rules-downloadable-updates.asciidoc
+++ b/docs/detections/prebuilt-rules/prebuilt-rules-downloadable-updates.asciidoc
@@ -13,6 +13,10 @@ For previous rule updates, please navigate to the https://www.elastic.co/guide/e
 |Update version |Date | New rules | Updated rules | Notes
 
 
+|<<prebuilt-rule-8-11-17-prebuilt-rules-8-11-17-summary, 8.11.17>> | 29 May 2024 | 4 | 123 | 
+This release includes new rules for Linux and AWS integration and tuned rules for Windows ,Linux and MacOS. New rules for Linux include detection for persistence. New rules for AWS include detection for lateral movement, defense evasion and discovery. Additionally, significant rule tuning for Windows ,Linux and MacOS rules has been added for better rule efficacy and performance.
+
+
 |<<prebuilt-rule-8-11-16-prebuilt-rules-8-11-16-summary, 8.11.16>> | 15 May 2024 | 10 | 40 | 
 This release includes new rules for  Windows and AWS integration and tuned rules for Windows and MacOS. New rules for Windows include detection for impact, execution, command and control and defense evasion. New rules for AWS include detection for persistence, defense evasion, exfiltration and credential access. Additionally, significant rule tuning for Windows and MacOS rules has been added for better rule efficacy and performance.
 
@@ -131,3 +135,4 @@ include::downloadable-packages/8-11-13/prebuilt-rules-8-11-13-summary.asciidoc[l
 include::downloadable-packages/8-11-14/prebuilt-rules-8-11-14-summary.asciidoc[leveloffset=+1]
 include::downloadable-packages/8-11-15/prebuilt-rules-8-11-15-summary.asciidoc[leveloffset=+1]
 include::downloadable-packages/8-11-16/prebuilt-rules-8-11-16-summary.asciidoc[leveloffset=+1]
+include::downloadable-packages/8-11-17/prebuilt-rules-8-11-17-summary.asciidoc[leveloffset=+1]
diff --git a/docs/detections/prebuilt-rules/prebuilt-rules-reference.asciidoc b/docs/detections/prebuilt-rules/prebuilt-rules-reference.asciidoc
index 7f7b7efea4..51772f4fe9 100644
--- a/docs/detections/prebuilt-rules/prebuilt-rules-reference.asciidoc
+++ b/docs/detections/prebuilt-rules/prebuilt-rules-reference.asciidoc
@@ -14,187 +14,189 @@ and their rule type is `machine_learning`.
 |Rule |Description |Tags |Added |Version
 
 
-|<<a-scheduled-task-was-created, A scheduled task was created>> |Indicates the creation of a scheduled task using Windows event logs. Adversaries can use these to establish persistence, move laterally, and/or escalate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence] |8.3.0 |8
+|<<a-scheduled-task-was-created, A scheduled task was created>> |Indicates the creation of a scheduled task using Windows event logs. Adversaries can use these to establish persistence, move laterally, and/or escalate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence] |None |8
 
-|<<a-scheduled-task-was-updated, A scheduled task was updated>> |Indicates the update of a scheduled task using Windows event logs. Adversaries can use these to establish persistence, by changing the configuration of a legit scheduled task. Some changes such as disabling or enabling a scheduled task are common and may may generate noise. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence] |8.3.0 |8
+|<<a-scheduled-task-was-updated, A scheduled task was updated>> |Indicates the update of a scheduled task using Windows event logs. Adversaries can use these to establish persistence, by changing the configuration of a legit scheduled task. Some changes such as disabling or enabling a scheduled task are common and may may generate noise. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence] |None |8
 
-|<<aws-cloudtrail-log-created, AWS CloudTrail Log Created>> |Identifies the creation of an AWS log trail that specifies the settings for delivery of log data. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Tactic: Collection] |8.9.0 |207
+|<<aws-cloudtrail-log-created, AWS CloudTrail Log Created>> |Identifies the creation of an AWS log trail that specifies the settings for delivery of log data. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Tactic: Collection] |None |207
 
-|<<aws-cloudtrail-log-deleted, AWS CloudTrail Log Deleted>> |Identifies the deletion of an AWS log trail. An adversary may delete trails in an attempt to evade defenses. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |8.9.0 |209
+|<<aws-cloudtrail-log-deleted, AWS CloudTrail Log Deleted>> |Identifies the deletion of an AWS log trail. An adversary may delete trails in an attempt to evade defenses. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |None |209
 
-|<<aws-cloudtrail-log-suspended, AWS CloudTrail Log Suspended>> |Identifies suspending the recording of AWS API calls and log file delivery for the specified trail. An adversary may suspend trails in an attempt to evade defenses. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |8.9.0 |209
+|<<aws-cloudtrail-log-suspended, AWS CloudTrail Log Suspended>> |Identifies suspending the recording of AWS API calls and log file delivery for the specified trail. An adversary may suspend trails in an attempt to evade defenses. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |None |209
 
-|<<aws-cloudtrail-log-updated, AWS CloudTrail Log Updated>> |Identifies an update to an AWS log trail setting that specifies the delivery of log files. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Cloudtrail], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Impact] |8.9.0 |209
+|<<aws-cloudtrail-log-updated, AWS CloudTrail Log Updated>> |Identifies an update to an AWS log trail setting that specifies the delivery of log files. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Cloudtrail], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Impact] |None |209
 
-|<<aws-cloudwatch-alarm-deletion, AWS CloudWatch Alarm Deletion>> |Identifies the deletion of an AWS CloudWatch alarm. An adversary may delete alarms in an attempt to evade defenses. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Resources: Investigation Guide], [Tactic: Defense Evasion] |8.9.0 |209
+|<<aws-cloudwatch-alarm-deletion, AWS CloudWatch Alarm Deletion>> |Identifies the deletion of an AWS CloudWatch alarm. An adversary may delete alarms in an attempt to evade defenses. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Resources: Investigation Guide], [Tactic: Defense Evasion] |None |209
 
-|<<aws-cloudwatch-log-group-deletion, AWS CloudWatch Log Group Deletion>> |Identifies the deletion of a specified AWS CloudWatch log group. When a log group is deleted, all the archived log events associated with the log group are also permanently deleted. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS CloudWatch], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Impact] |8.9.0 |209
+|<<aws-cloudwatch-log-group-deletion, AWS CloudWatch Log Group Deletion>> |Identifies the deletion of a specified AWS CloudWatch log group. When a log group is deleted, all the archived log events associated with the log group are also permanently deleted. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS CloudWatch], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Impact] |None |209
 
-|<<aws-cloudwatch-log-stream-deletion, AWS CloudWatch Log Stream Deletion>> |Identifies the deletion of an AWS CloudWatch log stream, which permanently deletes all associated archived log events with the stream. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS CloudWatch], [Use Case: Log Auditing], [Tactic: Impact], [Resources: Investigation Guide] |8.9.0 |209
+|<<aws-cloudwatch-log-stream-deletion, AWS CloudWatch Log Stream Deletion>> |Identifies the deletion of an AWS CloudWatch log stream, which permanently deletes all associated archived log events with the stream. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS CloudWatch], [Use Case: Log Auditing], [Tactic: Impact], [Resources: Investigation Guide] |None |209
 
-|<<aws-config-resource-deletion, AWS Config Resource Deletion>> |Identifies attempts to delete an AWS Config Service resource. An adversary may tamper with Config services in order to reduce visibility into the security posture of an account and / or its workload instances. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Resources: Investigation Guide], [Tactic: Defense Evasion] |8.9.0 |209
+|<<aws-config-resource-deletion, AWS Config Resource Deletion>> |Identifies attempts to delete an AWS Config Service resource. An adversary may tamper with Config services in order to reduce visibility into the security posture of an account and / or its workload instances. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Resources: Investigation Guide], [Tactic: Defense Evasion] |None |209
 
-|<<aws-configuration-recorder-stopped, AWS Configuration Recorder Stopped>> |Identifies an AWS configuration change to stop recording a designated set of resources. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |8.9.0 |206
+|<<aws-configuration-recorder-stopped, AWS Configuration Recorder Stopped>> |Identifies an AWS configuration change to stop recording a designated set of resources. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |None |206
 
-|<<aws-credentials-searched-for-inside-a-container, AWS Credentials Searched For Inside A Container>> |This rule detects the use of system search utilities like grep and find to search for AWS credentials inside a container. Unauthorized access to these sensitive files could lead to further compromise of the container environment or facilitate a container breakout to the underlying cloud environment. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |8.8.0 |1
+|<<aws-credentials-searched-for-inside-a-container, AWS Credentials Searched For Inside A Container>> |This rule detects the use of system search utilities like grep and find to search for AWS credentials inside a container. Unauthorized access to these sensitive files could lead to further compromise of the container environment or facilitate a container breakout to the underlying cloud environment. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |None |1
 
-|<<aws-deletion-of-rds-instance-or-cluster, AWS Deletion of RDS Instance or Cluster>> |Identifies the deletion of an Amazon Relational Database Service (RDS) Aurora database cluster, global database cluster, or database instance. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Impact] |8.9.0 |206
+|<<aws-deletion-of-rds-instance-or-cluster, AWS Deletion of RDS Instance or Cluster>> |Identifies the deletion of an Amazon Relational Database Service (RDS) Aurora database cluster, global database cluster, or database instance. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Impact] |None |206
 
-|<<aws-ec2-admin-credential-fetch-via-assumed-role, AWS EC2 Admin Credential Fetch via Assumed Role>> |Identifies the first occurrence of a user identity in AWS using `GetPassword` for the administrator password of an EC2 instance with an assumed role. Adversaries may use this API call to escalate privileges or move laterally within EC2 instances. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon EC2], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Credential Access] |8.3.0 |2
+|<<aws-ec2-admin-credential-fetch-via-assumed-role, AWS EC2 Admin Credential Fetch via Assumed Role>> |Identifies the first occurrence of a user identity in AWS using `GetPassword` for the administrator password of an EC2 instance with an assumed role. Adversaries may use this API call to escalate privileges or move laterally within EC2 instances. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon EC2], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Credential Access] |None |3
 
-|<<aws-ec2-encryption-disabled, AWS EC2 Encryption Disabled>> |Identifies disabling of Amazon Elastic Block Store (EBS) encryption by default in the current region. Disabling encryption by default does not change the encryption status of your existing volumes. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Tactic: Impact] |8.9.0 |206
+|<<aws-ec2-encryption-disabled, AWS EC2 Encryption Disabled>> |Identifies disabling of Amazon Elastic Block Store (EBS) encryption by default in the current region. Disabling encryption by default does not change the encryption status of your existing volumes. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Tactic: Impact] |None |206
 
-|<<aws-ec2-full-network-packet-capture-detected, AWS EC2 Full Network Packet Capture Detected>> |Identifies potential Traffic Mirroring in an Amazon Elastic Compute Cloud (EC2) instance. Traffic Mirroring is an Amazon VPC feature that you can use to copy network traffic from an Elastic network interface. This feature can potentially be abused to exfiltrate sensitive data from unencrypted internal traffic. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Exfiltration], [Tactic: Collection] |8.9.0 |206
+|<<aws-ec2-full-network-packet-capture-detected, AWS EC2 Full Network Packet Capture Detected>> |Identifies potential Traffic Mirroring in an Amazon Elastic Compute Cloud (EC2) instance. Traffic Mirroring is an Amazon VPC feature that you can use to copy network traffic from an Elastic network interface. This feature can potentially be abused to exfiltrate sensitive data from unencrypted internal traffic. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Exfiltration], [Tactic: Collection] |None |206
 
-|<<aws-ec2-network-access-control-list-creation, AWS EC2 Network Access Control List Creation>> |Identifies the creation of an AWS Elastic Compute Cloud (EC2) network access control list (ACL) or an entry in a network ACL with a specified rule number. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Network Security Monitoring], [Tactic: Persistence] |8.9.0 |206
+|<<aws-ec2-network-access-control-list-creation, AWS EC2 Network Access Control List Creation>> |Identifies the creation of an AWS Elastic Compute Cloud (EC2) network access control list (ACL) or an entry in a network ACL with a specified rule number. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Network Security Monitoring], [Tactic: Persistence] |None |206
 
-|<<aws-ec2-network-access-control-list-deletion, AWS EC2 Network Access Control List Deletion>> |Identifies the deletion of an Amazon Elastic Compute Cloud (EC2) network access control list (ACL) or one of its ingress/egress entries. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |8.9.0 |206
+|<<aws-ec2-network-access-control-list-deletion, AWS EC2 Network Access Control List Deletion>> |Identifies the deletion of an Amazon Elastic Compute Cloud (EC2) network access control list (ACL) or one of its ingress/egress entries. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |None |206
 
-|<<aws-ec2-snapshot-activity, AWS EC2 Snapshot Activity>> |An attempt was made to modify AWS EC2 snapshot attributes. Snapshots are sometimes shared by threat actors in order to exfiltrate bulk data from an EC2 fleet. If the permissions were modified, verify the snapshot was not shared with an unauthorized or unexpected AWS account. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Exfiltration], [Resources: Investigation Guide] |8.9.0 |209
+|<<aws-ec2-snapshot-activity, AWS EC2 Snapshot Activity>> |An attempt was made to modify AWS EC2 snapshot attributes. Snapshots are sometimes shared by threat actors in order to exfiltrate bulk data from an EC2 fleet. If the permissions were modified, verify the snapshot was not shared with an unauthorized or unexpected AWS account. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Exfiltration], [Resources: Investigation Guide] |None |209
 
-|<<aws-ec2-vm-export-failure, AWS EC2 VM Export Failure>> |Identifies an attempt to export an AWS EC2 instance. A virtual machine (VM) export may indicate an attempt to extract or exfiltrate information. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Exfiltration], [Tactic: Collection] |8.9.0 |206
+|<<aws-ec2-vm-export-failure, AWS EC2 VM Export Failure>> |Identifies an attempt to export an AWS EC2 instance. A virtual machine (VM) export may indicate an attempt to extract or exfiltrate information. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Exfiltration], [Tactic: Collection] |None |206
 
-|<<aws-efs-file-system-or-mount-deleted, AWS EFS File System or Mount Deleted>> |Detects when an EFS File System or Mount is deleted. An adversary could break any file system using the mount target that is being deleted, which might disrupt instances or applications using those mounts. The mount must be deleted prior to deleting the File System, or the adversary will be unable to delete the File System. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Impact] |8.9.0 |206
+|<<aws-efs-file-system-or-mount-deleted, AWS EFS File System or Mount Deleted>> |Detects when an EFS File System or Mount is deleted. An adversary could break any file system using the mount target that is being deleted, which might disrupt instances or applications using those mounts. The mount must be deleted prior to deleting the File System, or the adversary will be unable to delete the File System. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Impact] |None |206
 
-|<<aws-elasticache-security-group-created, AWS ElastiCache Security Group Created>> |Identifies when an ElastiCache security group has been created. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |8.9.0 |206
+|<<aws-elasticache-security-group-created, AWS ElastiCache Security Group Created>> |Identifies when an ElastiCache security group has been created. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |None |206
 
-|<<aws-elasticache-security-group-modified-or-deleted, AWS ElastiCache Security Group Modified or Deleted>> |Identifies when an ElastiCache security group has been modified or deleted. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |8.9.0 |206
+|<<aws-elasticache-security-group-modified-or-deleted, AWS ElastiCache Security Group Modified or Deleted>> |Identifies when an ElastiCache security group has been modified or deleted. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |None |206
 
-|<<aws-eventbridge-rule-disabled-or-deleted, AWS EventBridge Rule Disabled or Deleted>> |Identifies when a user has disabled or deleted an EventBridge rule. This activity can result in an unintended loss of visibility in applications or a break in the flow with other AWS services. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Impact] |8.9.0 |206
+|<<aws-eventbridge-rule-disabled-or-deleted, AWS EventBridge Rule Disabled or Deleted>> |Identifies when a user has disabled or deleted an EventBridge rule. This activity can result in an unintended loss of visibility in applications or a break in the flow with other AWS services. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Impact] |None |206
 
-|<<aws-execution-via-system-manager, AWS Execution via System Manager>> |Identifies the execution of commands and scripts via System Manager. Execution methods such as RunShellScript, RunPowerShellScript, and alike can be abused by an authenticated attacker to install a backdoor or to interact with a compromised instance via reverse-shell using system only commands. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS SSM], [Use Case: Log Auditing], [Tactic: Initial Access], [Resources: Investigation Guide] |8.9.0 |209
+|<<aws-execution-via-system-manager, AWS Execution via System Manager>> |Identifies the execution of commands and scripts via System Manager. Execution methods such as RunShellScript, RunPowerShellScript, and alike can be abused by an authenticated attacker to install a backdoor or to interact with a compromised instance via reverse-shell using system only commands. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS SSM], [Use Case: Log Auditing], [Tactic: Initial Access], [Resources: Investigation Guide] |None |209
 
-|<<aws-guardduty-detector-deletion, AWS GuardDuty Detector Deletion>> |Identifies the deletion of an Amazon GuardDuty detector. Upon deletion, GuardDuty stops monitoring the environment and all existing findings are lost. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |8.9.0 |206
+|<<aws-guardduty-detector-deletion, AWS GuardDuty Detector Deletion>> |Identifies the deletion of an Amazon GuardDuty detector. Upon deletion, GuardDuty stops monitoring the environment and all existing findings are lost. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Defense Evasion] |None |206
 
-|<<aws-iam-assume-role-policy-update, AWS IAM Assume Role Policy Update>> |Identifies attempts to modify an AWS IAM Assume Role Policy. An adversary may attempt to modify the AssumeRolePolicy of a misconfigured role in order to gain the privileges of that role. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Privilege Escalation] |8.9.0 |209
+|<<aws-iam-assume-role-policy-update, AWS IAM Assume Role Policy Update>> |Identifies attempts to modify an AWS IAM Assume Role Policy. An adversary may attempt to modify the AssumeRolePolicy of a misconfigured role in order to gain the privileges of that role. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Privilege Escalation] |None |209
 
-|<<aws-iam-brute-force-of-assume-role-policy, AWS IAM Brute Force of Assume Role Policy>> |Identifies a high number of failed attempts to assume an AWS Identity and Access Management (IAM) role. IAM roles are used to delegate access to users or services. An adversary may attempt to enumerate IAM roles in order to determine if a role exists before attempting to assume or hijack the discovered role. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Credential Access] |8.9.0 |210
+|<<aws-iam-brute-force-of-assume-role-policy, AWS IAM Brute Force of Assume Role Policy>> |Identifies a high number of failed attempts to assume an AWS Identity and Access Management (IAM) role. IAM roles are used to delegate access to users or services. An adversary may attempt to enumerate IAM roles in order to determine if a role exists before attempting to assume or hijack the discovered role. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Credential Access] |None |210
 
-|<<aws-iam-deactivation-of-mfa-device, AWS IAM Deactivation of MFA Device>> |Identifies the deactivation of a specified multi-factor authentication (MFA) device and removes it from association with the user name for which it was originally enabled. In AWS Identity and Access Management (IAM), a device must be deactivated before it can be deleted. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Resources: Investigation Guide], [Tactic: Impact] |8.9.0 |209
+|<<aws-iam-deactivation-of-mfa-device, AWS IAM Deactivation of MFA Device>> |Identifies the deactivation of a specified multi-factor authentication (MFA) device and removes it from association with the user name for which it was originally enabled. In AWS Identity and Access Management (IAM), a device must be deactivated before it can be deleted. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Resources: Investigation Guide], [Tactic: Impact] |None |209
 
-|<<aws-iam-group-creation, AWS IAM Group Creation>> |Identifies the creation of a group in AWS Identity and Access Management (IAM). Groups specify permissions for multiple users. Any user in a group automatically has the permissions that are assigned to the group. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.9.0 |206
+|<<aws-iam-group-creation, AWS IAM Group Creation>> |Identifies the creation of a group in AWS Identity and Access Management (IAM). Groups specify permissions for multiple users. Any user in a group automatically has the permissions that are assigned to the group. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Persistence] |None |206
 
-|<<aws-iam-group-deletion, AWS IAM Group Deletion>> |Identifies the deletion of a specified AWS Identity and Access Management (IAM) resource group. Deleting a resource group does not delete resources that are members of the group; it only deletes the group structure. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Tactic: Impact] |8.9.0 |206
+|<<aws-iam-group-deletion, AWS IAM Group Deletion>> |Identifies the deletion of a specified AWS Identity and Access Management (IAM) resource group. Deleting a resource group does not delete resources that are members of the group; it only deletes the group structure. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Tactic: Impact] |None |206
 
-|<<aws-iam-login-profile-added-to-user, AWS IAM Login Profile Added to User>> |Identifies when an AWS IAM login profile is added to a user. Adversaries may add a login profile to an IAM user who typically does not have one and is used only for programmatic access. This can be used to maintain access to the account even if the original access key is rotated or disabled. This is a building block rule and does not generate alerts on its own. It is meant to be used for correlation with other rules to detect suspicious activity. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Rule Type: BBR] |8.9.0 |1
+|<<aws-iam-login-profile-added-to-user, AWS IAM Login Profile Added to User>> |Identifies when an AWS IAM login profile is added to a user. Adversaries may add a login profile to an IAM user who typically does not have one and is used only for programmatic access. This can be used to maintain access to the account even if the original access key is rotated or disabled. This is a building block rule and does not generate alerts on its own. It is meant to be used for correlation with other rules to detect suspicious activity. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS IAM], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Rule Type: BBR] |None |2
 
-|<<aws-iam-password-recovery-requested, AWS IAM Password Recovery Requested>> |Identifies AWS IAM password recovery requests. An adversary may attempt to gain unauthorized AWS access by abusing password recovery mechanisms. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Signin], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |8.9.0 |206
+|<<aws-iam-password-recovery-requested, AWS IAM Password Recovery Requested>> |Identifies AWS IAM password recovery requests. An adversary may attempt to gain unauthorized AWS access by abusing password recovery mechanisms. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Signin], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |None |206
 
-|<<aws-iam-user-addition-to-group, AWS IAM User Addition to Group>> |Identifies the addition of a user to a specified group in AWS Identity and Access Management (IAM). |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Tactic: Credential Access], [Tactic: Persistence], [Resources: Investigation Guide] |8.9.0 |209
+|<<aws-iam-user-addition-to-group, AWS IAM User Addition to Group>> |Identifies the addition of a user to a specified group in AWS Identity and Access Management (IAM). |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Tactic: Credential Access], [Tactic: Persistence], [Resources: Investigation Guide] |None |209
 
-|<<aws-kms-customer-managed-key-disabled-or-scheduled-for-deletion, AWS KMS Customer Managed Key Disabled or Scheduled for Deletion>> |Identifies attempts to disable or schedule the deletion of an AWS KMS Customer Managed Key (CMK). Deleting an AWS KMS key is destructive and potentially dangerous. It deletes the key material and all metadata associated with the KMS key and is irreversible. After a KMS key is deleted, the data that was encrypted under that KMS key can no longer be decrypted, which means that data becomes unrecoverable. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS KMS], [Use Case: Log Auditing], [Tactic: Impact] |8.9.0 |106
+|<<aws-kms-customer-managed-key-disabled-or-scheduled-for-deletion, AWS KMS Customer Managed Key Disabled or Scheduled for Deletion>> |Identifies attempts to disable or schedule the deletion of an AWS KMS Customer Managed Key (CMK). Deleting an AWS KMS key is destructive and potentially dangerous. It deletes the key material and all metadata associated with the KMS key and is irreversible. After a KMS key is deleted, the data that was encrypted under that KMS key can no longer be decrypted, which means that data becomes unrecoverable. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS KMS], [Use Case: Log Auditing], [Tactic: Impact] |None |106
 
-|<<aws-management-console-brute-force-of-root-user-identity, AWS Management Console Brute Force of Root User Identity>> |Identifies a high number of failed authentication attempts to the AWS management console for the Root user identity. An adversary may attempt to brute force the password for the Root user identity, as it has complete access to all services and resources for the AWS account. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |8.9.0 |207
+|<<aws-management-console-brute-force-of-root-user-identity, AWS Management Console Brute Force of Root User Identity>> |Identifies a high number of failed authentication attempts to the AWS management console for the Root user identity. An adversary may attempt to brute force the password for the Root user identity, as it has complete access to all services and resources for the AWS account. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |None |207
 
-|<<aws-management-console-root-login, AWS Management Console Root Login>> |Identifies a successful login to the AWS Management Console by the Root user. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Signin], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |8.9.0 |209
+|<<aws-management-console-root-login, AWS Management Console Root Login>> |Identifies a successful login to the AWS Management Console by the Root user. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Signin], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |None |209
 
-|<<aws-rds-cluster-creation, AWS RDS Cluster Creation>> |Identifies the creation of a new Amazon Relational Database Service (RDS) Aurora DB cluster or global database spread across multiple regions. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Persistence] |8.9.0 |206
+|<<aws-rds-cluster-creation, AWS RDS Cluster Creation>> |Identifies the creation of a new Amazon Relational Database Service (RDS) Aurora DB cluster or global database spread across multiple regions. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Persistence] |None |206
 
-|<<aws-rds-instance-creation, AWS RDS Instance Creation>> |Identifies the creation of an Amazon Relational Database Service (RDS) Aurora database instance. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Persistence] |8.9.0 |206
+|<<aws-rds-instance-creation, AWS RDS Instance Creation>> |Identifies the creation of an Amazon Relational Database Service (RDS) Aurora database instance. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Persistence] |None |206
 
-|<<aws-rds-instance-cluster-stoppage, AWS RDS Instance/Cluster Stoppage>> |Identifies that an Amazon Relational Database Service (RDS) cluster or instance has been stopped. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Impact] |8.9.0 |206
+|<<aws-rds-instance-cluster-stoppage, AWS RDS Instance/Cluster Stoppage>> |Identifies that an Amazon Relational Database Service (RDS) cluster or instance has been stopped. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Use Case: Asset Visibility], [Tactic: Impact] |None |206
 
-|<<aws-rds-security-group-creation, AWS RDS Security Group Creation>> |Identifies the creation of an Amazon Relational Database Service (RDS) Security group. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Tactic: Persistence] |8.9.0 |206
+|<<aws-rds-security-group-creation, AWS RDS Security Group Creation>> |Identifies the creation of an Amazon Relational Database Service (RDS) Security group. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Tactic: Persistence] |None |206
 
-|<<aws-rds-security-group-deletion, AWS RDS Security Group Deletion>> |Identifies the deletion of an Amazon Relational Database Service (RDS) Security group. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Tactic: Impact] |8.9.0 |206
+|<<aws-rds-security-group-deletion, AWS RDS Security Group Deletion>> |Identifies the deletion of an Amazon Relational Database Service (RDS) Security group. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS RDS], [Tactic: Impact] |None |206
 
-|<<aws-rds-snapshot-export, AWS RDS Snapshot Export>> |Identifies the export of an Amazon Relational Database Service (RDS) Aurora database snapshot. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Exfiltration] |8.9.0 |206
+|<<aws-rds-snapshot-export, AWS RDS Snapshot Export>> |Identifies the export of an Amazon Relational Database Service (RDS) Aurora database snapshot. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Exfiltration] |None |206
 
-|<<aws-rds-snapshot-restored, AWS RDS Snapshot Restored>> |Identifies when an attempt was made to restore an RDS Snapshot. Snapshots are sometimes shared by threat actors in order to exfiltrate bulk data or evade detection after performing malicious activities. If the permissions were modified, verify if the snapshot was shared with an unauthorized or unexpected AWS account. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Defense Evasion] |8.9.0 |206
+|<<aws-rds-snapshot-restored, AWS RDS Snapshot Restored>> |Identifies when an attempt was made to restore an RDS Snapshot. Snapshots are sometimes shared by threat actors in order to exfiltrate bulk data or evade detection after performing malicious activities. If the permissions were modified, verify if the snapshot was shared with an unauthorized or unexpected AWS account. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Defense Evasion] |None |206
 
-|<<aws-redshift-cluster-creation, AWS Redshift Cluster Creation>> |Identifies the creation of an Amazon Redshift cluster. Unexpected creation of this cluster by a non-administrative user may indicate a permission or role issue with current users. If unexpected, the resource may not properly be configured and could introduce security vulnerabilities. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Redshift], [Use Case: Asset Visibility], [Tactic: Persistence] |8.9.0 |206
+|<<aws-redshift-cluster-creation, AWS Redshift Cluster Creation>> |Identifies the creation of an Amazon Redshift cluster. Unexpected creation of this cluster by a non-administrative user may indicate a permission or role issue with current users. If unexpected, the resource may not properly be configured and could introduce security vulnerabilities. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Redshift], [Use Case: Asset Visibility], [Tactic: Persistence] |None |206
 
-|<<aws-root-login-without-mfa, AWS Root Login Without MFA>> |Identifies attempts to login to AWS as the root user without using multi-factor authentication (MFA). Amazon AWS best practices indicate that the root user should be protected by MFA. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Privilege Escalation] |8.9.0 |209
+|<<aws-root-login-without-mfa, AWS Root Login Without MFA>> |Identifies attempts to login to AWS as the root user without using multi-factor authentication (MFA). Amazon AWS best practices indicate that the root user should be protected by MFA. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Privilege Escalation] |None |209
 
-|<<aws-route-53-domain-transfer-lock-disabled, AWS Route 53 Domain Transfer Lock Disabled>> |Identifies when a transfer lock was removed from a Route 53 domain. It is recommended to refrain from performing this action unless intending to transfer the domain to a different registrar. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Asset Visibility], [Tactic: Persistence] |8.9.0 |206
+|<<aws-route-53-domain-transfer-lock-disabled, AWS Route 53 Domain Transfer Lock Disabled>> |Identifies when a transfer lock was removed from a Route 53 domain. It is recommended to refrain from performing this action unless intending to transfer the domain to a different registrar. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Asset Visibility], [Tactic: Persistence] |None |206
 
-|<<aws-route-53-domain-transferred-to-another-account, AWS Route 53 Domain Transferred to Another Account>> |Identifies when a request has been made to transfer a Route 53 domain to another AWS account. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Asset Visibility], [Tactic: Persistence] |8.9.0 |206
+|<<aws-route-53-domain-transferred-to-another-account, AWS Route 53 Domain Transferred to Another Account>> |Identifies when a request has been made to transfer a Route 53 domain to another AWS account. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Asset Visibility], [Tactic: Persistence] |None |206
 
-|<<aws-route-table-created, AWS Route Table Created>> |Identifies when an AWS Route Table has been created. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Network Security Monitoring], [Tactic: Persistence] |8.9.0 |207
+|<<aws-route-table-created, AWS Route Table Created>> |Identifies when an AWS Route Table has been created. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Network Security Monitoring], [Tactic: Persistence] |None |207
 
-|<<aws-route-table-modified-or-deleted, AWS Route Table Modified or Deleted>> |Identifies when an AWS Route Table has been modified or deleted. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Network Security Monitoring], [Tactic: Persistence] |8.9.0 |207
+|<<aws-route-table-modified-or-deleted, AWS Route Table Modified or Deleted>> |Identifies when an AWS Route Table has been modified or deleted. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Network Security Monitoring], [Tactic: Persistence] |None |207
 
-|<<aws-route53-private-hosted-zone-associated-with-a-vpc, AWS Route53 private hosted zone associated with a VPC>> |Identifies when a Route53 private hosted zone has been associated with VPC. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Asset Visibility], [Tactic: Persistence] |8.9.0 |206
+|<<aws-route53-private-hosted-zone-associated-with-a-vpc, AWS Route53 private hosted zone associated with a VPC>> |Identifies when a Route53 private hosted zone has been associated with VPC. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS Route53], [Use Case: Asset Visibility], [Tactic: Persistence] |None |206
 
-|<<aws-s3-bucket-configuration-deletion, AWS S3 Bucket Configuration Deletion>> |Identifies the deletion of various Amazon Simple Storage Service (S3) bucket configuration components. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Defense Evasion] |8.9.0 |207
+|<<aws-s3-bucket-configuration-deletion, AWS S3 Bucket Configuration Deletion>> |Identifies the deletion of various Amazon Simple Storage Service (S3) bucket configuration components. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Asset Visibility], [Tactic: Defense Evasion] |None |207
 
-|<<aws-saml-activity, AWS SAML Activity>> |Identifies when SAML activity has occurred in AWS. An adversary could manipulate SAML to maintain access to the target. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |8.9.0 |206
+|<<aws-s3-bucket-expiration-lifecycle-configuration-added, AWS S3 Bucket Expiration Lifecycle Configuration Added>> |Identifies an expiration lifecycle configuration added to an S3 bucket. Lifecycle configurations can be used to manage objects in a bucket, including setting expiration policies. This rule detects when a lifecycle configuration is added to an S3 bucket, which could indicate that objects in the bucket will be automatically deleted after a specified period of time. This could be used to evade detection by deleting objects that contain evidence of malicious activity. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon S3], [Use Case: Asset Visibility], [Tactic: Defense Evasion] |8.9.0 |1
 
-|<<aws-sts-getsessiontoken-abuse, AWS STS GetSessionToken Abuse>> |Identifies the suspicious use of GetSessionToken. Tokens could be created and used by attackers to move laterally and escalate privileges. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |8.9.0 |206
+|<<aws-saml-activity, AWS SAML Activity>> |Identifies when SAML activity has occurred in AWS. An adversary could manipulate SAML to maintain access to the target. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |None |206
 
-|<<aws-security-group-configuration-change-detection, AWS Security Group Configuration Change Detection>> |Identifies a change to an AWS Security Group Configuration. A security group is like a virtual firewall, and modifying configurations may allow unauthorized access. Threat actors may abuse this to establish persistence, exfiltrate data, or pivot in an AWS environment. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Network Security Monitoring], [Tactic: Persistence] |8.9.0 |206
+|<<aws-sts-getsessiontoken-abuse, AWS STS GetSessionToken Abuse>> |Identifies the suspicious use of GetSessionToken. Tokens could be created and used by attackers to move laterally and escalate privileges. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |None |206
 
-|<<aws-security-token-service-sts-assumerole-usage, AWS Security Token Service (STS) AssumeRole Usage>> |Identifies the use of AssumeRole. AssumeRole returns a set of temporary security credentials that can be used to access AWS resources. An adversary could use those credentials to move laterally and escalate privileges. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |8.9.0 |206
+|<<aws-security-group-configuration-change-detection, AWS Security Group Configuration Change Detection>> |Identifies a change to an AWS Security Group Configuration. A security group is like a virtual firewall, and modifying configurations may allow unauthorized access. Threat actors may abuse this to establish persistence, exfiltrate data, or pivot in an AWS environment. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Network Security Monitoring], [Tactic: Persistence] |None |206
 
-|<<aws-vpc-flow-logs-deletion, AWS VPC Flow Logs Deletion>> |Identifies the deletion of one or more flow logs in AWS Elastic Compute Cloud (EC2). An adversary may delete flow logs in an attempt to evade defenses. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |8.9.0 |209
+|<<aws-security-token-service-sts-assumerole-usage, AWS Security Token Service (STS) AssumeRole Usage>> |Identifies the use of AssumeRole. AssumeRole returns a set of temporary security credentials that can be used to access AWS resources. An adversary could use those credentials to move laterally and escalate privileges. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS STS], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |None |206
 
-|<<aws-waf-access-control-list-deletion, AWS WAF Access Control List Deletion>> |Identifies the deletion of a specified AWS Web Application Firewall (WAF) access control list. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |8.9.0 |206
+|<<aws-vpc-flow-logs-deletion, AWS VPC Flow Logs Deletion>> |Identifies the deletion of one or more flow logs in AWS Elastic Compute Cloud (EC2). An adversary may delete flow logs in an attempt to evade defenses. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |None |209
 
-|<<aws-waf-rule-or-rule-group-deletion, AWS WAF Rule or Rule Group Deletion>> |Identifies the deletion of a specified AWS Web Application Firewall (WAF) rule or rule group. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |8.9.0 |206
+|<<aws-waf-access-control-list-deletion, AWS WAF Access Control List Deletion>> |Identifies the deletion of a specified AWS Web Application Firewall (WAF) access control list. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |None |206
 
-|<<abnormal-process-id-or-lock-file-created, Abnormal Process ID or Lock File Created>> |Identifies the creation of a Process ID (PID), lock or reboot file created in temporary file storage paradigm (tmpfs) directory /var/run. On Linux, the PID files typically hold the process ID to track previous copies running and manage other tasks. Certain Linux malware use the /var/run directory for holding data, executables and other tasks, disguising itself or these files as legitimate PID files. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: BPFDoor], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.6.0 |213
+|<<aws-waf-rule-or-rule-group-deletion, AWS WAF Rule or Rule Group Deletion>> |Identifies the deletion of a specified AWS Web Application Firewall (WAF) rule or rule group. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |None |206
 
-|<<abnormally-large-dns-response, Abnormally Large DNS Response>> |Specially crafted DNS requests can manipulate a known overflow vulnerability in some Windows DNS servers, resulting in Remote Code Execution (RCE) or a Denial of Service (DoS) from crashing the service. |[Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Use Case: Vulnerability] |8.3.0 |105
+|<<abnormal-process-id-or-lock-file-created, Abnormal Process ID or Lock File Created>> |Identifies the creation of a Process ID (PID), lock or reboot file created in temporary file storage paradigm (tmpfs) directory /var/run. On Linux, the PID files typically hold the process ID to track previous copies running and manage other tasks. Certain Linux malware use the /var/run directory for holding data, executables and other tasks, disguising itself or these files as legitimate PID files. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: BPFDoor], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |213
 
-|<<accepted-default-telnet-port-connection, Accepted Default Telnet Port Connection>> |This rule detects network events that may indicate the use of Telnet traffic. Telnet is commonly used by system administrators to remotely control older or embedded systems using the command line shell. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. As a plain-text protocol, it may also expose usernames and passwords to anyone capable of observing the traffic. |[Domain: Endpoint], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Lateral Movement], [Tactic: Initial Access] |8.3.0 |104
+|<<abnormally-large-dns-response, Abnormally Large DNS Response>> |Specially crafted DNS requests can manipulate a known overflow vulnerability in some Windows DNS servers, resulting in Remote Code Execution (RCE) or a Denial of Service (DoS) from crashing the service. |[Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Use Case: Vulnerability] |None |105
 
-|<<access-to-keychain-credentials-directories, Access to Keychain Credentials Directories>> |Adversaries may collect the keychain storage data from a system to acquire credentials. Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features such as WiFi passwords, websites, secure notes and certificates. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.7.0 |207
+|<<accepted-default-telnet-port-connection, Accepted Default Telnet Port Connection>> |This rule detects network events that may indicate the use of Telnet traffic. Telnet is commonly used by system administrators to remotely control older or embedded systems using the command line shell. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. As a plain-text protocol, it may also expose usernames and passwords to anyone capable of observing the traffic. |[Domain: Endpoint], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Lateral Movement], [Tactic: Initial Access] |None |104
 
-|<<access-to-a-sensitive-ldap-attribute, Access to a Sensitive LDAP Attribute>> |Identify access to sensitive Active Directory object attributes that contains credentials and decryption keys such as unixUserPassword, ms-PKI-AccountCredentials and msPKI-CredentialRoamingTokens. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |8.3.0 |10
+|<<access-to-keychain-credentials-directories, Access to Keychain Credentials Directories>> |Adversaries may collect the keychain storage data from a system to acquire credentials. Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features such as WiFi passwords, websites, secure notes and certificates. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |207
 
-|<<accessing-outlook-data-files, Accessing Outlook Data Files>> |Identifies commands containing references to Outlook data files extensions, which can potentially indicate the search, access, or modification of these files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |2
+|<<access-to-a-sensitive-ldap-attribute, Access to a Sensitive LDAP Attribute>> |Identify access to sensitive Active Directory object attributes that contains credentials and decryption keys such as unixUserPassword, ms-PKI-AccountCredentials and msPKI-CredentialRoamingTokens. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |None |10
 
-|<<account-configured-with-never-expiring-password, Account Configured with Never-Expiring Password>> |Detects the creation and modification of an account with the "Don't Expire Password" option Enabled. Attackers can abuse this misconfiguration to persist in the domain and maintain long-term access using compromised accounts with this property. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |8.3.0 |108
+|<<accessing-outlook-data-files, Accessing Outlook Data Files>> |Identifies commands containing references to Outlook data files extensions, which can potentially indicate the search, access, or modification of these files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Rule Type: BBR] |None |2
 
-|<<account-discovery-command-via-system-account, Account Discovery Command via SYSTEM Account>> |Identifies when the SYSTEM account uses an account discovery utility. This could be a sign of discovery activity after an adversary has achieved privilege escalation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<account-configured-with-never-expiring-password, Account Configured with Never-Expiring Password>> |Detects the creation and modification of an account with the "Don't Expire Password" option Enabled. Attackers can abuse this misconfiguration to persist in the domain and maintain long-term access using compromised accounts with this property. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |None |108
 
-|<<account-password-reset-remotely, Account Password Reset Remotely>> |Identifies an attempt to reset a potentially privileged account password remotely. Adversaries may manipulate account passwords to maintain access or evade password duration policies and preserve compromised credentials. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Impact] |8.3.0 |114
+|<<account-discovery-command-via-system-account, Account Discovery Command via SYSTEM Account>> |Identifies when the SYSTEM account uses an account discovery utility. This could be a sign of discovery activity after an adversary has achieved privilege escalation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<account-or-group-discovery-via-built-in-tools, Account or Group Discovery via Built-In Tools>> |Adversaries may use built-in applications to get a listing of local system or domain accounts and groups. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |3
+|<<account-password-reset-remotely, Account Password Reset Remotely>> |Identifies an attempt to reset a potentially privileged account password remotely. Adversaries may manipulate account passwords to maintain access or evade password duration policies and preserve compromised credentials. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Impact] |None |115
 
-|<<adfind-command-activity, AdFind Command Activity>> |This rule detects the Active Directory query tool, AdFind.exe. AdFind has legitimate purposes, but it is frequently leveraged by threat actors to perform post-exploitation Active Directory reconnaissance. The AdFind tool has been observed in Trickbot, Ryuk, Maze, and FIN6 campaigns. For Winlogbeat, this rule requires Sysmon. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<account-or-group-discovery-via-built-in-tools, Account or Group Discovery via Built-In Tools>> |Adversaries may use built-in applications to get a listing of local system or domain accounts and groups. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |3
 
-|<<adding-hidden-file-attribute-via-attrib, Adding Hidden File Attribute via Attrib>> |Adversaries can add the 'hidden' attribute to files to hide them from the user in an attempt to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |111
+|<<adfind-command-activity, AdFind Command Activity>> |This rule detects the Active Directory query tool, AdFind.exe. AdFind has legitimate purposes, but it is frequently leveraged by threat actors to perform post-exploitation Active Directory reconnaissance. The AdFind tool has been observed in Trickbot, Ryuk, Maze, and FIN6 campaigns. For Winlogbeat, this rule requires Sysmon. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<adminsdholder-backdoor, AdminSDHolder Backdoor>> |Detects modifications in the AdminSDHolder object. Attackers can abuse the SDProp process to implement a persistent backdoor in Active Directory. SDProp compares the permissions on protected objects with those defined on the AdminSDHolder object. If the permissions on any of the protected accounts and groups do not match, the permissions on the protected accounts and groups are reset to match those of the domain's AdminSDHolder object, regaining their Administrative Privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |8.3.0 |106
+|<<adding-hidden-file-attribute-via-attrib, Adding Hidden File Attribute via Attrib>> |Adversaries can add the 'hidden' attribute to files to hide them from the user in an attempt to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |112
 
-|<<adminsdholder-sdprop-exclusion-added, AdminSDHolder SDProp Exclusion Added>> |Identifies a modification on the dsHeuristics attribute on the bit that holds the configuration of groups excluded from the SDProp process. The SDProp compares the permissions on protected objects with those defined on the AdminSDHolder object. If the permissions on any of the protected accounts and groups do not match, the permissions on the protected accounts and groups are reset to match those of the domain's AdminSDHolder object, meaning that groups excluded will remain unchanged. Attackers can abuse this misconfiguration to maintain long-term access to privileged accounts in these groups. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |8.3.0 |110
+|<<adminsdholder-backdoor, AdminSDHolder Backdoor>> |Detects modifications in the AdminSDHolder object. Attackers can abuse the SDProp process to implement a persistent backdoor in Active Directory. SDProp compares the permissions on protected objects with those defined on the AdminSDHolder object. If the permissions on any of the protected accounts and groups do not match, the permissions on the protected accounts and groups are reset to match those of the domain's AdminSDHolder object, regaining their Administrative Privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |None |106
+
+|<<adminsdholder-sdprop-exclusion-added, AdminSDHolder SDProp Exclusion Added>> |Identifies a modification on the dsHeuristics attribute on the bit that holds the configuration of groups excluded from the SDProp process. The SDProp compares the permissions on protected objects with those defined on the AdminSDHolder object. If the permissions on any of the protected accounts and groups do not match, the permissions on the protected accounts and groups are reset to match those of the domain's AdminSDHolder object, meaning that groups excluded will remain unchanged. Attackers can abuse this misconfiguration to maintain long-term access to privileged accounts in these groups. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |None |110
 
 |<<administrator-privileges-assigned-to-an-okta-group, Administrator Privileges Assigned to an Okta Group>> |Detects when an administrator role is assigned to an Okta group. An adversary may attempt to assign administrator privileges to an Okta group in order to assign additional permissions to compromised user accounts and maintain access to their target organization. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Persistence] |8.10.0 |205
 
 |<<administrator-role-assigned-to-an-okta-user, Administrator Role Assigned to an Okta User>> |Identifies when an administrator role is assigned to an Okta user. An adversary may attempt to assign an administrator role to an Okta user in order to assign additional permissions to a user account and maintain access to their target's environment. |[Data Source: Okta], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.10.0 |205
 
-|<<adobe-hijack-persistence, Adobe Hijack Persistence>> |Detects writing executable files that will be automatically launched by Adobe on launch. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<adobe-hijack-persistence, Adobe Hijack Persistence>> |Detects writing executable files that will be automatically launched by Adobe on launch. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |213
 
-|<<adversary-behavior-detected-elastic-endgame, Adversary Behavior - Detected - Elastic Endgame>> |Elastic Endgame detected an Adversary Behavior. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |8.3.0 |104
+|<<adversary-behavior-detected-elastic-endgame, Adversary Behavior - Detected - Elastic Endgame>> |Elastic Endgame detected an Adversary Behavior. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |None |104
 
-|<<agent-spoofing-mismatched-agent-id, Agent Spoofing - Mismatched Agent ID>> |Detects events that have a mismatch on the expected event agent ID. The status "agent_id_mismatch" occurs when the expected agent ID associated with the API key does not match the actual agent ID in an event. This could indicate attempts to spoof events in order to masquerade actual activity to evade detection. |[Use Case: Threat Detection], [Tactic: Defense Evasion] |8.3.0 |101
+|<<agent-spoofing-mismatched-agent-id, Agent Spoofing - Mismatched Agent ID>> |Detects events that have a mismatch on the expected event agent ID. The status "agent_id_mismatch" occurs when the expected agent ID associated with the API key does not match the actual agent ID in an event. This could indicate attempts to spoof events in order to masquerade actual activity to evade detection. |[Use Case: Threat Detection], [Tactic: Defense Evasion] |None |101
 
-|<<agent-spoofing-multiple-hosts-using-same-agent, Agent Spoofing - Multiple Hosts Using Same Agent>> |Detects when multiple hosts are using the same agent ID. This could occur in the event of an agent being taken over and used to inject illegitimate documents into an instance as an attempt to spoof events in order to masquerade actual activity to evade detection. |[Use Case: Threat Detection], [Tactic: Defense Evasion] |8.3.0 |101
+|<<agent-spoofing-multiple-hosts-using-same-agent, Agent Spoofing - Multiple Hosts Using Same Agent>> |Detects when multiple hosts are using the same agent ID. This could occur in the event of an agent being taken over and used to inject illegitimate documents into an instance as an attempt to spoof events in order to masquerade actual activity to evade detection. |[Use Case: Threat Detection], [Tactic: Defense Evasion] |None |101
 
-|<<alternate-data-stream-creation-execution-at-volume-root-directory, Alternate Data Stream Creation/Execution at Volume Root Directory>> |Identifies the creation of an Alternate Data Stream (ADS) at a volume root directory, which can indicate the attempt to hide tools and malware, as ADSs created in this directory are not displayed by system utilities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |1
+|<<alternate-data-stream-creation-execution-at-volume-root-directory, Alternate Data Stream Creation/Execution at Volume Root Directory>> |Identifies the creation of an Alternate Data Stream (ADS) at a volume root directory, which can indicate the attempt to hide tools and malware, as ADSs created in this directory are not displayed by system utilities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |1
 
-|<<anomalous-linux-compiler-activity, Anomalous Linux Compiler Activity>> |Looks for compiler activity by a user context which does not normally run compilers. This can be the result of ad-hoc software changes or unauthorized software deployment. This can also be due to local privilege elevation via locally run exploits or malware activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Resource Development] |8.3.0 |103
+|<<anomalous-linux-compiler-activity, Anomalous Linux Compiler Activity>> |Looks for compiler activity by a user context which does not normally run compilers. This can be the result of ad-hoc software changes or unauthorized software deployment. This can also be due to local privilege elevation via locally run exploits or malware activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Resource Development] |None |103
 
-|<<anomalous-process-for-a-linux-population, Anomalous Process For a Linux Population>> |Searches for rare processes running on multiple Linux hosts in an entire fleet or network. This reduces the detection of false positives since automated maintenance processes usually only run occasionally on a single machine but are common to all or many hosts in a fleet. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Resources: Investigation Guide] |8.3.0 |104
+|<<anomalous-process-for-a-linux-population, Anomalous Process For a Linux Population>> |Searches for rare processes running on multiple Linux hosts in an entire fleet or network. This reduces the detection of false positives since automated maintenance processes usually only run occasionally on a single machine but are common to all or many hosts in a fleet. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Resources: Investigation Guide] |None |104
 
-|<<anomalous-process-for-a-windows-population, Anomalous Process For a Windows Population>> |Searches for rare processes running on multiple hosts in an entire fleet or network. This reduces the detection of false positives since automated maintenance processes usually only run occasionally on a single machine but are common to all or many hosts in a fleet. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Tactic: Execution] |8.3.0 |105
+|<<anomalous-process-for-a-windows-population, Anomalous Process For a Windows Population>> |Searches for rare processes running on multiple hosts in an entire fleet or network. This reduces the detection of false positives since automated maintenance processes usually only run occasionally on a single machine but are common to all or many hosts in a fleet. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Tactic: Execution] |None |105
 
-|<<anomalous-windows-process-creation, Anomalous Windows Process Creation>> |Identifies unusual parent-child process relationships that can indicate malware execution or persistence mechanisms. Malicious scripts often call on other applications and processes as part of their exploit payload. For example, when a malicious Office document runs scripts as part of an exploit payload, Excel or Word may start a script interpreter process, which, in turn, runs a script that downloads and executes malware. Another common scenario is Outlook running an unusual process when malware is downloaded in an email. Monitoring and identifying anomalous process relationships is a method of detecting new and emerging malware that is not yet recognized by anti-virus scanners. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Resources: Investigation Guide] |8.3.0 |105
+|<<anomalous-windows-process-creation, Anomalous Windows Process Creation>> |Identifies unusual parent-child process relationships that can indicate malware execution or persistence mechanisms. Malicious scripts often call on other applications and processes as part of their exploit payload. For example, when a malicious Office document runs scripts as part of an exploit payload, Excel or Word may start a script interpreter process, which, in turn, runs a script that downloads and executes malware. Another common scenario is Outlook running an unusual process when malware is downloaded in an email. Monitoring and identifying anomalous process relationships is a method of detecting new and emerging malware that is not yet recognized by anti-virus scanners. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Resources: Investigation Guide] |None |105
 
-|<<apple-script-execution-followed-by-network-connection, Apple Script Execution followed by Network Connection>> |Detects execution via the Apple script interpreter (osascript) followed by a network connection from the same process within a short time period. Adversaries may use malicious scripts for execution and command and control. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |106
+|<<apple-script-execution-followed-by-network-connection, Apple Script Execution followed by Network Connection>> |Detects execution via the Apple script interpreter (osascript) followed by a network connection from the same process within a short time period. Adversaries may use malicious scripts for execution and command and control. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Execution], [Data Source: Elastic Defend] |None |106
 
 |<<apple-scripting-execution-with-administrator-privileges, Apple Scripting Execution with Administrator Privileges>> |Identifies execution of the Apple script interpreter (osascript) without a password prompt and with administrator privileges. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.11.0 |207
 
-|<<application-added-to-google-workspace-domain, Application Added to Google Workspace Domain>> |Detects when a Google marketplace application is added to the Google Workspace domain. An adversary may add a malicious application to an organization’s Google Workspace domain in order to maintain a presence in their target’s organization and steal data. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Persistence], [Resources: Investigation Guide] |8.4.0 |205
+|<<application-added-to-google-workspace-domain, Application Added to Google Workspace Domain>> |Detects when a Google marketplace application is added to the Google Workspace domain. An adversary may add a malicious application to an organization’s Google Workspace domain in order to maintain a presence in their target’s organization and steal data. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Persistence], [Resources: Investigation Guide] |None |205
 
-|<<application-removed-from-blocklist-in-google-workspace, Application Removed from Blocklist in Google Workspace>> |Google Workspace administrators may be aware of malicious applications within the Google marketplace and block these applications for user security purposes. An adversary, with administrative privileges, may remove this application from the explicit block list to allow distribution of the application amongst users. This may also indicate the unauthorized use of an application that had been previously blocked before by a user with admin privileges. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Resources: Investigation Guide], [Tactic: Defense Evasion] |8.4.0 |106
+|<<application-removed-from-blocklist-in-google-workspace, Application Removed from Blocklist in Google Workspace>> |Google Workspace administrators may be aware of malicious applications within the Google marketplace and block these applications for user security purposes. An adversary, with administrative privileges, may remove this application from the explicit block list to allow distribution of the application amongst users. This may also indicate the unauthorized use of an application that had been previously blocked before by a user with admin privileges. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Resources: Investigation Guide], [Tactic: Defense Evasion] |None |106
 
-|<<archive-file-with-unusual-extension, Archive File with Unusual Extension>> |Identifies the creation of an archive file with an unusual extension. Attackers may attempt to evade detection by masquerading files using the file extension values used by image, audio, or document file types. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |2
+|<<archive-file-with-unusual-extension, Archive File with Unusual Extension>> |Identifies the creation of an archive file with an unusual extension. Attackers may attempt to evade detection by masquerading files using the file extension values used by image, audio, or document file types. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |None |2
 
-|<<at-exe-command-lateral-movement, At.exe Command Lateral Movement>> |Identifies use of at.exe to interact with the task scheduler on remote hosts. Remote task creations, modifications or execution could be indicative of adversary lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |8.3.0 |3
+|<<at-exe-command-lateral-movement, At.exe Command Lateral Movement>> |Identifies use of at.exe to interact with the task scheduler on remote hosts. Remote task creations, modifications or execution could be indicative of adversary lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |None |3
 
-|<<attempt-to-clear-kernel-ring-buffer, Attempt to Clear Kernel Ring Buffer>> |Monitors for the deletion of the kernel ring buffer events through dmesg. Attackers may clear kernel ring buffer events to evade detection after installing a Linux kernel module (LKM). |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |4
+|<<attempt-to-clear-kernel-ring-buffer, Attempt to Clear Kernel Ring Buffer>> |Monitors for the deletion of the kernel ring buffer events through dmesg. Attackers may clear kernel ring buffer events to evade detection after installing a Linux kernel module (LKM). |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |5
 
 |<<attempt-to-create-okta-api-token, Attempt to Create Okta API Token>> |Detects attempts to create an Okta API token. An adversary may create an Okta API token to maintain access to an organization's network while they work to achieve their objectives. An attacker may abuse an API token to execute techniques such as creating user accounts or disabling security rules or policies. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Persistence] |8.10.0 |205
 
@@ -214,17 +216,17 @@ and their rule type is `machine_learning`.
 
 |<<attempt-to-delete-an-okta-policy-rule, Attempt to Delete an Okta Policy Rule>> |Detects attempts to delete a rule within an Okta policy. An adversary may attempt to delete an Okta policy rule in order to weaken an organization's security controls. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Defense Evasion] |8.10.0 |206
 
-|<<attempt-to-disable-gatekeeper, Attempt to Disable Gatekeeper>> |Detects attempts to disable Gatekeeper on macOS. Gatekeeper is a security feature that's designed to ensure that only trusted software is run. Adversaries may attempt to disable Gatekeeper before executing malicious code. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |106
+|<<attempt-to-disable-gatekeeper, Attempt to Disable Gatekeeper>> |Detects attempts to disable Gatekeeper on macOS. Gatekeeper is a security feature that's designed to ensure that only trusted software is run. Adversaries may attempt to disable Gatekeeper before executing malicious code. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |106
 
-|<<attempt-to-disable-iptables-or-firewall, Attempt to Disable IPTables or Firewall>> |Adversaries may attempt to disable the iptables or firewall service in an attempt to affect how a host is allowed to receive or send network traffic. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |7
+|<<attempt-to-disable-iptables-or-firewall, Attempt to Disable IPTables or Firewall>> |Adversaries may attempt to disable the iptables or firewall service in an attempt to affect how a host is allowed to receive or send network traffic. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |7
 
-|<<attempt-to-disable-syslog-service, Attempt to Disable Syslog Service>> |Adversaries may attempt to disable the syslog service in an attempt to an attempt to disrupt event logging and evade detection by security controls. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<attempt-to-disable-syslog-service, Attempt to Disable Syslog Service>> |Adversaries may attempt to disable the syslog service in an attempt to an attempt to disrupt event logging and evade detection by security controls. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<attempt-to-enable-the-root-account, Attempt to Enable the Root Account>> |Identifies attempts to enable the root account using the dsenableroot command. This command may be abused by adversaries for persistence, as the root account is disabled by default. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<attempt-to-enable-the-root-account, Attempt to Enable the Root Account>> |Identifies attempts to enable the root account using the dsenableroot command. This command may be abused by adversaries for persistence, as the root account is disabled by default. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<attempt-to-install-kali-linux-via-wsl, Attempt to Install Kali Linux via WSL>> |Detects attempts to install or use Kali Linux via Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |7
+|<<attempt-to-install-kali-linux-via-wsl, Attempt to Install Kali Linux via WSL>> |Detects attempts to install or use Kali Linux via Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |7
 
-|<<attempt-to-install-root-certificate, Attempt to Install Root Certificate>> |Adversaries may install a root certificate on a compromised system to avoid warnings when connecting to their command and control servers. Root certificates are used in public key cryptography to identify a root certificate authority (CA). When a root certificate is installed, the system or application will trust certificates in the root's chain of trust that have been signed by the root certificate. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |106
+|<<attempt-to-install-root-certificate, Attempt to Install Root Certificate>> |Adversaries may install a root certificate on a compromised system to avoid warnings when connecting to their command and control servers. Root certificates are used in public key cryptography to identify a root certificate authority (CA). When a root certificate is installed, the system or application will trust certificates in the root's chain of trust that have been signed by the root certificate. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |106
 
 |<<attempt-to-modify-an-okta-application, Attempt to Modify an Okta Application>> |Detects attempts to modify an Okta application. An adversary may attempt to modify, deactivate, or delete an Okta application in order to weaken an organization's security controls or disrupt their business operations. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Impact] |8.10.0 |205
 
@@ -234,755 +236,759 @@ and their rule type is `machine_learning`.
 
 |<<attempt-to-modify-an-okta-policy-rule, Attempt to Modify an Okta Policy Rule>> |Detects attempts to modify a rule within an Okta policy. An adversary may attempt to modify an Okta policy rule in order to weaken an organization's security controls. |[Use Case: Identity and Access Audit], [Tactic: Defense Evasion], [Data Source: Okta] |8.10.0 |207
 
-|<<attempt-to-mount-smb-share-via-command-line, Attempt to Mount SMB Share via Command Line>> |Identifies the execution of macOS built-in commands to mount a Server Message Block (SMB) network share. Adversaries may use valid accounts to interact with a remote network share using SMB. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |8.3.0 |107
+|<<attempt-to-mount-smb-share-via-command-line, Attempt to Mount SMB Share via Command Line>> |Identifies the execution of macOS built-in commands to mount a Server Message Block (SMB) network share. Adversaries may use valid accounts to interact with a remote network share using SMB. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |None |107
 
 |<<attempt-to-reset-mfa-factors-for-an-okta-user-account, Attempt to Reset MFA Factors for an Okta User Account>> |Detects attempts to reset an Okta user's enrolled multi-factor authentication (MFA) factors. An adversary may attempt to reset the MFA factors for an Okta user's account in order to register new MFA factors and abuse the account to blend in with normal activity in the victim's environment. |[Tactic: Persistence], [Use Case: Identity and Access Audit], [Data Source: Okta] |8.10.0 |206
 
+|<<attempt-to-retrieve-user-data-from-aws-ec2-instance, Attempt to Retrieve User Data from AWS EC2 Instance>> |Identifies discovery request `DescribeInstanceAttribute` with the attribute userData and instanceId in AWS CloudTrail logs. This may indicate an attempt to retrieve user data from an EC2 instance. Adversaries may use this information to gather sensitive data from the instance or to identify potential vulnerabilities. This is a building block rule that does not generate an alert on its own, but serves as a signal for anomalous activity. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon EC2], [Use Case: Log Auditing], [Tactic: Discovery], [Rule Type: BBR] |8.9.0 |1
+
 |<<attempt-to-revoke-okta-api-token, Attempt to Revoke Okta API Token>> |Identifies attempts to revoke an Okta API token. An adversary may attempt to revoke or delete an Okta API token to disrupt an organization's business operations. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Impact] |8.10.0 |206
 
-|<<attempt-to-unload-elastic-endpoint-security-kernel-extension, Attempt to Unload Elastic Endpoint Security Kernel Extension>> |Identifies attempts to unload the Elastic Endpoint Security kernel extension via the kextunload command. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |106
+|<<attempt-to-unload-elastic-endpoint-security-kernel-extension, Attempt to Unload Elastic Endpoint Security Kernel Extension>> |Identifies attempts to unload the Elastic Endpoint Security kernel extension via the kextunload command. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |106
 
 |<<attempted-bypass-of-okta-mfa, Attempted Bypass of Okta MFA>> |Detects attempts to bypass Okta multi-factor authentication (MFA). An adversary may attempt to bypass the Okta MFA policies configured for an organization in order to obtain unauthorized access to an application. |[Data Source: Okta], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |8.10.0 |207
 
-|<<attempted-private-key-access, Attempted Private Key Access>> |Attackers may try to access private keys, e.g. ssh, in order to gain further authenticated access to the environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |3
+|<<attempted-private-key-access, Attempted Private Key Access>> |Attackers may try to access private keys, e.g. ssh, in order to gain further authenticated access to the environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Rule Type: BBR] |None |3
 
-|<<attempts-to-brute-force-a-microsoft-365-user-account, Attempts to Brute Force a Microsoft 365 User Account>> |Identifies attempts to brute force a Microsoft 365 user account. An adversary may attempt a brute force attack to obtain unauthorized access to user accounts. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |8.8.0 |207
+|<<attempts-to-brute-force-a-microsoft-365-user-account, Attempts to Brute Force a Microsoft 365 User Account>> |Identifies attempts to brute force a Microsoft 365 user account. An adversary may attempt a brute force attack to obtain unauthorized access to user accounts. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |None |207
 
 |<<attempts-to-brute-force-an-okta-user-account, Attempts to Brute Force an Okta User Account>> |Identifies when an Okta user account is locked out 3 times within a 3 hour window. An adversary may attempt a brute force or password spraying attack to obtain unauthorized access to user accounts. The default Okta authentication policy ensures that a user account is locked out after 10 failed authentication attempts. |[Use Case: Identity and Access Audit], [Tactic: Credential Access], [Data Source: Okta] |8.10.0 |208
 
-|<<authorization-plugin-modification, Authorization Plugin Modification>> |Authorization plugins are used to extend the authorization services API and implement mechanisms that are not natively supported by the OS, such as multi-factor authentication with third party software. Adversaries may abuse this feature to persist and/or collect clear text credentials as they traverse the registered plugins during user logon. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |107
+|<<authorization-plugin-modification, Authorization Plugin Modification>> |Authorization plugins are used to extend the authorization services API and implement mechanisms that are not natively supported by the OS, such as multi-factor authentication with third party software. Adversaries may abuse this feature to persist and/or collect clear text credentials as they traverse the registered plugins during user logon. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |107
 
-|<<azure-ad-global-administrator-role-assigned, Azure AD Global Administrator Role Assigned>> |In Azure Active Directory (Azure AD), permissions to manage resources are assigned using roles. The Global Administrator is a role that enables users to have access to all administrative features in Azure AD and services that use Azure AD identities like the Microsoft 365 Defender portal, the Microsoft 365 compliance center, Exchange, SharePoint Online, and Skype for Business Online. Attackers can add users as Global Administrators to maintain access and manage all subscriptions and their settings and resources. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.3.0 |102
+|<<azure-ad-global-administrator-role-assigned, Azure AD Global Administrator Role Assigned>> |In Azure Active Directory (Azure AD), permissions to manage resources are assigned using roles. The Global Administrator is a role that enables users to have access to all administrative features in Azure AD and services that use Azure AD identities like the Microsoft 365 Defender portal, the Microsoft 365 compliance center, Exchange, SharePoint Online, and Skype for Business Online. Attackers can add users as Global Administrators to maintain access and manage all subscriptions and their settings and resources. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Persistence] |None |102
 
-|<<azure-active-directory-high-risk-sign-in, Azure Active Directory High Risk Sign-in>> |Identifies high risk Azure Active Directory (AD) sign-ins by leveraging Microsoft's Identity Protection machine learning and heuristics. Identity Protection categorizes risk into three tiers: low, medium, and high. While Microsoft does not provide specific details about how risk is calculated, each level brings higher confidence that the user or sign-in is compromised. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |8.3.0 |105
+|<<azure-active-directory-high-risk-sign-in, Azure Active Directory High Risk Sign-in>> |Identifies high risk Azure Active Directory (AD) sign-ins by leveraging Microsoft's Identity Protection machine learning and heuristics. Identity Protection categorizes risk into three tiers: low, medium, and high. While Microsoft does not provide specific details about how risk is calculated, each level brings higher confidence that the user or sign-in is compromised. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |None |105
 
-|<<azure-active-directory-high-risk-user-sign-in-heuristic, Azure Active Directory High Risk User Sign-in Heuristic>> |Identifies high risk Azure Active Directory (AD) sign-ins by leveraging Microsoft Identity Protection machine learning and heuristics. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |8.3.0 |105
+|<<azure-active-directory-high-risk-user-sign-in-heuristic, Azure Active Directory High Risk User Sign-in Heuristic>> |Identifies high risk Azure Active Directory (AD) sign-ins by leveraging Microsoft Identity Protection machine learning and heuristics. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |None |105
 
-|<<azure-active-directory-powershell-sign-in, Azure Active Directory PowerShell Sign-in>> |Identifies a sign-in using the Azure Active Directory PowerShell module. PowerShell for Azure Active Directory allows for managing settings from the command line, which is intended for users who are members of an admin role. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |8.3.0 |105
+|<<azure-active-directory-powershell-sign-in, Azure Active Directory PowerShell Sign-in>> |Identifies a sign-in using the Azure Active Directory PowerShell module. PowerShell for Azure Active Directory allows for managing settings from the command line, which is intended for users who are members of an admin role. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |None |105
 
-|<<azure-alert-suppression-rule-created-or-modified, Azure Alert Suppression Rule Created or Modified>> |Identifies the creation of suppression rules in Azure. Suppression rules are a mechanism used to suppress alerts previously identified as false positives or too noisy to be in production. This mechanism can be abused or mistakenly configured, resulting in defense evasions and loss of security visibility. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.3.0 |102
+|<<azure-alert-suppression-rule-created-or-modified, Azure Alert Suppression Rule Created or Modified>> |Identifies the creation of suppression rules in Azure. Suppression rules are a mechanism used to suppress alerts previously identified as false positives or too noisy to be in production. This mechanism can be abused or mistakenly configured, resulting in defense evasions and loss of security visibility. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |102
 
-|<<azure-application-credential-modification, Azure Application Credential Modification>> |Identifies when a new credential is added to an application in Azure. An application may use a certificate or secret string to prove its identity when requesting a token. Multiple certificates and secrets can be added for an application and an adversary may abuse this by creating an additional authentication method to evade defenses or persist in an environment. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |8.3.0 |102
+|<<azure-application-credential-modification, Azure Application Credential Modification>> |Identifies when a new credential is added to an application in Azure. An application may use a certificate or secret string to prove its identity when requesting a token. Multiple certificates and secrets can be added for an application and an adversary may abuse this by creating an additional authentication method to evade defenses or persist in an environment. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |None |102
 
-|<<azure-automation-account-created, Azure Automation Account Created>> |Identifies when an Azure Automation account is created. Azure Automation accounts can be used to automate management tasks and orchestrate actions across systems. An adversary may create an Automation account in order to maintain persistence in their target's environment. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.3.0 |102
+|<<azure-automation-account-created, Azure Automation Account Created>> |Identifies when an Azure Automation account is created. Azure Automation accounts can be used to automate management tasks and orchestrate actions across systems. An adversary may create an Automation account in order to maintain persistence in their target's environment. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Persistence] |None |102
 
-|<<azure-automation-runbook-created-or-modified, Azure Automation Runbook Created or Modified>> |Identifies when an Azure Automation runbook is created or modified. An adversary may create or modify an Azure Automation runbook to execute malicious code and maintain persistence in their target's environment. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |8.3.0 |102
+|<<azure-automation-runbook-created-or-modified, Azure Automation Runbook Created or Modified>> |Identifies when an Azure Automation runbook is created or modified. An adversary may create or modify an Azure Automation runbook to execute malicious code and maintain persistence in their target's environment. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |None |102
 
-|<<azure-automation-runbook-deleted, Azure Automation Runbook Deleted>> |Identifies when an Azure Automation runbook is deleted. An adversary may delete an Azure Automation runbook in order to disrupt their target's automated business operations or to remove a malicious runbook for defense evasion. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.3.0 |102
+|<<azure-automation-runbook-deleted, Azure Automation Runbook Deleted>> |Identifies when an Azure Automation runbook is deleted. An adversary may delete an Azure Automation runbook in order to disrupt their target's automated business operations or to remove a malicious runbook for defense evasion. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |102
 
-|<<azure-automation-webhook-created, Azure Automation Webhook Created>> |Identifies when an Azure Automation webhook is created. Azure Automation runbooks can be configured to execute via a webhook. A webhook uses a custom URL passed to Azure Automation along with a data payload specific to the runbook. An adversary may create a webhook in order to trigger a runbook that contains malicious code. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |8.3.0 |102
+|<<azure-automation-webhook-created, Azure Automation Webhook Created>> |Identifies when an Azure Automation webhook is created. Azure Automation runbooks can be configured to execute via a webhook. A webhook uses a custom URL passed to Azure Automation along with a data payload specific to the runbook. An adversary may create a webhook in order to trigger a runbook that contains malicious code. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |None |102
 
-|<<azure-blob-container-access-level-modification, Azure Blob Container Access Level Modification>> |Identifies changes to container access levels in Azure. Anonymous public read access to containers and blobs in Azure is a way to share data broadly, but can present a security risk if access to sensitive data is not managed judiciously. |[Domain: Cloud], [Data Source: Azure], [Use Case: Asset Visibility], [Tactic: Discovery] |8.3.0 |102
+|<<azure-blob-container-access-level-modification, Azure Blob Container Access Level Modification>> |Identifies changes to container access levels in Azure. Anonymous public read access to containers and blobs in Azure is a way to share data broadly, but can present a security risk if access to sensitive data is not managed judiciously. |[Domain: Cloud], [Data Source: Azure], [Use Case: Asset Visibility], [Tactic: Discovery] |None |102
 
-|<<azure-blob-permissions-modification, Azure Blob Permissions Modification>> |Identifies when the Azure role-based access control (Azure RBAC) permissions are modified for an Azure Blob. An adversary may modify the permissions on a blob to weaken their target's security controls or an administrator may inadvertently modify the permissions, which could lead to data exposure or loss. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |103
+|<<azure-blob-permissions-modification, Azure Blob Permissions Modification>> |Identifies when the Azure role-based access control (Azure RBAC) permissions are modified for an Azure Blob. An adversary may modify the permissions on a blob to weaken their target's security controls or an administrator may inadvertently modify the permissions, which could lead to data exposure or loss. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |103
 
-|<<azure-command-execution-on-virtual-machine, Azure Command Execution on Virtual Machine>> |Identifies command execution on a virtual machine (VM) in Azure. A Virtual Machine Contributor role lets you manage virtual machines, but not access them, nor access the virtual network or storage account they’re connected to. However, commands can be run via PowerShell on the VM, which execute as System. Other roles, such as certain Administrator roles may be able to execute commands on a VM as well. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Execution] |8.3.0 |102
+|<<azure-command-execution-on-virtual-machine, Azure Command Execution on Virtual Machine>> |Identifies command execution on a virtual machine (VM) in Azure. A Virtual Machine Contributor role lets you manage virtual machines, but not access them, nor access the virtual network or storage account they’re connected to. However, commands can be run via PowerShell on the VM, which execute as System. Other roles, such as certain Administrator roles may be able to execute commands on a VM as well. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Execution] |None |102
 
-|<<azure-conditional-access-policy-modified, Azure Conditional Access Policy Modified>> |Identifies when an Azure Conditional Access policy is modified. Azure Conditional Access policies control access to resources via if-then statements. For example, if a user wants to access a resource, then they must complete an action such as using multi-factor authentication to access it. An adversary may modify a Conditional Access policy in order to weaken their target's security controls. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |8.3.0 |102
+|<<azure-conditional-access-policy-modified, Azure Conditional Access Policy Modified>> |Identifies when an Azure Conditional Access policy is modified. Azure Conditional Access policies control access to resources via if-then statements. For example, if a user wants to access a resource, then they must complete an action such as using multi-factor authentication to access it. An adversary may modify a Conditional Access policy in order to weaken their target's security controls. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |None |102
 
-|<<azure-diagnostic-settings-deletion, Azure Diagnostic Settings Deletion>> |Identifies the deletion of diagnostic settings in Azure, which send platform logs and metrics to different destinations. An adversary may delete diagnostic settings in an attempt to evade defenses. |[Domain: Cloud], [Data Source: Azure], [Tactic: Defense Evasion] |8.3.0 |102
+|<<azure-diagnostic-settings-deletion, Azure Diagnostic Settings Deletion>> |Identifies the deletion of diagnostic settings in Azure, which send platform logs and metrics to different destinations. An adversary may delete diagnostic settings in an attempt to evade defenses. |[Domain: Cloud], [Data Source: Azure], [Tactic: Defense Evasion] |None |102
 
-|<<azure-event-hub-authorization-rule-created-or-updated, Azure Event Hub Authorization Rule Created or Updated>> |Identifies when an Event Hub Authorization Rule is created or updated in Azure. An authorization rule is associated with specific rights, and carries a pair of cryptographic keys. When you create an Event Hubs namespace, a policy rule named RootManageSharedAccessKey is created for the namespace. This has manage permissions for the entire namespace and it's recommended that you treat this rule like an administrative root account and don't use it in your application. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Collection] |8.3.0 |103
+|<<azure-event-hub-authorization-rule-created-or-updated, Azure Event Hub Authorization Rule Created or Updated>> |Identifies when an Event Hub Authorization Rule is created or updated in Azure. An authorization rule is associated with specific rights, and carries a pair of cryptographic keys. When you create an Event Hubs namespace, a policy rule named RootManageSharedAccessKey is created for the namespace. This has manage permissions for the entire namespace and it's recommended that you treat this rule like an administrative root account and don't use it in your application. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Collection] |None |103
 
-|<<azure-event-hub-deletion, Azure Event Hub Deletion>> |Identifies an Event Hub deletion in Azure. An Event Hub is an event processing service that ingests and processes large volumes of events and data. An adversary may delete an Event Hub in an attempt to evade detection. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Defense Evasion] |8.3.0 |102
+|<<azure-event-hub-deletion, Azure Event Hub Deletion>> |Identifies an Event Hub deletion in Azure. An Event Hub is an event processing service that ingests and processes large volumes of events and data. An adversary may delete an Event Hub in an attempt to evade detection. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Defense Evasion] |None |102
 
-|<<azure-external-guest-user-invitation, Azure External Guest User Invitation>> |Identifies an invitation to an external user in Azure Active Directory (AD). Azure AD is extended to include collaboration, allowing you to invite people from outside your organization to be guest users in your cloud account. Unless there is a business need to provision guest access, it is best practice avoid creating guest users. Guest users could potentially be overlooked indefinitely leading to a potential vulnerability. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |8.3.0 |102
+|<<azure-external-guest-user-invitation, Azure External Guest User Invitation>> |Identifies an invitation to an external user in Azure Active Directory (AD). Azure AD is extended to include collaboration, allowing you to invite people from outside your organization to be guest users in your cloud account. Unless there is a business need to provision guest access, it is best practice avoid creating guest users. Guest users could potentially be overlooked indefinitely leading to a potential vulnerability. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |None |102
 
-|<<azure-firewall-policy-deletion, Azure Firewall Policy Deletion>> |Identifies the deletion of a firewall policy in Azure. An adversary may delete a firewall policy in an attempt to evade defenses and/or to eliminate barriers to their objective. |[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |8.3.0 |102
+|<<azure-firewall-policy-deletion, Azure Firewall Policy Deletion>> |Identifies the deletion of a firewall policy in Azure. An adversary may delete a firewall policy in an attempt to evade defenses and/or to eliminate barriers to their objective. |[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |None |102
 
-|<<azure-frontdoor-web-application-firewall-waf-policy-deleted, Azure Frontdoor Web Application Firewall (WAF) Policy Deleted>> |Identifies the deletion of a Frontdoor Web Application Firewall (WAF) Policy in Azure. An adversary may delete a Frontdoor Web Application Firewall (WAF) Policy in an attempt to evade defenses and/or to eliminate barriers to their objective. |[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |8.3.0 |102
+|<<azure-frontdoor-web-application-firewall-waf-policy-deleted, Azure Frontdoor Web Application Firewall (WAF) Policy Deleted>> |Identifies the deletion of a Frontdoor Web Application Firewall (WAF) Policy in Azure. An adversary may delete a Frontdoor Web Application Firewall (WAF) Policy in an attempt to evade defenses and/or to eliminate barriers to their objective. |[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |None |102
 
-|<<azure-full-network-packet-capture-detected, Azure Full Network Packet Capture Detected>> |Identifies potential full network packet capture in Azure. Packet Capture is an Azure Network Watcher feature that can be used to inspect network traffic. This feature can potentially be abused to read sensitive data from unencrypted internal traffic. |[Domain: Cloud], [Data Source: Azure], [Tactic: Credential Access] |8.3.0 |103
+|<<azure-full-network-packet-capture-detected, Azure Full Network Packet Capture Detected>> |Identifies potential full network packet capture in Azure. Packet Capture is an Azure Network Watcher feature that can be used to inspect network traffic. This feature can potentially be abused to read sensitive data from unencrypted internal traffic. |[Domain: Cloud], [Data Source: Azure], [Tactic: Credential Access] |None |103
 
-|<<azure-global-administrator-role-addition-to-pim-user, Azure Global Administrator Role Addition to PIM User>> |Identifies an Azure Active Directory (AD) Global Administrator role addition to a Privileged Identity Management (PIM) user account. PIM is a service that enables you to manage, control, and monitor access to important resources in an organization. Users who are assigned to the Global administrator role can read and modify any administrative setting in your Azure AD organization. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.3.0 |102
+|<<azure-global-administrator-role-addition-to-pim-user, Azure Global Administrator Role Addition to PIM User>> |Identifies an Azure Active Directory (AD) Global Administrator role addition to a Privileged Identity Management (PIM) user account. PIM is a service that enables you to manage, control, and monitor access to important resources in an organization. Users who are assigned to the Global administrator role can read and modify any administrative setting in your Azure AD organization. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Persistence] |None |102
 
-|<<azure-key-vault-modified, Azure Key Vault Modified>> |Identifies modifications to a Key Vault in Azure. The Key Vault is a service that safeguards encryption keys and secrets like certificates, connection strings, and passwords. Because this data is sensitive and business critical, access to key vaults should be secured to allow only authorized applications and users. |[Domain: Cloud], [Data Source: Azure], [Tactic: Credential Access] |8.3.0 |103
+|<<azure-key-vault-modified, Azure Key Vault Modified>> |Identifies modifications to a Key Vault in Azure. The Key Vault is a service that safeguards encryption keys and secrets like certificates, connection strings, and passwords. Because this data is sensitive and business critical, access to key vaults should be secured to allow only authorized applications and users. |[Domain: Cloud], [Data Source: Azure], [Tactic: Credential Access] |None |103
 
-|<<azure-kubernetes-events-deleted, Azure Kubernetes Events Deleted>> |Identifies when events are deleted in Azure Kubernetes. Kubernetes events are objects that log any state changes. Example events are a container creation, an image pull, or a pod scheduling on a node. An adversary may delete events in Azure Kubernetes in an attempt to evade detection. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Defense Evasion] |8.3.0 |102
+|<<azure-kubernetes-events-deleted, Azure Kubernetes Events Deleted>> |Identifies when events are deleted in Azure Kubernetes. Kubernetes events are objects that log any state changes. Example events are a container creation, an image pull, or a pod scheduling on a node. An adversary may delete events in Azure Kubernetes in an attempt to evade detection. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Defense Evasion] |None |102
 
-|<<azure-kubernetes-pods-deleted, Azure Kubernetes Pods Deleted>> |Identifies the deletion of Azure Kubernetes Pods. Adversaries may delete a Kubernetes pod to disrupt the normal behavior of the environment. |[Domain: Cloud], [Data Source: Azure], [Use Case: Asset Visibility], [Tactic: Impact] |8.3.0 |102
+|<<azure-kubernetes-pods-deleted, Azure Kubernetes Pods Deleted>> |Identifies the deletion of Azure Kubernetes Pods. Adversaries may delete a Kubernetes pod to disrupt the normal behavior of the environment. |[Domain: Cloud], [Data Source: Azure], [Use Case: Asset Visibility], [Tactic: Impact] |None |102
 
-|<<azure-kubernetes-rolebindings-created, Azure Kubernetes Rolebindings Created>> |Identifies the creation of role binding or cluster role bindings. You can assign these roles to Kubernetes subjects (users, groups, or service accounts) with role bindings and cluster role bindings. An adversary who has permissions to create bindings and cluster-bindings in the cluster can create a binding to the cluster-admin ClusterRole or to other high privileges roles. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |8.3.0 |102
+|<<azure-kubernetes-rolebindings-created, Azure Kubernetes Rolebindings Created>> |Identifies the creation of role binding or cluster role bindings. You can assign these roles to Kubernetes subjects (users, groups, or service accounts) with role bindings and cluster role bindings. An adversary who has permissions to create bindings and cluster-bindings in the cluster can create a binding to the cluster-admin ClusterRole or to other high privileges roles. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |None |102
 
-|<<azure-network-watcher-deletion, Azure Network Watcher Deletion>> |Identifies the deletion of a Network Watcher in Azure. Network Watchers are used to monitor, diagnose, view metrics, and enable or disable logs for resources in an Azure virtual network. An adversary may delete a Network Watcher in an attempt to evade defenses. |[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |8.3.0 |102
+|<<azure-network-watcher-deletion, Azure Network Watcher Deletion>> |Identifies the deletion of a Network Watcher in Azure. Network Watchers are used to monitor, diagnose, view metrics, and enable or disable logs for resources in an Azure virtual network. An adversary may delete a Network Watcher in an attempt to evade defenses. |[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Defense Evasion] |None |102
 
-|<<azure-privilege-identity-management-role-modified, Azure Privilege Identity Management Role Modified>> |Azure Active Directory (AD) Privileged Identity Management (PIM) is a service that enables you to manage, control, and monitor access to important resources in an organization. PIM can be used to manage the built-in Azure resource roles such as Global Administrator and Application Administrator. An adversary may add a user to a PIM role in order to maintain persistence in their target's environment or modify a PIM role to weaken their target's security controls. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |8.3.0 |105
+|<<azure-privilege-identity-management-role-modified, Azure Privilege Identity Management Role Modified>> |Azure Active Directory (AD) Privileged Identity Management (PIM) is a service that enables you to manage, control, and monitor access to important resources in an organization. PIM can be used to manage the built-in Azure resource roles such as Global Administrator and Application Administrator. An adversary may add a user to a PIM role in order to maintain persistence in their target's environment or modify a PIM role to weaken their target's security controls. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |None |105
 
-|<<azure-resource-group-deletion, Azure Resource Group Deletion>> |Identifies the deletion of a resource group in Azure, which includes all resources within the group. Deletion is permanent and irreversible. An adversary may delete a resource group in an attempt to evade defenses or intentionally destroy data. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Impact] |8.3.0 |102
+|<<azure-resource-group-deletion, Azure Resource Group Deletion>> |Identifies the deletion of a resource group in Azure, which includes all resources within the group. Deletion is permanent and irreversible. An adversary may delete a resource group in an attempt to evade defenses or intentionally destroy data. |[Domain: Cloud], [Data Source: Azure], [Use Case: Log Auditing], [Tactic: Impact] |None |102
 
-|<<azure-service-principal-addition, Azure Service Principal Addition>> |Identifies when a new service principal is added in Azure. An application, hosted service, or automated tool that accesses or modifies resources needs an identity created. This identity is known as a service principal. For security reasons, it's always recommended to use service principals with automated tools rather than allowing them to log in with a user identity. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Defense Evasion] |8.3.0 |105
+|<<azure-service-principal-addition, Azure Service Principal Addition>> |Identifies when a new service principal is added in Azure. An application, hosted service, or automated tool that accesses or modifies resources needs an identity created. This identity is known as a service principal. For security reasons, it's always recommended to use service principals with automated tools rather than allowing them to log in with a user identity. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Defense Evasion] |None |105
 
-|<<azure-service-principal-credentials-added, Azure Service Principal Credentials Added>> |Identifies when new Service Principal credentials have been added in Azure. In most organizations, credentials will be added to service principals infrequently. Hijacking an application (by adding a rogue secret or certificate) with granted permissions will allow the attacker to access data that is normally protected by MFA requirements. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Impact] |8.3.0 |102
+|<<azure-service-principal-credentials-added, Azure Service Principal Credentials Added>> |Identifies when new Service Principal credentials have been added in Azure. In most organizations, credentials will be added to service principals infrequently. Hijacking an application (by adding a rogue secret or certificate) with granted permissions will allow the attacker to access data that is normally protected by MFA requirements. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Impact] |None |102
 
-|<<azure-storage-account-key-regenerated, Azure Storage Account Key Regenerated>> |Identifies a rotation to storage account access keys in Azure. Regenerating access keys can affect any applications or Azure services that are dependent on the storage account key. Adversaries may regenerate a key as a means of acquiring credentials to access systems and resources. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |8.3.0 |102
+|<<azure-storage-account-key-regenerated, Azure Storage Account Key Regenerated>> |Identifies a rotation to storage account access keys in Azure. Regenerating access keys can affect any applications or Azure services that are dependent on the storage account key. Adversaries may regenerate a key as a means of acquiring credentials to access systems and resources. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |None |102
 
-|<<azure-virtual-network-device-modified-or-deleted, Azure Virtual Network Device Modified or Deleted>> |Identifies when a virtual network device is modified or deleted. This can be a network virtual appliance, virtual hub, or virtual router. |[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Impact] |8.3.0 |102
+|<<azure-virtual-network-device-modified-or-deleted, Azure Virtual Network Device Modified or Deleted>> |Identifies when a virtual network device is modified or deleted. This can be a network virtual appliance, virtual hub, or virtual router. |[Domain: Cloud], [Data Source: Azure], [Use Case: Network Security Monitoring], [Tactic: Impact] |None |102
 
-|<<bpf-filter-applied-using-tc, BPF filter applied using TC>> |Detects when the tc (transmission control) binary is utilized to set a BPF (Berkeley Packet Filter) on a network interface. Tc is used to configure Traffic Control in the Linux kernel. It can shape, schedule, police and drop traffic. A threat actor can utilize tc to set a bpf filter on an interface for the purpose of manipulating the incoming traffic. This technique is not at all common and should indicate abnormal, suspicious or malicious activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: TripleCross], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |108
+|<<bpf-filter-applied-using-tc, BPF filter applied using TC>> |Detects when the tc (transmission control) binary is utilized to set a BPF (Berkeley Packet Filter) on a network interface. Tc is used to configure Traffic Control in the Linux kernel. It can shape, schedule, police and drop traffic. A threat actor can utilize tc to set a bpf filter on an interface for the purpose of manipulating the incoming traffic. This technique is not at all common and should indicate abnormal, suspicious or malicious activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: TripleCross], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |108
 
-|<<base16-or-base32-encoding-decoding-activity, Base16 or Base32 Encoding/Decoding Activity>> |Adversaries may encode/decode data in an attempt to evade detection by host- or network-based security controls. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |110
+|<<base16-or-base32-encoding-decoding-activity, Base16 or Base32 Encoding/Decoding Activity>> |Adversaries may encode/decode data in an attempt to evade detection by host- or network-based security controls. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |110
 
-|<<bash-shell-profile-modification, Bash Shell Profile Modification>> |Both ~/.bash_profile and ~/.bashrc are files containing shell commands that are run when Bash is invoked. These files are executed in a user's context, either interactively or non-interactively, when a user logs in so that their environment is set correctly. Adversaries may abuse this to establish persistence by executing malicious content triggered by a user’s shell. |[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |104
+|<<bash-shell-profile-modification, Bash Shell Profile Modification>> |Both ~/.bash_profile and ~/.bashrc are files containing shell commands that are run when Bash is invoked. These files are executed in a user's context, either interactively or non-interactively, when a user logs in so that their environment is set correctly. Adversaries may abuse this to establish persistence by executing malicious content triggered by a user’s shell. |[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |104
 
-|<<binary-content-copy-via-cmd-exe, Binary Content Copy via Cmd.exe>> |Attackers may abuse cmd.exe commands to reassemble binary fragments into a malicious payload. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |3
+|<<binary-content-copy-via-cmd-exe, Binary Content Copy via Cmd.exe>> |Attackers may abuse cmd.exe commands to reassemble binary fragments into a malicious payload. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR] |None |3
 
-|<<binary-executed-from-shared-memory-directory, Binary Executed from Shared Memory Directory>> |Identifies the execution of a binary by root in Linux shared memory directories: (/dev/shm/, /run/shm/, /var/run/, /var/lock/). This activity is to be considered highly abnormal and should be investigated. Threat actors have placed executables used for persistence on high-uptime servers in these directories as system backdoors. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: BPFDoor], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<binary-executed-from-shared-memory-directory, Binary Executed from Shared Memory Directory>> |Identifies the execution of a binary by root in Linux shared memory directories: (/dev/shm/, /run/shm/, /var/run/, /var/lock/). This activity is to be considered highly abnormal and should be investigated. Threat actors have placed executables used for persistence on high-uptime servers in these directories as system backdoors. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: BPFDoor], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<bitsadmin-activity, Bitsadmin Activity>> |Windows Background Intelligent Transfer Service (BITS) is a low-bandwidth, asynchronous file transfer mechanism. Adversaries may abuse BITS to persist, download, execute, and even clean up after running malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |2
+|<<bitsadmin-activity, Bitsadmin Activity>> |Windows Background Intelligent Transfer Service (BITS) is a low-bandwidth, asynchronous file transfer mechanism. Adversaries may abuse BITS to persist, download, execute, and even clean up after running malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Rule Type: BBR] |None |2
 
-|<<browser-extension-install, Browser Extension Install>> |Identifies the install of browser extensions. Malicious browser extensions can be installed via app store downloads masquerading as legitimate extensions, social engineering, or by an adversary that has already compromised a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |2
+|<<browser-extension-install, Browser Extension Install>> |Identifies the install of browser extensions. Malicious browser extensions can be installed via app store downloads masquerading as legitimate extensions, social engineering, or by an adversary that has already compromised a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |2
 
-|<<bypass-uac-via-event-viewer, Bypass UAC via Event Viewer>> |Identifies User Account Control (UAC) bypass via eventvwr.exe. Attackers bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<bypass-uac-via-event-viewer, Bypass UAC via Event Viewer>> |Identifies User Account Control (UAC) bypass via eventvwr.exe. Attackers bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
 |<<cap-sys-admin-assigned-to-binary, CAP_SYS_ADMIN Assigned to Binary>> |Identifies instances where a binary is granted the CAP_SYS_ADMIN capability. In Linux, the CAP_SYS_ADMIN capability is a powerful and broad capability that allows a process to perform a range of system administration operations, such as mounting and unmounting filesystems, configuring network interfaces, and accessing hardware devices. Attackers may leverage a misconfiguration for exploitation in order to escalate their privileges to root. The rule identifies previously unknown processes executing with CAP_SYS_ADMIN capabilities through the use of the new terms rule type. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Rule Type: BBR] |8.11.0 |2
 
-|<<chkconfig-service-add, Chkconfig Service Add>> |Detects the use of the chkconfig binary to manually add a service for management by chkconfig. Threat actors may utilize this technique to maintain persistence on a system. When a new service is added, chkconfig ensures that the service has either a start or a kill entry in every runlevel and when the system is rebooted the service file added will run providing long-term persistence. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Lightning Framework], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<chkconfig-service-add, Chkconfig Service Add>> |Detects the use of the chkconfig binary to manually add a service for management by chkconfig. Threat actors may utilize this technique to maintain persistence on a system. When a new service is added, chkconfig ensures that the service has either a start or a kill entry in every runlevel and when the system is rebooted the service file added will run providing long-term persistence. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Lightning Framework], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<clearing-windows-console-history, Clearing Windows Console History>> |Identifies when a user attempts to clear console history. An adversary may clear the command history of a compromised account to conceal the actions undertaken during an intrusion. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<clearing-windows-console-history, Clearing Windows Console History>> |Identifies when a user attempts to clear console history. An adversary may clear the command history of a compromised account to conceal the actions undertaken during an intrusion. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<clearing-windows-event-logs, Clearing Windows Event Logs>> |Identifies attempts to clear or disable Windows event log stores using Windows wevetutil command. This is often done by attackers in an attempt to evade detection or destroy forensic evidence on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<clearing-windows-event-logs, Clearing Windows Event Logs>> |Identifies attempts to clear or disable Windows event log stores using Windows wevetutil command. This is often done by attackers in an attempt to evade detection or destroy forensic evidence on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<cobalt-strike-command-and-control-beacon, Cobalt Strike Command and Control Beacon>> |Cobalt Strike is a threat emulation platform commonly modified and used by adversaries to conduct network attack and exploitation campaigns. This rule detects a network activity algorithm leveraged by Cobalt Strike implant beacons for command and control. |[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |8.3.0 |105
+|<<cobalt-strike-command-and-control-beacon, Cobalt Strike Command and Control Beacon>> |Cobalt Strike is a threat emulation platform commonly modified and used by adversaries to conduct network attack and exploitation campaigns. This rule detects a network activity algorithm leveraged by Cobalt Strike implant beacons for command and control. |[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |None |105
 
-|<<code-signing-policy-modification-through-built-in-tools, Code Signing Policy Modification Through Built-in tools>> |Identifies attempts to disable/modify the code signing policy through system native utilities. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |7
+|<<code-signing-policy-modification-through-built-in-tools, Code Signing Policy Modification Through Built-in tools>> |Identifies attempts to disable/modify the code signing policy through system native utilities. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |8
 
-|<<code-signing-policy-modification-through-registry, Code Signing Policy Modification Through Registry>> |Identifies attempts to disable the code signing policy through the registry. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |9
+|<<code-signing-policy-modification-through-registry, Code Signing Policy Modification Through Registry>> |Identifies attempts to disable the code signing policy through the registry. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |10
 
-|<<command-execution-via-solarwinds-process, Command Execution via SolarWinds Process>> |A suspicious SolarWinds child process (Cmd.exe or Powershell.exe) was detected. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<command-execution-via-solarwinds-process, Command Execution via SolarWinds Process>> |A suspicious SolarWinds child process (Cmd.exe or Powershell.exe) was detected. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<command-prompt-network-connection, Command Prompt Network Connection>> |Identifies cmd.exe making a network connection. Adversaries could abuse cmd.exe to download or execute malware from a remote URL. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<command-prompt-network-connection, Command Prompt Network Connection>> |Identifies cmd.exe making a network connection. Adversaries could abuse cmd.exe to download or execute malware from a remote URL. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<command-shell-activity-started-via-rundll32, Command Shell Activity Started via RunDLL32>> |Identifies command shell activity started via RunDLL32, which is commonly abused by attackers to host malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<command-shell-activity-started-via-rundll32, Command Shell Activity Started via RunDLL32>> |Identifies command shell activity started via RunDLL32, which is commonly abused by attackers to host malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<component-object-model-hijacking, Component Object Model Hijacking>> |Identifies Component Object Model (COM) hijacking via registry modification. Adversaries may establish persistence by executing malicious content triggered by hijacked references to COM objects. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |113
+|<<component-object-model-hijacking, Component Object Model Hijacking>> |Identifies Component Object Model (COM) hijacking via registry modification. Adversaries may establish persistence by executing malicious content triggered by hijacked references to COM objects. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |113
 
-|<<compression-dll-loaded-by-unusual-process, Compression DLL Loaded by Unusual Process>> |Identifies the image load of a compression DLL. Adversaries will often compress and encrypt data in preparation for exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |3
+|<<compression-dll-loaded-by-unusual-process, Compression DLL Loaded by Unusual Process>> |Identifies the image load of a compression DLL. Adversaries will often compress and encrypt data in preparation for exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Rule Type: BBR] |None |3
 
-|<<conhost-spawned-by-suspicious-parent-process, Conhost Spawned By Suspicious Parent Process>> |Detects when the Console Window Host (conhost.exe) process is spawned by a suspicious parent process, which could be indicative of code injection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<conhost-spawned-by-suspicious-parent-process, Conhost Spawned By Suspicious Parent Process>> |Detects when the Console Window Host (conhost.exe) process is spawned by a suspicious parent process, which could be indicative of code injection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<connection-to-commonly-abused-free-ssl-certificate-providers, Connection to Commonly Abused Free SSL Certificate Providers>> |Identifies unusual processes connecting to domains using known free SSL certificates. Adversaries may employ a known encryption algorithm to conceal command and control traffic. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<connection-to-commonly-abused-free-ssl-certificate-providers, Connection to Commonly Abused Free SSL Certificate Providers>> |Identifies unusual processes connecting to domains using known free SSL certificates. Adversaries may employ a known encryption algorithm to conceal command and control traffic. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<connection-to-commonly-abused-web-services, Connection to Commonly Abused Web Services>> |Adversaries may implement command and control (C2) communications that use common web services to hide their activity. This attack technique is typically targeted at an organization and uses web services common to the victim network, which allows the adversary to blend into legitimate traffic activity. These popular services are typically targeted since they have most likely been used before compromise, which helps malicious traffic blend in. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |113
+|<<connection-to-commonly-abused-web-services, Connection to Commonly Abused Web Services>> |Adversaries may implement command and control (C2) communications that use common web services to hide their activity. This attack technique is typically targeted at an organization and uses web services common to the victim network, which allows the adversary to blend into legitimate traffic activity. These popular services are typically targeted since they have most likely been used before compromise, which helps malicious traffic blend in. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |113
 
-|<<connection-to-external-network-via-telnet, Connection to External Network via Telnet>> |Telnet provides a command line interface for communication with a remote device or server. This rule identifies Telnet network connections to publicly routable IP addresses. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |8.3.0 |107
+|<<connection-to-external-network-via-telnet, Connection to External Network via Telnet>> |Telnet provides a command line interface for communication with a remote device or server. This rule identifies Telnet network connections to publicly routable IP addresses. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |None |107
 
-|<<connection-to-internal-network-via-telnet, Connection to Internal Network via Telnet>> |Telnet provides a command line interface for communication with a remote device or server. This rule identifies Telnet network connections to non-publicly routable IP addresses. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |8.3.0 |107
+|<<connection-to-internal-network-via-telnet, Connection to Internal Network via Telnet>> |Telnet provides a command line interface for communication with a remote device or server. This rule identifies Telnet network connections to non-publicly routable IP addresses. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |None |107
 
-|<<container-management-utility-run-inside-a-container, Container Management Utility Run Inside A Container>> |This rule detects when a container management binary is run from inside a container. These binaries are critical components of many containerized environments, and their presence and execution in unauthorized containers could indicate compromise or a misconfiguration. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |8.8.0 |2
+|<<container-management-utility-run-inside-a-container, Container Management Utility Run Inside A Container>> |This rule detects when a container management binary is run from inside a container. These binaries are critical components of many containerized environments, and their presence and execution in unauthorized containers could indicate compromise or a misconfiguration. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |None |2
 
-|<<container-workload-protection, Container Workload Protection>> |Generates a detection alert each time a 'Container Workload Protection' alert is received. Enabling this rule allows you to immediately begin triaging and investigating these alerts. |[Data Source: Elastic Defend for Containers], [Domain: Container] |8.8.0 |4
+|<<container-workload-protection, Container Workload Protection>> |Generates a detection alert each time a 'Container Workload Protection' alert is received. Enabling this rule allows you to immediately begin triaging and investigating these alerts. |[Data Source: Elastic Defend for Containers], [Domain: Container] |None |4
 
-|<<control-panel-process-with-unusual-arguments, Control Panel Process with Unusual Arguments>> |Identifies unusual instances of Control Panel with suspicious keywords or paths in the process command line value. Adversaries may abuse control.exe to proxy execution of malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<control-panel-process-with-unusual-arguments, Control Panel Process with Unusual Arguments>> |Identifies unusual instances of Control Panel with suspicious keywords or paths in the process command line value. Adversaries may abuse control.exe to proxy execution of malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<creation-of-hidden-files-and-directories-via-commandline, Creation of Hidden Files and Directories via CommandLine>> |Users can mark specific files as hidden simply by putting a "." as the first character in the file or folder name. Adversaries can use this to their advantage to hide files and folders on the system for persistence and defense evasion. This rule looks for hidden files or folders in common writable directories. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |110
+|<<creation-of-hidden-files-and-directories-via-commandline, Creation of Hidden Files and Directories via CommandLine>> |Users can mark specific files as hidden simply by putting a "." as the first character in the file or folder name. Adversaries can use this to their advantage to hide files and folders on the system for persistence and defense evasion. This rule looks for hidden files or folders in common writable directories. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |110
 
-|<<creation-of-hidden-launch-agent-or-daemon, Creation of Hidden Launch Agent or Daemon>> |Identifies the creation of a hidden launch agent or daemon. An adversary may establish persistence by installing a new launch agent or daemon which executes at login. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |107
+|<<creation-of-hidden-launch-agent-or-daemon, Creation of Hidden Launch Agent or Daemon>> |Identifies the creation of a hidden launch agent or daemon. An adversary may establish persistence by installing a new launch agent or daemon which executes at login. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |107
 
-|<<creation-of-hidden-login-item-via-apple-script, Creation of Hidden Login Item via Apple Script>> |Identifies the execution of osascript to create a hidden login item. This may indicate an attempt to persist a malicious program while concealing its presence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |108
+|<<creation-of-hidden-login-item-via-apple-script, Creation of Hidden Login Item via Apple Script>> |Identifies the execution of osascript to create a hidden login item. This may indicate an attempt to persist a malicious program while concealing its presence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Defend] |None |108
 
-|<<creation-of-hidden-shared-object-file, Creation of Hidden Shared Object File>> |Identifies the creation of a hidden shared object (.so) file. Users can mark specific files as hidden simply by putting a "." as the first character in the file or folder name. Adversaries can use this to their advantage to hide files and folders on the system for persistence and defense evasion. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<creation-of-hidden-shared-object-file, Creation of Hidden Shared Object File>> |Identifies the creation of a hidden shared object (.so) file. Users can mark specific files as hidden simply by putting a "." as the first character in the file or folder name. Adversaries can use this to their advantage to hide files and folders on the system for persistence and defense evasion. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<creation-of-kernel-module, Creation of Kernel Module>> |Identifies activity related to loading kernel modules on Linux via creation of new ko files in the LKM directory. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |3
+|<<creation-of-kernel-module, Creation of Kernel Module>> |Identifies activity related to loading kernel modules on Linux via creation of new ko files in the LKM directory. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |3
 
-|<<creation-of-settingcontent-ms-files, Creation of SettingContent-ms Files>> |Identifies the suspicious creation of SettingContents-ms files, which have been used in attacks to achieve code execution while evading defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |3
+|<<creation-of-settingcontent-ms-files, Creation of SettingContent-ms Files>> |Identifies the suspicious creation of SettingContents-ms files, which have been used in attacks to achieve code execution while evading defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR] |None |3
 
-|<<creation-of-a-dns-named-record, Creation of a DNS-Named Record>> |Active Directory Integrated DNS (ADIDNS) is one of the core components of AD DS, leveraging AD's access control and replication to maintain domain consistency. It stores DNS zones as AD objects, a feature that, while robust, introduces some security issues because of the default permission (Any authenticated users) to create DNS-named records. Attackers can perform Dynamic Spoofing attacks, where they monitor LLMNR/NBT-NS requests and create DNS-named records to target systems that are requested from multiple systems. They can also create specific records to target specific services, such as wpad, for spoofing attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Use Case: Active Directory Monitoring] |8.3.0 |1
+|<<creation-of-a-dns-named-record, Creation of a DNS-Named Record>> |Active Directory Integrated DNS (ADIDNS) is one of the core components of AD DS, leveraging AD's access control and replication to maintain domain consistency. It stores DNS zones as AD objects, a feature that, while robust, introduces some security issues because of the default permission (Any authenticated users) to create DNS-named records. Attackers can perform Dynamic Spoofing attacks, where they monitor LLMNR/NBT-NS requests and create DNS-named records to target systems that are requested from multiple systems. They can also create specific records to target specific services, such as wpad, for spoofing attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Use Case: Active Directory Monitoring] |None |1
 
-|<<creation-of-a-hidden-local-user-account, Creation of a Hidden Local User Account>> |Identifies the creation of a hidden local user account by appending the dollar sign to the account name. This is sometimes done by attackers to increase access to a system and avoid appearing in the results of accounts listing using the net users command. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<creation-of-a-hidden-local-user-account, Creation of a Hidden Local User Account>> |Identifies the creation of a hidden local user account by appending the dollar sign to the account name. This is sometimes done by attackers to increase access to a system and avoid appearing in the results of accounts listing using the net users command. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<creation-or-modification-of-domain-backup-dpapi-private-key, Creation or Modification of Domain Backup DPAPI private key>> |Identifies the creation or modification of Domain Backup private keys. Adversaries may extract the Data Protection API (DPAPI) domain backup key from a Domain Controller (DC) to be able to decrypt any domain user master key file. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<creation-or-modification-of-domain-backup-dpapi-private-key, Creation or Modification of Domain Backup DPAPI private key>> |Identifies the creation or modification of Domain Backup private keys. Adversaries may extract the Data Protection API (DPAPI) domain backup key from a Domain Controller (DC) to be able to decrypt any domain user master key file. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |210
 
-|<<creation-or-modification-of-root-certificate, Creation or Modification of Root Certificate>> |Identifies the creation or modification of a local trusted root certificate in Windows. The install of a malicious root certificate would allow an attacker the ability to masquerade malicious files as valid signed components from any entity (for example, Microsoft). It could also allow an attacker to decrypt SSL traffic. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<creation-or-modification-of-root-certificate, Creation or Modification of Root Certificate>> |Identifies the creation or modification of a local trusted root certificate in Windows. The install of a malicious root certificate would allow an attacker the ability to masquerade malicious files as valid signed components from any entity (for example, Microsoft). It could also allow an attacker to decrypt SSL traffic. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<creation-or-modification-of-a-new-gpo-scheduled-task-or-service, Creation or Modification of a new GPO Scheduled Task or Service>> |Detects the creation or modification of a new Group Policy based scheduled task or service. These methods are used for legitimate system administration, but can also be abused by an attacker with domain admin permissions to execute a malicious payload remotely on all or a subset of the domain joined machines. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<creation-or-modification-of-a-new-gpo-scheduled-task-or-service, Creation or Modification of a new GPO Scheduled Task or Service>> |Detects the creation or modification of a new Group Policy based scheduled task or service. These methods are used for legitimate system administration, but can also be abused by an attacker with domain admin permissions to execute a malicious payload remotely on all or a subset of the domain joined machines. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<credential-acquisition-via-registry-hive-dumping, Credential Acquisition via Registry Hive Dumping>> |Identifies attempts to export a registry hive which may contain credentials using the Windows reg.exe tool. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<credential-acquisition-via-registry-hive-dumping, Credential Acquisition via Registry Hive Dumping>> |Identifies attempts to export a registry hive which may contain credentials using the Windows reg.exe tool. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<credential-dumping-detected-elastic-endgame, Credential Dumping - Detected - Elastic Endgame>> |Elastic Endgame detected Credential Dumping. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Credential Access] |8.3.0 |103
+|<<credential-dumping-detected-elastic-endgame, Credential Dumping - Detected - Elastic Endgame>> |Elastic Endgame detected Credential Dumping. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Credential Access] |None |103
 
-|<<credential-dumping-prevented-elastic-endgame, Credential Dumping - Prevented - Elastic Endgame>> |Elastic Endgame prevented Credential Dumping. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Credential Access] |8.3.0 |103
+|<<credential-dumping-prevented-elastic-endgame, Credential Dumping - Prevented - Elastic Endgame>> |Elastic Endgame prevented Credential Dumping. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Credential Access] |None |103
 
-|<<credential-manipulation-detected-elastic-endgame, Credential Manipulation - Detected - Elastic Endgame>> |Elastic Endgame detected Credential Manipulation. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<credential-manipulation-detected-elastic-endgame, Credential Manipulation - Detected - Elastic Endgame>> |Elastic Endgame detected Credential Manipulation. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |103
 
-|<<credential-manipulation-prevented-elastic-endgame, Credential Manipulation - Prevented - Elastic Endgame>> |Elastic Endgame prevented Credential Manipulation. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<credential-manipulation-prevented-elastic-endgame, Credential Manipulation - Prevented - Elastic Endgame>> |Elastic Endgame prevented Credential Manipulation. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |103
 
-|<<cron-job-created-or-changed-by-previously-unknown-process, Cron Job Created or Changed by Previously Unknown Process>> |Linux cron jobs are scheduled tasks that can be leveraged by malicious actors for persistence, privilege escalation and command execution. By creating or modifying cron job configurations, attackers can execute malicious commands or scripts at predefined intervals, ensuring their continued presence and enabling unauthorized activities. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |9
+|<<cron-job-created-or-changed-by-previously-unknown-process, Cron Job Created or Changed by Previously Unknown Process>> |Linux cron jobs are scheduled tasks that can be leveraged by malicious actors for persistence, privilege escalation and command execution. By creating or modifying cron job configurations, attackers can execute malicious commands or scripts at predefined intervals, ensuring their continued presence and enabling unauthorized activities. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |10
 
-|<<cyberark-privileged-access-security-error, CyberArk Privileged Access Security Error>> |Identifies the occurrence of a CyberArk Privileged Access Security (PAS) error level audit event. The event.code correlates to the CyberArk Vault Audit Action Code. |[Data Source: CyberArk PAS], [Use Case: Log Auditing], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |102
+|<<cyberark-privileged-access-security-error, CyberArk Privileged Access Security Error>> |Identifies the occurrence of a CyberArk Privileged Access Security (PAS) error level audit event. The event.code correlates to the CyberArk Vault Audit Action Code. |[Data Source: CyberArk PAS], [Use Case: Log Auditing], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |102
 
-|<<cyberark-privileged-access-security-recommended-monitor, CyberArk Privileged Access Security Recommended Monitor>> |Identifies the occurrence of a CyberArk Privileged Access Security (PAS) non-error level audit event which is recommended for monitoring by the vendor. The event.code correlates to the CyberArk Vault Audit Action Code. |[Data Source: CyberArk PAS], [Use Case: Log Auditing], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |102
+|<<cyberark-privileged-access-security-recommended-monitor, CyberArk Privileged Access Security Recommended Monitor>> |Identifies the occurrence of a CyberArk Privileged Access Security (PAS) non-error level audit event which is recommended for monitoring by the vendor. The event.code correlates to the CyberArk Vault Audit Action Code. |[Data Source: CyberArk PAS], [Use Case: Log Auditing], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |102
 
-|<<dns-tunneling, DNS Tunneling>> |A machine learning job detected unusually large numbers of DNS queries for a single top-level DNS domain, which is often used for DNS tunneling. DNS tunneling can be used for command-and-control, persistence, or data exfiltration activity. For example, dnscat tends to generate many DNS questions for a top-level domain as it uses the DNS protocol to tunnel data. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |8.3.0 |103
+|<<dns-tunneling, DNS Tunneling>> |A machine learning job detected unusually large numbers of DNS queries for a single top-level DNS domain, which is often used for DNS tunneling. DNS tunneling can be used for command-and-control, persistence, or data exfiltration activity. For example, dnscat tends to generate many DNS questions for a top-level domain as it uses the DNS protocol to tunnel data. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |None |103
 
-|<<dns-over-https-enabled-via-registry, DNS-over-HTTPS Enabled via Registry>> |Identifies when a user enables DNS-over-HTTPS. This can be used to hide internet activity or the process of exfiltrating data. With this enabled, an organization will lose visibility into data such as query type, response, and originating IP, which are used to determine bad actors. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<dns-over-https-enabled-via-registry, DNS-over-HTTPS Enabled via Registry>> |Identifies when a user enables DNS-over-HTTPS. This can be used to hide internet activity or the process of exfiltrating data. With this enabled, an organization will lose visibility into data such as query type, response, and originating IP, which are used to determine bad actors. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<default-cobalt-strike-team-server-certificate, Default Cobalt Strike Team Server Certificate>> |This rule detects the use of the default Cobalt Strike Team Server TLS certificate. Cobalt Strike is software for Adversary Simulations and Red Team Operations which are security assessments that replicate the tactics and techniques of an advanced adversary in a network. Modifications to the Packetbeat configuration can be made to include MD5 and SHA256 hashing algorithms (the default is SHA1). See the References section for additional information on module configuration. |[Tactic: Command and Control], [Threat: Cobalt Strike], [Use Case: Threat Detection], [Domain: Endpoint] |8.3.0 |104
+|<<default-cobalt-strike-team-server-certificate, Default Cobalt Strike Team Server Certificate>> |This rule detects the use of the default Cobalt Strike Team Server TLS certificate. Cobalt Strike is software for Adversary Simulations and Red Team Operations which are security assessments that replicate the tactics and techniques of an advanced adversary in a network. Modifications to the Packetbeat configuration can be made to include MD5 and SHA256 hashing algorithms (the default is SHA1). See the References section for additional information on module configuration. |[Tactic: Command and Control], [Threat: Cobalt Strike], [Use Case: Threat Detection], [Domain: Endpoint] |None |104
 
-|<<delayed-execution-via-ping, Delayed Execution via Ping>> |Identifies the execution of commonly abused Windows utilities via a delayed Ping execution. This behavior is often observed during malware installation and is consistent with an attacker attempting to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |2
+|<<delayed-execution-via-ping, Delayed Execution via Ping>> |Identifies the execution of commonly abused Windows utilities via a delayed Ping execution. This behavior is often observed during malware installation and is consistent with an attacker attempting to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |3
 
-|<<delete-volume-usn-journal-with-fsutil, Delete Volume USN Journal with Fsutil>> |Identifies use of the fsutil.exe to delete the volume USNJRNL. This technique is used by attackers to eliminate evidence of files created during post-exploitation activities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |109
+|<<delete-volume-usn-journal-with-fsutil, Delete Volume USN Journal with Fsutil>> |Identifies use of the fsutil.exe to delete the volume USNJRNL. This technique is used by attackers to eliminate evidence of files created during post-exploitation activities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |109
 
-|<<deleting-backup-catalogs-with-wbadmin, Deleting Backup Catalogs with Wbadmin>> |Identifies use of the wbadmin.exe to delete the backup catalog. Ransomware and other malware may do this to prevent system recovery. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<deleting-backup-catalogs-with-wbadmin, Deleting Backup Catalogs with Wbadmin>> |Identifies use of the wbadmin.exe to delete the backup catalog. Ransomware and other malware may do this to prevent system recovery. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<direct-outbound-smb-connection, Direct Outbound SMB Connection>> |Identifies unexpected processes making network connections over port 445. Windows File Sharing is typically implemented over Server Message Block (SMB), which communicates between hosts using port 445. When legitimate, these network connections are established by the kernel. Processes making 445/tcp connections may be port scanners, exploits, or suspicious user-level processes moving laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |110
+|<<direct-outbound-smb-connection, Direct Outbound SMB Connection>> |Identifies unexpected processes making network connections over port 445. Windows File Sharing is typically implemented over Server Message Block (SMB), which communicates between hosts using port 445. When legitimate, these network connections are established by the kernel. Processes making 445/tcp connections may be port scanners, exploits, or suspicious user-level processes moving laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |110
 
-|<<disable-windows-event-and-security-logs-using-built-in-tools, Disable Windows Event and Security Logs Using Built-in Tools>> |Identifies attempts to disable EventLog via the logman Windows utility, PowerShell, or auditpol. This is often done by attackers in an attempt to evade detection on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<disable-windows-event-and-security-logs-using-built-in-tools, Disable Windows Event and Security Logs Using Built-in Tools>> |Identifies attempts to disable EventLog via the logman Windows utility, PowerShell, or auditpol. This is often done by attackers in an attempt to evade detection on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<disable-windows-firewall-rules-via-netsh, Disable Windows Firewall Rules via Netsh>> |Identifies use of the netsh.exe to disable or weaken the local firewall. Attackers will use this command line tool to disable the firewall during troubleshooting or to enable network mobility. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<disable-windows-firewall-rules-via-netsh, Disable Windows Firewall Rules via Netsh>> |Identifies use of the netsh.exe to disable or weaken the local firewall. Attackers will use this command line tool to disable the firewall during troubleshooting or to enable network mobility. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<disabling-user-account-control-via-registry-modification, Disabling User Account Control via Registry Modification>> |User Account Control (UAC) can help mitigate the impact of malware on Windows hosts. With UAC, apps and tasks always run in the security context of a non-administrator account, unless an administrator specifically authorizes administrator-level access to the system. This rule identifies registry value changes to bypass User Access Control (UAC) protection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<disabling-user-account-control-via-registry-modification, Disabling User Account Control via Registry Modification>> |User Account Control (UAC) can help mitigate the impact of malware on Windows hosts. With UAC, apps and tasks always run in the security context of a non-administrator account, unless an administrator specifically authorizes administrator-level access to the system. This rule identifies registry value changes to bypass User Access Control (UAC) protection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<disabling-windows-defender-security-settings-via-powershell, Disabling Windows Defender Security Settings via PowerShell>> |Identifies use of the Set-MpPreference PowerShell command to disable or weaken certain Windows Defender settings. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<disabling-windows-defender-security-settings-via-powershell, Disabling Windows Defender Security Settings via PowerShell>> |Identifies use of the Set-MpPreference PowerShell command to disable or weaken certain Windows Defender settings. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<discovery-of-domain-groups, Discovery of Domain Groups>> |Identifies the execution of Linux built-in commands related to account or group enumeration. Adversaries may use account and group information to orient themselves before deciding how to act. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |2
+|<<discovery-of-domain-groups, Discovery of Domain Groups>> |Identifies the execution of Linux built-in commands related to account or group enumeration. Adversaries may use account and group information to orient themselves before deciding how to act. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |2
 
-|<<discovery-of-internet-capabilities-via-built-in-tools, Discovery of Internet Capabilities via Built-in Tools>> |Identifies the use of built-in tools attackers can use to check for Internet connectivity on compromised systems. These results may be used to determine communication capabilities with C2 servers, or to identify routes, redirectors, and proxy servers. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |8.6.0 |102
+|<<discovery-of-internet-capabilities-via-built-in-tools, Discovery of Internet Capabilities via Built-in Tools>> |Identifies the use of built-in tools attackers can use to check for Internet connectivity on compromised systems. These results may be used to determine communication capabilities with C2 servers, or to identify routes, redirectors, and proxy servers. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |None |102
 
-|<<domain-added-to-google-workspace-trusted-domains, Domain Added to Google Workspace Trusted Domains>> |Detects when a domain is added to the list of trusted Google Workspace domains. An adversary may add a trusted domain in order to collect and exfiltrate data from their target’s organization with less restrictive security controls. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Defense Evasion], [Resources: Investigation Guide] |8.4.0 |205
+|<<domain-added-to-google-workspace-trusted-domains, Domain Added to Google Workspace Trusted Domains>> |Detects when a domain is added to the list of trusted Google Workspace domains. An adversary may add a trusted domain in order to collect and exfiltrate data from their target’s organization with less restrictive security controls. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Defense Evasion], [Resources: Investigation Guide] |None |205
 
-|<<downloaded-shortcut-files, Downloaded Shortcut Files>> |Identifies .lnk shortcut file downloaded from outside the local network. These shortcut files are commonly used in phishing campaigns. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |2
+|<<downloaded-shortcut-files, Downloaded Shortcut Files>> |Identifies .lnk shortcut file downloaded from outside the local network. These shortcut files are commonly used in phishing campaigns. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |2
 
-|<<downloaded-url-files, Downloaded URL Files>> |Identifies .url shortcut files downloaded from outside the local network. These shortcut files are commonly used in phishing campaigns. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |2
+|<<downloaded-url-files, Downloaded URL Files>> |Identifies .url shortcut files downloaded from outside the local network. These shortcut files are commonly used in phishing campaigns. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR] |None |2
 
-|<<dumping-account-hashes-via-built-in-commands, Dumping Account Hashes via Built-In Commands>> |Identifies the execution of macOS built-in commands used to dump user account hashes. Adversaries may attempt to dump credentials to obtain account login information in the form of a hash. These hashes can be cracked or leveraged for lateral movement. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.3.0 |106
+|<<dumping-account-hashes-via-built-in-commands, Dumping Account Hashes via Built-In Commands>> |Identifies the execution of macOS built-in commands used to dump user account hashes. Adversaries may attempt to dump credentials to obtain account login information in the form of a hash. These hashes can be cracked or leveraged for lateral movement. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |106
 
-|<<dumping-of-keychain-content-via-security-command, Dumping of Keychain Content via Security Command>> |Adversaries may dump the content of the keychain storage data from a system to acquire credentials. Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features, including Wi-Fi and website passwords, secure notes, certificates, and Kerberos. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.3.0 |107
+|<<dumping-of-keychain-content-via-security-command, Dumping of Keychain Content via Security Command>> |Adversaries may dump the content of the keychain storage data from a system to acquire credentials. Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features, including Wi-Fi and website passwords, secure notes, certificates, and Kerberos. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |107
 
-|<<dynamic-linker-copy, Dynamic Linker Copy>> |Detects the copying of the Linux dynamic loader binary and subsequent file creation for the purpose of creating a backup copy. This technique was seen recently being utilized by Linux malware prior to patching the dynamic loader in order to inject and preload a malicious shared object file. This activity should never occur and if it does then it should be considered highly suspicious or malicious. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Orbit], [Data Source: Elastic Defend] |8.3.0 |108
+|<<dynamic-linker-copy, Dynamic Linker Copy>> |Detects the copying of the Linux dynamic loader binary and subsequent file creation for the purpose of creating a backup copy. This technique was seen recently being utilized by Linux malware prior to patching the dynamic loader in order to inject and preload a malicious shared object file. This activity should never occur and if it does then it should be considered highly suspicious or malicious. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Orbit], [Data Source: Elastic Defend] |None |109
 
-|<<ec2-ami-shared-with-another-account, EC2 AMI Shared with Another Account>> |Identifies an AWS Amazon Machine Image (AMI) being shared with another AWS account. Adversaries with access may share an AMI with an external AWS account as a means of data exfiltration. AMIs can contain secrets, bash histories, code artifacts, and other sensitive data that adversaries may abuse if shared with unauthorized accounts. AMIs can be made publicly available accidentally as well. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Threat Detection], [Tactic: Exfiltration] |8.9.0 |1
+|<<ec2-ami-shared-with-another-account, EC2 AMI Shared with Another Account>> |Identifies an AWS Amazon Machine Image (AMI) being shared with another AWS account. Adversaries with access may share an AMI with an external AWS account as a means of data exfiltration. AMIs can contain secrets, bash histories, code artifacts, and other sensitive data that adversaries may abuse if shared with unauthorized accounts. AMIs can be made publicly available accidentally as well. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Threat Detection], [Tactic: Exfiltration] |None |2
 
-|<<esxi-discovery-via-find, ESXI Discovery via Find>> |Identifies instances where the 'find' command is started on a Linux system with arguments targeting specific VM-related paths, such as "/etc/vmware/", "/usr/lib/vmware/", or "/vmfs/*". These paths are associated with VMware virtualization software, and their presence in the find command arguments may indicate that a threat actor is attempting to search for, analyze, or manipulate VM-related files and configurations on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.5.0 |6
+|<<esxi-discovery-via-find, ESXI Discovery via Find>> |Identifies instances where the 'find' command is started on a Linux system with arguments targeting specific VM-related paths, such as "/etc/vmware/", "/usr/lib/vmware/", or "/vmfs/*". These paths are associated with VMware virtualization software, and their presence in the find command arguments may indicate that a threat actor is attempting to search for, analyze, or manipulate VM-related files and configurations on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |6
 
-|<<esxi-discovery-via-grep, ESXI Discovery via Grep>> |Identifies instances where a process named 'grep', 'egrep', or 'pgrep' is started on a Linux system with arguments related to virtual machine (VM) files, such as "vmdk", "vmx", "vmxf", "vmsd", "vmsn", "vswp", "vmss", "nvram", or "vmem". These file extensions are associated with VM-related file formats, and their presence in grep command arguments may indicate that a threat actor is attempting to search for, analyze, or manipulate VM files on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.5.0 |6
+|<<esxi-discovery-via-grep, ESXI Discovery via Grep>> |Identifies instances where a process named 'grep', 'egrep', or 'pgrep' is started on a Linux system with arguments related to virtual machine (VM) files, such as "vmdk", "vmx", "vmxf", "vmsd", "vmsn", "vswp", "vmss", "nvram", or "vmem". These file extensions are associated with VM-related file formats, and their presence in grep command arguments may indicate that a threat actor is attempting to search for, analyze, or manipulate VM files on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |6
 
-|<<esxi-timestomping-using-touch-command, ESXI Timestomping using Touch Command>> |Identifies instances where the 'touch' command is executed on a Linux system with the "-r" flag, which is used to modify the timestamp of a file based on another file's timestamp. The rule targets specific VM-related paths, such as "/etc/vmware/", "/usr/lib/vmware/", or "/vmfs/*". These paths are associated with VMware virtualization software, and their presence in the touch command arguments may indicate that a threat actor is attempting to tamper with timestamps of VM-related files and configurations on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.5.0 |8
+|<<esxi-timestomping-using-touch-command, ESXI Timestomping using Touch Command>> |Identifies instances where the 'touch' command is executed on a Linux system with the "-r" flag, which is used to modify the timestamp of a file based on another file's timestamp. The rule targets specific VM-related paths, such as "/etc/vmware/", "/usr/lib/vmware/", or "/vmfs/*". These paths are associated with VMware virtualization software, and their presence in the touch command arguments may indicate that a threat actor is attempting to tamper with timestamps of VM-related files and configurations on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |8
 
-|<<eggshell-backdoor-execution, EggShell Backdoor Execution>> |Identifies the execution of and EggShell Backdoor. EggShell is a known post exploitation tool for macOS and Linux. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |103
+|<<eggshell-backdoor-execution, EggShell Backdoor Execution>> |Identifies the execution of and EggShell Backdoor. EggShell is a known post exploitation tool for macOS and Linux. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |103
 
-|<<elastic-agent-service-terminated, Elastic Agent Service Terminated>> |Identifies the Elastic endpoint agent has stopped and is no longer running on the host. Adversaries may attempt to disable security monitoring tools in an attempt to evade detection or prevention capabilities during an intrusion. This may also indicate an issue with the agent itself and should be addressed to ensure defensive measures are back in a stable state. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |106
+|<<elastic-agent-service-terminated, Elastic Agent Service Terminated>> |Identifies the Elastic endpoint agent has stopped and is no longer running on the host. Adversaries may attempt to disable security monitoring tools in an attempt to evade detection or prevention capabilities during an intrusion. This may also indicate an issue with the agent itself and should be addressed to ensure defensive measures are back in a stable state. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |106
 
-|<<emond-rules-creation-or-modification, Emond Rules Creation or Modification>> |Identifies the creation or modification of the Event Monitor Daemon (emond) rules. Adversaries may abuse this service by writing a rule to execute commands when a defined event occurs, such as system start up or user authentication. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |107
+|<<emond-rules-creation-or-modification, Emond Rules Creation or Modification>> |Identifies the creation or modification of the Event Monitor Daemon (emond) rules. Adversaries may abuse this service by writing a rule to execute commands when a defined event occurs, such as system start up or user authentication. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |107
 
-|<<enable-host-network-discovery-via-netsh, Enable Host Network Discovery via Netsh>> |Identifies use of the netsh.exe program to enable host discovery via the network. Attackers can use this command-line tool to weaken the host firewall settings. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<enable-host-network-discovery-via-netsh, Enable Host Network Discovery via Netsh>> |Identifies use of the netsh.exe program to enable host discovery via the network. Attackers can use this command-line tool to weaken the host firewall settings. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<encoded-executable-stored-in-the-registry, Encoded Executable Stored in the Registry>> |Identifies registry write modifications to hide an encoded portable executable. This could be indicative of adversary defense evasion by avoiding the storing of malicious content directly on disk. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<encoded-executable-stored-in-the-registry, Encoded Executable Stored in the Registry>> |Identifies registry write modifications to hide an encoded portable executable. This could be indicative of adversary defense evasion by avoiding the storing of malicious content directly on disk. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |209
 
-|<<encrypting-files-with-winrar-or-7z, Encrypting Files with WinRar or 7z>> |Identifies use of WinRar or 7z to create an encrypted files. Adversaries will often compress and encrypt data in preparation for exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<encrypting-files-with-winrar-or-7z, Encrypting Files with WinRar or 7z>> |Identifies use of WinRar or 7z to create an encrypted files. Adversaries will often compress and encrypt data in preparation for exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<endpoint-security, Endpoint Security>> |Generates a detection alert each time an Elastic Endpoint Security alert is received. Enabling this rule allows you to immediately begin investigating your Endpoint alerts. |[Data Source: Elastic Defend] |8.3.0 |103
+|<<endpoint-security, Endpoint Security>> |Generates a detection alert each time an Elastic Endpoint Security alert is received. Enabling this rule allows you to immediately begin investigating your Endpoint alerts. |[Data Source: Elastic Defend] |None |103
 
-|<<enumerating-domain-trusts-via-dsquery-exe, Enumerating Domain Trusts via DSQUERY.EXE>> |Identifies the use of dsquery.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate trust relationships that may be used for Lateral Movement opportunities in Windows multi-domain forest environments. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |7
+|<<enumerating-domain-trusts-via-dsquery-exe, Enumerating Domain Trusts via DSQUERY.EXE>> |Identifies the use of dsquery.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate trust relationships that may be used for Lateral Movement opportunities in Windows multi-domain forest environments. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |8
 
-|<<enumerating-domain-trusts-via-nltest-exe, Enumerating Domain Trusts via NLTEST.EXE>> |Identifies the use of nltest.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate domain trusts and gain insight into trust relationships, as well as the state of Domain Controller (DC) replication in a Microsoft Windows NT Domain. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |110
+|<<enumerating-domain-trusts-via-nltest-exe, Enumerating Domain Trusts via NLTEST.EXE>> |Identifies the use of nltest.exe for domain trust discovery purposes. Adversaries may use this command-line utility to enumerate domain trusts and gain insight into trust relationships, as well as the state of Domain Controller (DC) replication in a Microsoft Windows NT Domain. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |111
 
-|<<enumeration-command-spawned-via-wmiprvse, Enumeration Command Spawned via WMIPrvSE>> |Identifies native Windows host and network enumeration commands spawned by the Windows Management Instrumentation Provider Service (WMIPrvSE). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<enumeration-command-spawned-via-wmiprvse, Enumeration Command Spawned via WMIPrvSE>> |Identifies native Windows host and network enumeration commands spawned by the Windows Management Instrumentation Provider Service (WMIPrvSE). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<enumeration-of-administrator-accounts, Enumeration of Administrator Accounts>> |Identifies instances of lower privilege accounts enumerating Administrator accounts or groups using built-in Windows tools. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<enumeration-of-administrator-accounts, Enumeration of Administrator Accounts>> |Identifies instances of lower privilege accounts enumerating Administrator accounts or groups using built-in Windows tools. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<enumeration-of-kernel-modules, Enumeration of Kernel Modules>> |Loadable Kernel Modules (or LKMs) are pieces of code that can be loaded and unloaded into the kernel upon demand. They extend the functionality of the kernel without the need to reboot the system. This identifies attempts to enumerate information about a kernel module. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.6.0 |209
+|<<enumeration-of-kernel-modules, Enumeration of Kernel Modules>> |Loadable Kernel Modules (or LKMs) are pieces of code that can be loaded and unloaded into the kernel upon demand. They extend the functionality of the kernel without the need to reboot the system. This identifies attempts to enumerate information about a kernel module. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |209
 
-|<<enumeration-of-kernel-modules-via-proc, Enumeration of Kernel Modules via Proc>> |Loadable Kernel Modules (or LKMs) are pieces of code that can be loaded and unloaded into the kernel upon demand. They extend the functionality of the kernel without the need to reboot the system. This identifies attempts to enumerate information about a kernel module using the /proc/modules filesystem. This filesystem is used by utilities such as lsmod and kmod to list the available kernel modules. |[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |8.6.0 |106
+|<<enumeration-of-kernel-modules-via-proc, Enumeration of Kernel Modules via Proc>> |Loadable Kernel Modules (or LKMs) are pieces of code that can be loaded and unloaded into the kernel upon demand. They extend the functionality of the kernel without the need to reboot the system. This identifies attempts to enumerate information about a kernel module using the /proc/modules filesystem. This filesystem is used by utilities such as lsmod and kmod to list the available kernel modules. |[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |None |106
 
 |<<enumeration-of-privileged-local-groups-membership, Enumeration of Privileged Local Groups Membership>> |Identifies instances of an unusual process enumerating built-in Windows privileged local groups membership like Administrators or Remote Desktop users. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide] |8.6.0 |211
 
-|<<enumeration-of-users-or-groups-via-built-in-commands, Enumeration of Users or Groups via Built-in Commands>> |Identifies the execution of macOS built-in commands related to account or group enumeration. Adversaries may use account and group information to orient themselves before deciding how to act. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |8.7.0 |207
+|<<enumeration-of-users-or-groups-via-built-in-commands, Enumeration of Users or Groups via Built-in Commands>> |Identifies the execution of macOS built-in commands related to account or group enumeration. Adversaries may use account and group information to orient themselves before deciding how to act. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |None |207
 
 |<<exchange-mailbox-export-via-powershell, Exchange Mailbox Export via PowerShell>> |Identifies the use of the Exchange PowerShell cmdlet, New-MailBoxExportRequest, to export the contents of a primary mailbox or archive to a .pst file. Adversaries may target user email to collect sensitive information. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |8
 
-|<<executable-file-creation-with-multiple-extensions, Executable File Creation with Multiple Extensions>> |Masquerading can allow an adversary to evade defenses and better blend in with the environment. One way it occurs is when the name or location of a file is manipulated as a means of tricking a user into executing what they think is a benign file type but is actually executable code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<executable-file-creation-with-multiple-extensions, Executable File Creation with Multiple Extensions>> |Masquerading can allow an adversary to evade defenses and better blend in with the environment. One way it occurs is when the name or location of a file is manipulated as a means of tricking a user into executing what they think is a benign file type but is actually executable code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<executable-file-with-unusual-extension, Executable File with Unusual Extension>> |Identifies the creation or modification of an executable file with an unexpected file extension. Attackers may attempt to evade detection by masquerading files using the file extension values used by image, audio, or document file types. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |2
+|<<executable-file-with-unusual-extension, Executable File with Unusual Extension>> |Identifies the creation or modification of an executable file with an unexpected file extension. Attackers may attempt to evade detection by masquerading files using the file extension values used by image, audio, or document file types. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |None |2
 
-|<<executable-masquerading-as-kernel-process, Executable Masquerading as Kernel Process>> |Monitors for kernel processes with associated process executable fields that are not empty. Unix kernel processes such as kthreadd and kworker typically do not have process.executable fields associated to them. Attackers may attempt to hide their malicious programs by masquerading as legitimate kernel processes. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<executable-masquerading-as-kernel-process, Executable Masquerading as Kernel Process>> |Monitors for kernel processes with associated process executable fields that are not empty. Unix kernel processes such as kthreadd and kworker typically do not have process.executable fields associated to them. Attackers may attempt to hide their malicious programs by masquerading as legitimate kernel processes. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |3
 
-|<<execution-from-unusual-directory-command-line, Execution from Unusual Directory - Command Line>> |Identifies process execution from suspicious default Windows directories. This may be abused by adversaries to hide malware in trusted paths. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<execution-from-unusual-directory-command-line, Execution from Unusual Directory - Command Line>> |Identifies process execution from suspicious default Windows directories. This may be abused by adversaries to hide malware in trusted paths. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<execution-from-a-removable-media-with-network-connection, Execution from a Removable Media with Network Connection>> |Identifies process execution from a removable media and by an unusual process. Adversaries may move onto systems, possibly those on disconnected or air-gapped networks, by copying malware to removable media and taking advantage of Autorun features when the media is inserted into a system and executes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Defend] |8.3.0 |3
+|<<execution-from-a-removable-media-with-network-connection, Execution from a Removable Media with Network Connection>> |Identifies process execution from a removable media and by an unusual process. Adversaries may move onto systems, possibly those on disconnected or air-gapped networks, by copying malware to removable media and taking advantage of Autorun features when the media is inserted into a system and executes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Defend] |None |3
 
-|<<execution-of-com-object-via-xwizard, Execution of COM object via Xwizard>> |Windows Component Object Model (COM) is an inter-process communication (IPC) component of the native Windows application programming interface (API) that enables interaction between software objects or executable code. Xwizard can be used to run a COM object created in registry to evade defensive counter measures. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<execution-of-com-object-via-xwizard, Execution of COM object via Xwizard>> |Windows Component Object Model (COM) is an inter-process communication (IPC) component of the native Windows application programming interface (API) that enables interaction between software objects or executable code. Xwizard can be used to run a COM object created in registry to evade defensive counter measures. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<execution-of-file-written-or-modified-by-microsoft-office, Execution of File Written or Modified by Microsoft Office>> |Identifies an executable created by a Microsoft Office application and subsequently executed. These processes are often launched via scripts inside documents or during exploitation of Microsoft Office applications. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<execution-of-file-written-or-modified-by-microsoft-office, Execution of File Written or Modified by Microsoft Office>> |Identifies an executable created by a Microsoft Office application and subsequently executed. These processes are often launched via scripts inside documents or during exploitation of Microsoft Office applications. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<execution-of-file-written-or-modified-by-pdf-reader, Execution of File Written or Modified by PDF Reader>> |Identifies a suspicious file that was written by a PDF reader application and subsequently executed. These processes are often launched via exploitation of PDF applications. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<execution-of-file-written-or-modified-by-pdf-reader, Execution of File Written or Modified by PDF Reader>> |Identifies a suspicious file that was written by a PDF reader application and subsequently executed. These processes are often launched via exploitation of PDF applications. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<execution-of-persistent-suspicious-program, Execution of Persistent Suspicious Program>> |Identifies execution of suspicious persistent programs (scripts, rundll32, etc.) by looking at process lineage and command line usage. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<execution-of-persistent-suspicious-program, Execution of Persistent Suspicious Program>> |Identifies execution of suspicious persistent programs (scripts, rundll32, etc.) by looking at process lineage and command line usage. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<execution-of-an-unsigned-service, Execution of an Unsigned Service>> |This rule identifies the execution of unsigned executables via service control manager (SCM). Adversaries may abuse SCM to execute malware or escalate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |8.6.0 |105
+|<<execution-of-an-unsigned-service, Execution of an Unsigned Service>> |This rule identifies the execution of unsigned executables via service control manager (SCM). Adversaries may abuse SCM to execute malware or escalate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |None |105
 
-|<<execution-via-electron-child-process-node-js-module, Execution via Electron Child Process Node.js Module>> |Identifies attempts to execute a child process from within the context of an Electron application using the child_process Node.js module. Adversaries may abuse this technique to inherit permissions from parent processes. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |106
+|<<execution-via-electron-child-process-node-js-module, Execution via Electron Child Process Node.js Module>> |Identifies attempts to execute a child process from within the context of an Electron application using the child_process Node.js module. Adversaries may abuse this technique to inherit permissions from parent processes. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |None |106
 
-|<<execution-via-ms-visualstudio-pre-post-build-events, Execution via MS VisualStudio Pre/Post Build Events>> |Identifies the execution of a command via Microsoft Visual Studio Pre or Post build events. Adversaries may backdoor a trusted visual studio project to execute a malicious command during the project build process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |2
+|<<execution-via-ms-visualstudio-pre-post-build-events, Execution via MS VisualStudio Pre/Post Build Events>> |Identifies the execution of a command via Microsoft Visual Studio Pre or Post build events. Adversaries may backdoor a trusted visual studio project to execute a malicious command during the project build process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Rule Type: BBR], [Data Source: Elastic Defend] |None |2
 
-|<<execution-via-mssql-xp-cmdshell-stored-procedure, Execution via MSSQL xp_cmdshell Stored Procedure>> |Identifies execution via MSSQL xp_cmdshell stored procedure. Malicious users may attempt to elevate their privileges by using xp_cmdshell, which is disabled by default, thus, it's important to review the context of it's use. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<execution-via-mssql-xp-cmdshell-stored-procedure, Execution via MSSQL xp_cmdshell Stored Procedure>> |Identifies execution via MSSQL xp_cmdshell stored procedure. Malicious users may attempt to elevate their privileges by using xp_cmdshell, which is disabled by default, thus, it's important to review the context of it's use. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<execution-via-microsoft-dotnet-clickonce-host, Execution via Microsoft DotNet ClickOnce Host>> |Identifies the execution of DotNet ClickOnce installer via Dfsvc.exe trampoline. Adversaries may take advantage of ClickOnce to proxy execution of malicious payloads via trusted Microsoft processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |1
+|<<execution-via-microsoft-dotnet-clickonce-host, Execution via Microsoft DotNet ClickOnce Host>> |Identifies the execution of DotNet ClickOnce installer via Dfsvc.exe trampoline. Adversaries may take advantage of ClickOnce to proxy execution of malicious payloads via trusted Microsoft processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |None |1
 
-|<<execution-via-tsclient-mountpoint, Execution via TSClient Mountpoint>> |Identifies execution from the Remote Desktop Protocol (RDP) shared mountpoint tsclient on the target host. This may indicate a lateral movement attempt. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<execution-via-tsclient-mountpoint, Execution via TSClient Mountpoint>> |Identifies execution from the Remote Desktop Protocol (RDP) shared mountpoint tsclient on the target host. This may indicate a lateral movement attempt. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<execution-via-windows-subsystem-for-linux, Execution via Windows Subsystem for Linux>> |Detects attempts to execute a program on the host from the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |6
+|<<execution-via-windows-subsystem-for-linux, Execution via Windows Subsystem for Linux>> |Detects attempts to execute a program on the host from the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |6
 
-|<<execution-via-local-sxs-shared-module, Execution via local SxS Shared Module>> |Identifies the creation, change, or deletion of a DLL module within a Windows SxS local folder. Adversaries may abuse shared modules to execute malicious payloads by instructing the Windows module loader to load DLLs from arbitrary local paths. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<execution-via-local-sxs-shared-module, Execution via local SxS Shared Module>> |Identifies the creation, change, or deletion of a DLL module within a Windows SxS local folder. Adversaries may abuse shared modules to execute malicious payloads by instructing the Windows module loader to load DLLs from arbitrary local paths. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<execution-with-explicit-credentials-via-scripting, Execution with Explicit Credentials via Scripting>> |Identifies execution of the security_authtrampoline process via a scripting interpreter. This occurs when programs use AuthorizationExecute-WithPrivileges from the Security.framework to run another program with root privileges. It should not be run by itself, as this is a sign of execution with explicit logon credentials. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |106
+|<<execution-with-explicit-credentials-via-scripting, Execution with Explicit Credentials via Scripting>> |Identifies execution of the security_authtrampoline process via a scripting interpreter. This occurs when programs use AuthorizationExecute-WithPrivileges from the Security.framework to run another program with root privileges. It should not be run by itself, as this is a sign of execution with explicit logon credentials. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |106
 
-|<<expired-or-revoked-driver-loaded, Expired or Revoked Driver Loaded>> |Identifies an attempt to load a revoked or expired driver. Adversaries may bring outdated drivers with vulnerabilities to gain code execution in kernel mode or abuse revoked certificates to sign their drivers. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |5
+|<<expired-or-revoked-driver-loaded, Expired or Revoked Driver Loaded>> |Identifies an attempt to load a revoked or expired driver. Adversaries may bring outdated drivers with vulnerabilities to gain code execution in kernel mode or abuse revoked certificates to sign their drivers. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |5
 
-|<<exploit-detected-elastic-endgame, Exploit - Detected - Elastic Endgame>> |Elastic Endgame detected an Exploit. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<exploit-detected-elastic-endgame, Exploit - Detected - Elastic Endgame>> |Elastic Endgame detected an Exploit. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation] |None |103
 
-|<<exploit-prevented-elastic-endgame, Exploit - Prevented - Elastic Endgame>> |Elastic Endgame prevented an Exploit. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<exploit-prevented-elastic-endgame, Exploit - Prevented - Elastic Endgame>> |Elastic Endgame prevented an Exploit. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Privilege Escalation] |None |103
 
-|<<exporting-exchange-mailbox-via-powershell, Exporting Exchange Mailbox via PowerShell>> |Identifies the use of the Exchange PowerShell cmdlet, New-MailBoxExportRequest, to export the contents of a primary mailbox or archive to a .pst file. Adversaries may target user email to collect sensitive information. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<exporting-exchange-mailbox-via-powershell, Exporting Exchange Mailbox via PowerShell>> |Identifies the use of the Exchange PowerShell cmdlet, New-MailBoxExportRequest, to export the contents of a primary mailbox or archive to a .pst file. Adversaries may target user email to collect sensitive information. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne] |8.11.0 |213
 
-|<<external-alerts, External Alerts>> |Generates a detection alert for each external alert written to the configured indices. Enabling this rule allows you to immediately begin investigating external alerts in the app. |[OS: Windows], [Data Source: APM], [OS: macOS], [OS: Linux] |8.3.0 |103
+|<<external-alerts, External Alerts>> |Generates a detection alert for each external alert written to the configured indices. Enabling this rule allows you to immediately begin investigating external alerts in the app. |[OS: Windows], [Data Source: APM], [OS: macOS], [OS: Linux] |None |103
 
-|<<external-ip-lookup-from-non-browser-process, External IP Lookup from Non-Browser Process>> |Identifies domains commonly used by adversaries for post-exploitation IP lookups. It is common for adversaries to test for Internet access and acquire their external IP address after they have gained access to a system. Among others, this has been observed in campaigns leveraging the information stealer, Trickbot. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |108
+|<<external-ip-lookup-from-non-browser-process, External IP Lookup from Non-Browser Process>> |Identifies domains commonly used by adversaries for post-exploitation IP lookups. It is common for adversaries to test for Internet access and acquire their external IP address after they have gained access to a system. Among others, this has been observed in campaigns leveraging the information stealer, Trickbot. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Rule Type: BBR] |None |108
 
-|<<external-user-added-to-google-workspace-group, External User Added to Google Workspace Group>> |Detects an external Google Workspace user account being added to an existing group. Adversaries may add external user accounts as a means to intercept shared files or emails with that specific group. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Initial Access], [Resources: Investigation Guide] |8.4.0 |2
+|<<external-user-added-to-google-workspace-group, External User Added to Google Workspace Group>> |Detects an external Google Workspace user account being added to an existing group. Adversaries may add external user accounts as a means to intercept shared files or emails with that specific group. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Initial Access], [Resources: Investigation Guide] |None |2
 
-|<<file-compressed-or-archived-into-common-format, File Compressed or Archived into Common Format>> |Detects files being compressed or archived into common formats. This is a common technique used to obfuscate files to evade detection or to staging data for exfiltration. |[Data Source: Elastic Defend], [Domain: Endpoint], [OS: macOS], [OS: Windows], [Tactic: Collection], [Rule Type: BBR] |8.3.0 |4
+|<<file-compressed-or-archived-into-common-format, File Compressed or Archived into Common Format>> |Detects files being compressed or archived into common formats. This is a common technique used to obfuscate files to evade detection or to staging data for exfiltration. |[Data Source: Elastic Defend], [Domain: Endpoint], [OS: macOS], [OS: Windows], [Tactic: Collection], [Rule Type: BBR] |None |5
 
-|<<file-creation-time-changed, File Creation Time Changed>> |Identifies modification of a file creation time. Adversaries may modify file time attributes to blend malicious content with existing files. Timestomping is a technique that modifies the timestamps of a file often to mimic files that are in trusted directories. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Sysmon] |8.3.0 |5
+|<<file-creation-time-changed, File Creation Time Changed>> |Identifies modification of a file creation time. Adversaries may modify file time attributes to blend malicious content with existing files. Timestomping is a technique that modifies the timestamps of a file often to mimic files that are in trusted directories. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Sysmon] |None |5
 
-|<<file-creation-execution-and-self-deletion-in-suspicious-directory, File Creation, Execution and Self-Deletion in Suspicious Directory>> |This rule monitors for the creation of a file, followed by its execution and self-deletion in a short timespan within a directory often used for malicious purposes by threat actors. This behavior is often used by malware to execute malicious code and delete itself to hide its tracks. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |4
+|<<file-creation-execution-and-self-deletion-in-suspicious-directory, File Creation, Execution and Self-Deletion in Suspicious Directory>> |This rule monitors for the creation of a file, followed by its execution and self-deletion in a short timespan within a directory often used for malicious purposes by threat actors. This behavior is often used by malware to execute malicious code and delete itself to hide its tracks. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |4
 
-|<<file-deletion-via-shred, File Deletion via Shred>> |Malware or other files dropped or created on a system by an adversary may leave traces behind as to what was done within a network and how. Adversaries may remove these files over the course of an intrusion to keep their footprint low or remove them at the end as part of the post-intrusion cleanup process. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |109
+|<<file-deletion-via-shred, File Deletion via Shred>> |Malware or other files dropped or created on a system by an adversary may leave traces behind as to what was done within a network and how. Adversaries may remove these files over the course of an intrusion to keep their footprint low or remove them at the end as part of the post-intrusion cleanup process. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |109
 
-|<<file-made-executable-via-chmod-inside-a-container, File Made Executable via Chmod Inside A Container>> |This rule detects when chmod is used to add the execute permission to a file inside a container. Modifying file permissions to make a file executable could indicate malicious activity, as an attacker may attempt to run unauthorized or malicious code inside the container. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion] |8.8.0 |2
+|<<file-made-executable-via-chmod-inside-a-container, File Made Executable via Chmod Inside A Container>> |This rule detects when chmod is used to add the execute permission to a file inside a container. Modifying file permissions to make a file executable could indicate malicious activity, as an attacker may attempt to run unauthorized or malicious code inside the container. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion] |None |2
 
-|<<file-permission-modification-in-writable-directory, File Permission Modification in Writable Directory>> |Identifies file permission modifications in common writable directories by a non-root user. Adversaries often drop files or payloads into a writable directory and change permissions prior to execution. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.6.0 |210
+|<<file-permission-modification-in-writable-directory, File Permission Modification in Writable Directory>> |Identifies file permission modifications in common writable directories by a non-root user. Adversaries often drop files or payloads into a writable directory and change permissions prior to execution. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |210
 
-|<<file-staged-in-root-folder-of-recycle-bin, File Staged in Root Folder of Recycle Bin>> |Identifies files written to the root of the Recycle Bin folder instead of subdirectories. Adversaries may place files in the root of the Recycle Bin in preparation for exfiltration or to evade defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |3
+|<<file-staged-in-root-folder-of-recycle-bin, File Staged in Root Folder of Recycle Bin>> |Identifies files written to the root of the Recycle Bin folder instead of subdirectories. Adversaries may place files in the root of the Recycle Bin in preparation for exfiltration or to evade defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend], [Rule Type: BBR] |None |3
 
 |<<file-system-debugger-launched-inside-a-privileged-container, File System Debugger Launched Inside a Privileged Container>> |This rule detects the use of the built-in Linux DebugFS utility from inside a privileged container. DebugFS is a special file system debugging utility which supports reading and writing directly from a hard drive device. When launched inside a privileged container, a container deployed with all the capabilities of the host machine, an attacker can access sensitive host level files which could be used for further privilege escalation and container escapes to the host machine. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.10.0 |1
 
-|<<file-transfer-or-listener-established-via-netcat, File Transfer or Listener Established via Netcat>> |A netcat process is engaging in network activity on a Linux host. Netcat is often used as a persistence mechanism by exporting a reverse shell or by serving a shell on a listening port. Netcat is also sometimes used for data exfiltration. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |110
+|<<file-transfer-or-listener-established-via-netcat, File Transfer or Listener Established via Netcat>> |A netcat process is engaging in network activity on a Linux host. Netcat is often used as a persistence mechanism by exporting a reverse shell or by serving a shell on a listening port. Netcat is also sometimes used for data exfiltration. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |110
 
-|<<file-and-directory-permissions-modification, File and Directory Permissions Modification>> |Identifies the change of permissions/ownership of files/folders through built-in Windows utilities. Threat actors may require permission modification of files/folders to change, modify or delete them. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |2
+|<<file-and-directory-permissions-modification, File and Directory Permissions Modification>> |Identifies the change of permissions/ownership of files/folders through built-in Windows utilities. Threat actors may require permission modification of files/folders to change, modify or delete them. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |None |2
 
-|<<file-made-immutable-by-chattr, File made Immutable by Chattr>> |Detects a file being made immutable using the chattr binary. Making a file immutable means it cannot be deleted or renamed, no link can be created to this file, most of the file's metadata can not be modified, and the file can not be opened in write mode. Threat actors will commonly utilize this to prevent tampering or modification of their malicious files or any system files they have modified for purposes of persistence (e.g .ssh, /etc/passwd, etc.). |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<file-made-immutable-by-chattr, File made Immutable by Chattr>> |Detects a file being made immutable using the chattr binary. Making a file immutable means it cannot be deleted or renamed, no link can be created to this file, most of the file's metadata can not be modified, and the file can not be opened in write mode. Threat actors will commonly utilize this to prevent tampering or modification of their malicious files or any system files they have modified for purposes of persistence (e.g .ssh, /etc/passwd, etc.). |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<file-or-directory-deletion-command, File or Directory Deletion Command>> |This rule identifies the execution of commands that can be used to delete files and directories. Adversaries may delete files and directories on a host system, such as logs, browser history, or malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |3
+|<<file-or-directory-deletion-command, File or Directory Deletion Command>> |This rule identifies the execution of commands that can be used to delete files and directories. Adversaries may delete files and directories on a host system, such as logs, browser history, or malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |None |3
 
-|<<file-with-suspicious-extension-downloaded, File with Suspicious Extension Downloaded>> |Identifies unusual files downloaded from outside the local network that have the potential to be abused for code execution. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |3
+|<<file-with-suspicious-extension-downloaded, File with Suspicious Extension Downloaded>> |Identifies unusual files downloaded from outside the local network that have the potential to be abused for code execution. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |None |3
 
 |<<finder-sync-plugin-registered-and-enabled, Finder Sync Plugin Registered and Enabled>> |Finder Sync plugins enable users to extend Finder’s functionality by modifying the user interface. Adversaries may abuse this feature by adding a rogue Finder Plugin to repeatedly execute malicious payloads for persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.11.0 |206
 
-|<<first-occurrence-github-event-for-a-personal-access-token-pat, First Occurrence GitHub Event for a Personal Access Token (PAT)>> |Detects a first occurrence event for a personal access token (PAT) not seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |8.8.0 |1
+|<<first-occurrence-github-event-for-a-personal-access-token-pat, First Occurrence GitHub Event for a Personal Access Token (PAT)>> |Detects a first occurrence event for a personal access token (PAT) not seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<first-occurrence-of-github-repo-interaction-from-a-new-ip, First Occurrence of GitHub Repo Interaction From a New IP>> |Detects an interaction with a private GitHub repository from a new IP address not seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |8.8.0 |1
+|<<first-occurrence-of-github-repo-interaction-from-a-new-ip, First Occurrence of GitHub Repo Interaction From a New IP>> |Detects an interaction with a private GitHub repository from a new IP address not seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<first-occurrence-of-github-user-interaction-with-private-repo, First Occurrence of GitHub User Interaction with Private Repo>> |Detects a new private repo interaction for a GitHub user not seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |8.6.0 |1
+|<<first-occurrence-of-github-user-interaction-with-private-repo, First Occurrence of GitHub User Interaction with Private Repo>> |Detects a new private repo interaction for a GitHub user not seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<first-occurrence-of-ip-address-for-github-personal-access-token-pat, First Occurrence of IP Address For GitHub Personal Access Token (PAT)>> |Detects a new IP address used for a GitHub PAT not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |8.8.0 |1
+|<<first-occurrence-of-ip-address-for-github-personal-access-token-pat, First Occurrence of IP Address For GitHub Personal Access Token (PAT)>> |Detects a new IP address used for a GitHub PAT not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<first-occurrence-of-ip-address-for-github-user, First Occurrence of IP Address For GitHub User>> |Detects a new IP address used for a GitHub user not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |8.8.0 |1
+|<<first-occurrence-of-ip-address-for-github-user, First Occurrence of IP Address For GitHub User>> |Detects a new IP address used for a GitHub user not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |None |1
 
 |<<first-occurrence-of-okta-user-session-started-via-proxy, First Occurrence of Okta User Session Started via Proxy>> |Identifies the first occurrence of an Okta user session started via a proxy. |[Tactic: Initial Access], [Use Case: Identity and Access Audit], [Data Source: Okta] |8.10.0 |1
 
-|<<first-occurrence-of-personal-access-token-pat-use-for-a-github-user, First Occurrence of Personal Access Token (PAT) Use For a GitHub User>> |A new PAT was used for a GitHub user not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Github] |8.8.0 |1
+|<<first-occurrence-of-personal-access-token-pat-use-for-a-github-user, First Occurrence of Personal Access Token (PAT) Use For a GitHub User>> |A new PAT was used for a GitHub user not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<first-occurrence-of-private-repo-event-from-specific-github-personal-access-token-pat, First Occurrence of Private Repo Event from Specific GitHub Personal Access Token (PAT)>> |Detects a new private repo interaction for a GitHub PAT not seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |8.8.0 |1
+|<<first-occurrence-of-private-repo-event-from-specific-github-personal-access-token-pat, First Occurrence of Private Repo Event from Specific GitHub Personal Access Token (PAT)>> |Detects a new private repo interaction for a GitHub PAT not seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<first-occurrence-of-user-agent-for-a-github-personal-access-token-pat, First Occurrence of User Agent For a GitHub Personal Access Token (PAT)>> |Detects a new user agent used for a GitHub PAT not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |8.8.0 |1
+|<<first-occurrence-of-user-agent-for-a-github-personal-access-token-pat, First Occurrence of User Agent For a GitHub Personal Access Token (PAT)>> |Detects a new user agent used for a GitHub PAT not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<first-occurrence-of-user-agent-for-a-github-user, First Occurrence of User-Agent For a GitHub User>> |Detects a new user agent used for a GitHub user not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |8.8.0 |1
+|<<first-occurrence-of-user-agent-for-a-github-user, First Occurrence of User-Agent For a GitHub User>> |Detects a new user agent used for a GitHub user not previously seen in the last 14 days. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<first-time-seen-aws-secret-value-accessed-in-secrets-manager, First Time Seen AWS Secret Value Accessed in Secrets Manager>> |An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service may attempt to leverage the compromised service to access secrets in AWS Secrets Manager. This rule looks for the first time a specific user identity has programmatically retrieved a specific secret value from Secrets Manager using the `GetSecretValue` action.  This rule assumes that AWS services such as Lambda functions and EC2 instances are setup with IAM role's assigned that have the necessary permissions to access the secrets in Secrets Manager. An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service would rely on the compromised service's IAM role to access the secrets in Secrets Manager. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Credential Access], [Resources: Investigation Guide] |8.9.0 |310
+|<<first-time-seen-aws-secret-value-accessed-in-secrets-manager, First Time Seen AWS Secret Value Accessed in Secrets Manager>> |An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service may attempt to leverage the compromised service to access secrets in AWS Secrets Manager. This rule looks for the first time a specific user identity has programmatically retrieved a specific secret value from Secrets Manager using the `GetSecretValue` action. This rule assumes that AWS services such as Lambda functions and EC2 instances are setup with IAM role's assigned that have the necessary permissions to access the secrets in Secrets Manager. An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service would rely on the compromised service's IAM role to access the secrets in Secrets Manager. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Tactic: Credential Access], [Resources: Investigation Guide] |None |311
 
-|<<first-time-seen-commonly-abused-remote-access-tool-execution, First Time Seen Commonly Abused Remote Access Tool Execution>> |Adversaries may install legitimate remote access tools (RAT) to compromised endpoints for further command-and-control (C2). Adversaries can rely on installed RATs for persistence, execution of native commands and more. This rule detects when a process is started whose name or code signature resembles commonly abused RATs. This is a New Terms rule type indicating the host has not seen this RAT process started before within the last 30 days. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.4.0 |5
+|<<first-time-seen-commonly-abused-remote-access-tool-execution, First Time Seen Commonly Abused Remote Access Tool Execution>> |Adversaries may install legitimate remote access tools (RAT) to compromised endpoints for further command-and-control (C2). Adversaries can rely on installed RATs for persistence, execution of native commands and more. This rule detects when a process is started whose name or code signature resembles commonly abused RATs. This is a New Terms rule type indicating the host has not seen this RAT process started before within the last 30 days. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |5
 
-|<<first-time-seen-driver-loaded, First Time Seen Driver Loaded>> |Identifies the load of a driver with an original file name and signature values that were observed for the first time during the last 30 days. This rule type can help baseline drivers installation within your environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.6.0 |7
+|<<first-time-seen-driver-loaded, First Time Seen Driver Loaded>> |Identifies the load of a driver with an original file name and signature values that were observed for the first time during the last 30 days. This rule type can help baseline drivers installation within your environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |8
 
-|<<first-time-seen-google-workspace-oauth-login-from-third-party-application, First Time Seen Google Workspace OAuth Login from Third-Party Application>> |Detects the first time a third-party application logs in and authenticated with OAuth. OAuth is used to grant permissions to specific resources and services in Google Workspace. Compromised credentials or service accounts could allow an adversary to authenticate to Google Workspace as a valid user and inherit their privileges. |[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Defense Evasion], [Tactic: Initial Access] |8.4.0 |3
+|<<first-time-seen-google-workspace-oauth-login-from-third-party-application, First Time Seen Google Workspace OAuth Login from Third-Party Application>> |Detects the first time a third-party application logs in and authenticated with OAuth. OAuth is used to grant permissions to specific resources and services in Google Workspace. Compromised credentials or service accounts could allow an adversary to authenticate to Google Workspace as a valid user and inherit their privileges. |[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Defense Evasion], [Tactic: Initial Access] |None |3
 
-|<<first-time-seen-newcredentials-logon-process, First Time Seen NewCredentials Logon Process>> |Identifies a new credentials logon type performed by an unusual process. This may indicate the existence of an access token forging capability that are often abused to bypass access control restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.4.0 |2
+|<<first-time-seen-newcredentials-logon-process, First Time Seen NewCredentials Logon Process>> |Identifies a new credentials logon type performed by an unusual process. This may indicate the existence of an access token forging capability that are often abused to bypass access control restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |2
 
-|<<first-time-seen-removable-device, First Time Seen Removable Device>> |Identifies newly seen removable devices by device friendly name using registry modification events. While this activity is not inherently malicious, analysts can use those events to aid monitoring for data exfiltration over those devices. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Exfiltration], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.4.0 |4
+|<<first-time-seen-removable-device, First Time Seen Removable Device>> |Identifies newly seen removable devices by device friendly name using registry modification events. While this activity is not inherently malicious, analysts can use those events to aid monitoring for data exfiltration over those devices. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Exfiltration], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |4
 
-|<<firsttime-seen-account-performing-dcsync, FirstTime Seen Account Performing DCSync>> |This rule identifies when a User Account starts the Active Directory Replication Process for the first time. Attackers can use the DCSync technique to get credential information of individual accounts or the entire domain, thus compromising the entire domain. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Resources: Investigation Guide] |8.4.0 |10
+|<<firsttime-seen-account-performing-dcsync, FirstTime Seen Account Performing DCSync>> |This rule identifies when a User Account starts the Active Directory Replication Process for the first time. Attackers can use the DCSync technique to get credential information of individual accounts or the entire domain, thus compromising the entire domain. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Resources: Investigation Guide] |None |10
 
-|<<forwarded-google-workspace-security-alert, Forwarded Google Workspace Security Alert>> |Identifies the occurrence of a security alert from the Google Workspace alerts center. Google Workspace's security alert center provides an overview of actionable alerts that may be affecting an organization's domain. An alert is a warning of a potential security issue that Google has detected. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Log Auditing], [Use Case: Threat Detection] |8.4.0 |2
+|<<forwarded-google-workspace-security-alert, Forwarded Google Workspace Security Alert>> |Identifies the occurrence of a security alert from the Google Workspace alerts center. Google Workspace's security alert center provides an overview of actionable alerts that may be affecting an organization's domain. An alert is a warning of a potential security issue that Google has detected. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Log Auditing], [Use Case: Threat Detection] |None |2
 
-|<<full-user-mode-dumps-enabled-system-wide, Full User-Mode Dumps Enabled System-Wide>> |Identifies the enable of the full user-mode dumps feature system-wide. This feature allows Windows Error Reporting (WER) to collect data after an application crashes. This setting is a requirement for the LSASS Shtinkering attack, which fakes the communication of a crash on LSASS, generating a dump of the process memory, which gives the attacker access to the credentials present on the system without having to bring malware to the system. This setting is not enabled by default, and applications must create their registry subkeys to hold settings that enable them to collect dumps. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Sysmon] |8.3.0 |7
+|<<full-user-mode-dumps-enabled-system-wide, Full User-Mode Dumps Enabled System-Wide>> |Identifies the enable of the full user-mode dumps feature system-wide. This feature allows Windows Error Reporting (WER) to collect data after an application crashes. This setting is a requirement for the LSASS Shtinkering attack, which fakes the communication of a crash on LSASS, generating a dump of the process memory, which gives the attacker access to the credentials present on the system without having to bring malware to the system. This setting is not enabled by default, and applications must create their registry subkeys to hold settings that enable them to collect dumps. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Sysmon] |None |7
 
-|<<gcp-firewall-rule-creation, GCP Firewall Rule Creation>> |Identifies when a firewall rule is created in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be configured to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may create a new firewall rule in order to weaken their target's security controls and allow more permissive ingress or egress traffic flows for their benefit. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-firewall-rule-creation, GCP Firewall Rule Creation>> |Identifies when a firewall rule is created in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be configured to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may create a new firewall rule in order to weaken their target's security controls and allow more permissive ingress or egress traffic flows for their benefit. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-firewall-rule-deletion, GCP Firewall Rule Deletion>> |Identifies when a firewall rule is deleted in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be configured to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may delete a firewall rule in order to weaken their target's security controls. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-firewall-rule-deletion, GCP Firewall Rule Deletion>> |Identifies when a firewall rule is deleted in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be configured to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may delete a firewall rule in order to weaken their target's security controls. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-firewall-rule-modification, GCP Firewall Rule Modification>> |Identifies when a firewall rule is modified in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be modified to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may modify an existing firewall rule in order to weaken their target's security controls and allow more permissive ingress or egress traffic flows for their benefit. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-firewall-rule-modification, GCP Firewall Rule Modification>> |Identifies when a firewall rule is modified in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be modified to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may modify an existing firewall rule in order to weaken their target's security controls and allow more permissive ingress or egress traffic flows for their benefit. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-iam-custom-role-creation, GCP IAM Custom Role Creation>> |Identifies an Identity and Access Management (IAM) custom role creation in Google Cloud Platform (GCP). Custom roles are user-defined, and allow for the bundling of one or more supported permissions to meet specific needs. Custom roles will not be updated automatically and could lead to privilege creep if not carefully scrutinized. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |8.3.0 |104
+|<<gcp-iam-custom-role-creation, GCP IAM Custom Role Creation>> |Identifies an Identity and Access Management (IAM) custom role creation in Google Cloud Platform (GCP). Custom roles are user-defined, and allow for the bundling of one or more supported permissions to meet specific needs. Custom roles will not be updated automatically and could lead to privilege creep if not carefully scrutinized. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |None |104
 
-|<<gcp-iam-role-deletion, GCP IAM Role Deletion>> |Identifies an Identity and Access Management (IAM) role deletion in Google Cloud Platform (GCP). A role contains a set of permissions that allows you to perform specific actions on Google Cloud resources. An adversary may delete an IAM role to inhibit access to accounts utilized by legitimate users. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Impact] |8.3.0 |104
+|<<gcp-iam-role-deletion, GCP IAM Role Deletion>> |Identifies an Identity and Access Management (IAM) role deletion in Google Cloud Platform (GCP). A role contains a set of permissions that allows you to perform specific actions on Google Cloud resources. An adversary may delete an IAM role to inhibit access to accounts utilized by legitimate users. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Impact] |None |104
 
-|<<gcp-iam-service-account-key-deletion, GCP IAM Service Account Key Deletion>> |Identifies the deletion of an Identity and Access Management (IAM) service account key in Google Cloud Platform (GCP). Each service account is associated with two sets of public/private RSA key pairs that are used to authenticate. If a key is deleted, the application will no longer be able to access Google Cloud resources using that key. A security best practice is to rotate your service account keys regularly. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.3.0 |104
+|<<gcp-iam-service-account-key-deletion, GCP IAM Service Account Key Deletion>> |Identifies the deletion of an Identity and Access Management (IAM) service account key in Google Cloud Platform (GCP). Each service account is associated with two sets of public/private RSA key pairs that are used to authenticate. If a key is deleted, the application will no longer be able to access Google Cloud resources using that key. A security best practice is to rotate your service account keys regularly. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Persistence] |None |104
 
-|<<gcp-logging-bucket-deletion, GCP Logging Bucket Deletion>> |Identifies a Logging bucket deletion in Google Cloud Platform (GCP). Log buckets are containers that store and organize log data. A deleted bucket stays in a pending state for 7 days, and Logging continues to route logs to the bucket during that time. To stop routing logs to a deleted bucket, you can delete the log sinks that have the bucket as their destination, or modify the filter for the sinks to stop it from routing logs to the deleted bucket. An adversary may delete a log bucket to evade detection. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-logging-bucket-deletion, GCP Logging Bucket Deletion>> |Identifies a Logging bucket deletion in Google Cloud Platform (GCP). Log buckets are containers that store and organize log data. A deleted bucket stays in a pending state for 7 days, and Logging continues to route logs to the bucket during that time. To stop routing logs to a deleted bucket, you can delete the log sinks that have the bucket as their destination, or modify the filter for the sinks to stop it from routing logs to the deleted bucket. An adversary may delete a log bucket to evade detection. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-logging-sink-deletion, GCP Logging Sink Deletion>> |Identifies a Logging sink deletion in Google Cloud Platform (GCP). Every time a log entry arrives, Logging compares the log entry to the sinks in that resource. Each sink whose filter matches the log entry writes a copy of the log entry to the sink's export destination. An adversary may delete a Logging sink to evade detection. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-logging-sink-deletion, GCP Logging Sink Deletion>> |Identifies a Logging sink deletion in Google Cloud Platform (GCP). Every time a log entry arrives, Logging compares the log entry to the sinks in that resource. Each sink whose filter matches the log entry writes a copy of the log entry to the sink's export destination. An adversary may delete a Logging sink to evade detection. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-logging-sink-modification, GCP Logging Sink Modification>> |Identifies a modification to a Logging sink in Google Cloud Platform (GCP). Logging compares the log entry to the sinks in that resource. Each sink whose filter matches the log entry writes a copy of the log entry to the sink's export destination. An adversary may update a Logging sink to exfiltrate logs to a different export destination. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Exfiltration] |8.3.0 |104
+|<<gcp-logging-sink-modification, GCP Logging Sink Modification>> |Identifies a modification to a Logging sink in Google Cloud Platform (GCP). Logging compares the log entry to the sinks in that resource. Each sink whose filter matches the log entry writes a copy of the log entry to the sink's export destination. An adversary may update a Logging sink to exfiltrate logs to a different export destination. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Exfiltration] |None |104
 
-|<<gcp-pub-sub-subscription-creation, GCP Pub/Sub Subscription Creation>> |Identifies the creation of a subscription in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A subscription is a named resource representing the stream of messages to be delivered to the subscribing application. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Collection] |8.3.0 |105
+|<<gcp-pub-sub-subscription-creation, GCP Pub/Sub Subscription Creation>> |Identifies the creation of a subscription in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A subscription is a named resource representing the stream of messages to be delivered to the subscribing application. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Collection] |None |105
 
-|<<gcp-pub-sub-subscription-deletion, GCP Pub/Sub Subscription Deletion>> |Identifies the deletion of a subscription in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A subscription is a named resource representing the stream of messages to be delivered to the subscribing application. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-pub-sub-subscription-deletion, GCP Pub/Sub Subscription Deletion>> |Identifies the deletion of a subscription in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A subscription is a named resource representing the stream of messages to be delivered to the subscribing application. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-pub-sub-topic-creation, GCP Pub/Sub Topic Creation>> |Identifies the creation of a topic in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A topic is used to forward messages from publishers to subscribers. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Collection] |8.3.0 |105
+|<<gcp-pub-sub-topic-creation, GCP Pub/Sub Topic Creation>> |Identifies the creation of a topic in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A topic is used to forward messages from publishers to subscribers. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Collection] |None |105
 
-|<<gcp-pub-sub-topic-deletion, GCP Pub/Sub Topic Deletion>> |Identifies the deletion of a topic in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A publisher application creates and sends messages to a topic. Deleting a topic can interrupt message flow in the Pub/Sub pipeline. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-pub-sub-topic-deletion, GCP Pub/Sub Topic Deletion>> |Identifies the deletion of a topic in Google Cloud Platform (GCP). In GCP, the publisher-subscriber relationship (Pub/Sub) is an asynchronous messaging service that decouples event-producing and event-processing services. A publisher application creates and sends messages to a topic. Deleting a topic can interrupt message flow in the Pub/Sub pipeline. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Log Auditing], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-service-account-creation, GCP Service Account Creation>> |Identifies when a new service account is created in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. If service accounts are not tracked and managed properly, they can present a security risk. An adversary may create a new service account to use during their operations in order to avoid using a standard user account and attempt to evade detection. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.3.0 |104
+|<<gcp-service-account-creation, GCP Service Account Creation>> |Identifies when a new service account is created in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. If service accounts are not tracked and managed properly, they can present a security risk. An adversary may create a new service account to use during their operations in order to avoid using a standard user account and attempt to evade detection. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Persistence] |None |104
 
-|<<gcp-service-account-deletion, GCP Service Account Deletion>> |Identifies when a service account is deleted in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. An adversary may delete a service account in order to disrupt their target's business operations. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Impact] |8.3.0 |104
+|<<gcp-service-account-deletion, GCP Service Account Deletion>> |Identifies when a service account is deleted in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. An adversary may delete a service account in order to disrupt their target's business operations. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Impact] |None |104
 
-|<<gcp-service-account-disabled, GCP Service Account Disabled>> |Identifies when a service account is disabled in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. An adversary may disable a service account in order to disrupt to disrupt their target's business operations. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Impact] |8.3.0 |104
+|<<gcp-service-account-disabled, GCP Service Account Disabled>> |Identifies when a service account is disabled in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. An adversary may disable a service account in order to disrupt to disrupt their target's business operations. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Impact] |None |104
 
-|<<gcp-service-account-key-creation, GCP Service Account Key Creation>> |Identifies when a new key is created for a service account in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. If private keys are not tracked and managed properly, they can present a security risk. An adversary may create a new key for a service account in order to attempt to abuse the permissions assigned to that account and evade detection. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.3.0 |104
+|<<gcp-service-account-key-creation, GCP Service Account Key Creation>> |Identifies when a new key is created for a service account in Google Cloud Platform (GCP). A service account is a special type of account used by an application or a virtual machine (VM) instance, not a person. Applications use service accounts to make authorized API calls, authorized as either the service account itself, or as G Suite or Cloud Identity users through domain-wide delegation. If private keys are not tracked and managed properly, they can present a security risk. An adversary may create a new key for a service account in order to attempt to abuse the permissions assigned to that account and evade detection. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Persistence] |None |104
 
-|<<gcp-storage-bucket-configuration-modification, GCP Storage Bucket Configuration Modification>> |Identifies when the configuration is modified for a storage bucket in Google Cloud Platform (GCP). An adversary may modify the configuration of a storage bucket in order to weaken the security controls of their target's environment. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-storage-bucket-configuration-modification, GCP Storage Bucket Configuration Modification>> |Identifies when the configuration is modified for a storage bucket in Google Cloud Platform (GCP). An adversary may modify the configuration of a storage bucket in order to weaken the security controls of their target's environment. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-storage-bucket-deletion, GCP Storage Bucket Deletion>> |Identifies when a Google Cloud Platform (GCP) storage bucket is deleted. An adversary may delete a storage bucket in order to disrupt their target's business operations. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Tactic: Impact] |8.3.0 |104
+|<<gcp-storage-bucket-deletion, GCP Storage Bucket Deletion>> |Identifies when a Google Cloud Platform (GCP) storage bucket is deleted. An adversary may delete a storage bucket in order to disrupt their target's business operations. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Tactic: Impact] |None |104
 
-|<<gcp-storage-bucket-permissions-modification, GCP Storage Bucket Permissions Modification>> |Identifies when the Identity and Access Management (IAM) permissions are modified for a Google Cloud Platform (GCP) storage bucket. An adversary may modify the permissions on a storage bucket to weaken their target's security controls or an administrator may inadvertently modify the permissions, which could lead to data exposure or loss. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-storage-bucket-permissions-modification, GCP Storage Bucket Permissions Modification>> |Identifies when the Identity and Access Management (IAM) permissions are modified for a Google Cloud Platform (GCP) storage bucket. An adversary may modify the permissions on a storage bucket to weaken their target's security controls or an administrator may inadvertently modify the permissions, which could lead to data exposure or loss. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Identity and Access Audit], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-virtual-private-cloud-network-deletion, GCP Virtual Private Cloud Network Deletion>> |Identifies when a Virtual Private Cloud (VPC) network is deleted in Google Cloud Platform (GCP). A VPC network is a virtual version of a physical network within a GCP project. Each VPC network has its own subnets, routes, and firewall, as well as other elements. An adversary may delete a VPC network in order to disrupt their target's network and business operations. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-virtual-private-cloud-network-deletion, GCP Virtual Private Cloud Network Deletion>> |Identifies when a Virtual Private Cloud (VPC) network is deleted in Google Cloud Platform (GCP). A VPC network is a virtual version of a physical network within a GCP project. Each VPC network has its own subnets, routes, and firewall, as well as other elements. An adversary may delete a VPC network in order to disrupt their target's network and business operations. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-virtual-private-cloud-route-creation, GCP Virtual Private Cloud Route Creation>> |Identifies when a virtual private cloud (VPC) route is created in Google Cloud Platform (GCP). Google Cloud routes define the paths that network traffic takes from a virtual machine (VM) instance to other destinations. These destinations can be inside a Google VPC network or outside it. An adversary may create a route in order to impact the flow of network traffic in their target's cloud environment. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-virtual-private-cloud-route-creation, GCP Virtual Private Cloud Route Creation>> |Identifies when a virtual private cloud (VPC) route is created in Google Cloud Platform (GCP). Google Cloud routes define the paths that network traffic takes from a virtual machine (VM) instance to other destinations. These destinations can be inside a Google VPC network or outside it. An adversary may create a route in order to impact the flow of network traffic in their target's cloud environment. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |104
 
-|<<gcp-virtual-private-cloud-route-deletion, GCP Virtual Private Cloud Route Deletion>> |Identifies when a Virtual Private Cloud (VPC) route is deleted in Google Cloud Platform (GCP). Google Cloud routes define the paths that network traffic takes from a virtual machine (VM) instance to other destinations. These destinations can be inside a Google VPC network or outside it. An adversary may delete a route in order to impact the flow of network traffic in their target's cloud environment. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.3.0 |104
+|<<gcp-virtual-private-cloud-route-deletion, GCP Virtual Private Cloud Route Deletion>> |Identifies when a Virtual Private Cloud (VPC) route is deleted in Google Cloud Platform (GCP). Google Cloud routes define the paths that network traffic takes from a virtual machine (VM) instance to other destinations. These destinations can be inside a Google VPC network or outside it. An adversary may delete a route in order to impact the flow of network traffic in their target's cloud environment. |[Domain: Cloud], [Data Source: GCP], [Data Source: Google Cloud Platform], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |104
 
-|<<github-app-deleted, GitHub App Deleted>> |Detects the deletion of a GitHub app either from a repo or an organization. |[Domain: Cloud], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Github] |8.3.0 |1
+|<<github-app-deleted, GitHub App Deleted>> |Detects the deletion of a GitHub app either from a repo or an organization. |[Domain: Cloud], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Github] |None |1
 
-|<<github-owner-role-granted-to-user, GitHub Owner Role Granted To User>> |This rule detects when a member is granted the organization owner role of a GitHub organization. This role provides admin level privileges. Any new owner role should be investigated to determine its validity. Unauthorized owner roles could indicate compromise within your organization and provide unlimited access to data and settings. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Data Source: Github] |8.3.0 |3
+|<<github-owner-role-granted-to-user, GitHub Owner Role Granted To User>> |This rule detects when a member is granted the organization owner role of a GitHub organization. This role provides admin level privileges. Any new owner role should be investigated to determine its validity. Unauthorized owner roles could indicate compromise within your organization and provide unlimited access to data and settings. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Data Source: Github] |None |3
 
-|<<github-pat-access-revoked, GitHub PAT Access Revoked>> |Access to private GitHub organization resources was revoked for a PAT. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Rule Type: BBR], [Data Source: Github] |8.3.0 |1
+|<<github-pat-access-revoked, GitHub PAT Access Revoked>> |Access to private GitHub organization resources was revoked for a PAT. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<github-protected-branch-settings-changed, GitHub Protected Branch Settings Changed>> |This rule detects setting modifications for protected branches of a GitHub repository. Branch protection rules can be used to enforce certain workflows or requirements before a contributor can push changes to a branch in your repository. Changes to these protected branch settings should be investigated and verified as legitimate activity. Unauthorized changes could be used to lower your organization's security posture and leave you exposed for future attacks. |[Domain: Cloud], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Github] |8.3.0 |2
+|<<github-protected-branch-settings-changed, GitHub Protected Branch Settings Changed>> |This rule detects setting modifications for protected branches of a GitHub repository. Branch protection rules can be used to enforce certain workflows or requirements before a contributor can push changes to a branch in your repository. Changes to these protected branch settings should be investigated and verified as legitimate activity. Unauthorized changes could be used to lower your organization's security posture and leave you exposed for future attacks. |[Domain: Cloud], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Github] |None |3
 
-|<<github-repo-created, GitHub Repo Created>> |A new GitHub repository was created. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |8.3.0 |1
+|<<github-repo-created, GitHub Repo Created>> |A new GitHub repository was created. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<github-repository-deleted, GitHub Repository Deleted>> |This rule detects when a GitHub repository is deleted within your organization. Repositories are a critical component used within an organization to manage work, collaborate with others and release products to the public. Any delete action against a repository should be investigated to determine it's validity. Unauthorized deletion of organization repositories could cause irreversible loss of intellectual property and indicate compromise within your organization. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Data Source: Github] |8.3.0 |2
+|<<github-repository-deleted, GitHub Repository Deleted>> |This rule detects when a GitHub repository is deleted within your organization. Repositories are a critical component used within an organization to manage work, collaborate with others and release products to the public. Any delete action against a repository should be investigated to determine it's validity. Unauthorized deletion of organization repositories could cause irreversible loss of intellectual property and indicate compromise within your organization. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Data Source: Github] |None |2
 
-|<<github-ueba-multiple-alerts-from-a-github-account, GitHub UEBA - Multiple Alerts from a GitHub Account>> |This rule is part of the "GitHub UEBA - Unusual Activity from Account Pack", and leverages alert data to determine when multiple alerts are executed by the same user in a timespan of one hour. Analysts can use this to prioritize triage and response, as these alerts are a higher indicator of compromised user accounts or PATs. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: Higher-Order Rule], [Data Source: Github] |8.3.0 |1
+|<<github-ueba-multiple-alerts-from-a-github-account, GitHub UEBA - Multiple Alerts from a GitHub Account>> |This rule is part of the "GitHub UEBA - Unusual Activity from Account Pack", and leverages alert data to determine when multiple alerts are executed by the same user in a timespan of one hour. Analysts can use this to prioritize triage and response, as these alerts are a higher indicator of compromised user accounts or PATs. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Rule Type: Higher-Order Rule], [Data Source: Github] |None |1
 
-|<<github-user-blocked-from-organization, GitHub User Blocked From Organization>> |A GitHub user was blocked from access to an organization. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Rule Type: BBR], [Data Source: Github] |8.3.0 |1
+|<<github-user-blocked-from-organization, GitHub User Blocked From Organization>> |A GitHub user was blocked from access to an organization. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<google-drive-ownership-transferred-via-google-workspace, Google Drive Ownership Transferred via Google Workspace>> |Drive and Docs is a Google Workspace service that allows users to leverage Google Drive and Google Docs. Access to files is based on inherited permissions from the child organizational unit the user belongs to which is scoped by administrators. Typically if a user is removed, their files can be transferred to another user by the administrator. This service can also be abused by adversaries to transfer files to an adversary account for potential exfiltration. |[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Collection], [Resources: Investigation Guide] |8.4.0 |106
+|<<google-drive-ownership-transferred-via-google-workspace, Google Drive Ownership Transferred via Google Workspace>> |Drive and Docs is a Google Workspace service that allows users to leverage Google Drive and Google Docs. Access to files is based on inherited permissions from the child organizational unit the user belongs to which is scoped by administrators. Typically if a user is removed, their files can be transferred to another user by the administrator. This service can also be abused by adversaries to transfer files to an adversary account for potential exfiltration. |[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Collection], [Resources: Investigation Guide] |None |106
 
-|<<google-workspace-2sv-policy-disabled, Google Workspace 2SV Policy Disabled>> |Google Workspace admins may setup 2-step verification (2SV) to add an extra layer of security to user accounts by asking users to verify their identity when they use login credentials. Admins have the ability to enforce 2SV from the admin console as well as the methods acceptable for verification and enrollment period. 2SV requires enablement on admin accounts prior to it being enabled for users within organization units. Adversaries may disable 2SV to lower the security requirements to access a valid account. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Persistence], [Resources: Investigation Guide] |8.4.0 |106
+|<<google-workspace-2sv-policy-disabled, Google Workspace 2SV Policy Disabled>> |Google Workspace admins may setup 2-step verification (2SV) to add an extra layer of security to user accounts by asking users to verify their identity when they use login credentials. Admins have the ability to enforce 2SV from the admin console as well as the methods acceptable for verification and enrollment period. 2SV requires enablement on admin accounts prior to it being enabled for users within organization units. Adversaries may disable 2SV to lower the security requirements to access a valid account. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Persistence], [Resources: Investigation Guide] |None |106
 
-|<<google-workspace-api-access-granted-via-domain-wide-delegation-of-authority, Google Workspace API Access Granted via Domain-Wide Delegation of Authority>> |Detects when a domain-wide delegation of authority is granted to a service account. Domain-wide delegation can be configured to grant third-party and internal applications to access the data of Google Workspace users. An adversary may configure domain-wide delegation to maintain access to their target’s data. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |8.4.0 |205
+|<<google-workspace-api-access-granted-via-domain-wide-delegation-of-authority, Google Workspace API Access Granted via Domain-Wide Delegation of Authority>> |Detects when a domain-wide delegation of authority is granted to a service account. Domain-wide delegation can be configured to grant third-party and internal applications to access the data of Google Workspace users. An adversary may configure domain-wide delegation to maintain access to their target’s data. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |None |205
 
-|<<google-workspace-admin-role-assigned-to-a-user, Google Workspace Admin Role Assigned to a User>> |Assigning the administrative role to a user will grant them access to the Google Admin console and grant them administrator privileges which allow them to access and manage various resources and applications. An adversary may create a new administrator account for persistence or apply the admin role to an existing user to carry out further intrusion efforts. Users with super-admin privileges can bypass single-sign on if enabled in Google Workspace. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Resources: Investigation Guide] |8.4.0 |206
+|<<google-workspace-admin-role-assigned-to-a-user, Google Workspace Admin Role Assigned to a User>> |Assigning the administrative role to a user will grant them access to the Google Admin console and grant them administrator privileges which allow them to access and manage various resources and applications. An adversary may create a new administrator account for persistence or apply the admin role to an existing user to carry out further intrusion efforts. Users with super-admin privileges can bypass single-sign on if enabled in Google Workspace. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Resources: Investigation Guide] |None |206
 
-|<<google-workspace-admin-role-deletion, Google Workspace Admin Role Deletion>> |Detects when a custom admin role is deleted. An adversary may delete a custom admin role in order to impact the permissions or capabilities of system administrators. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Impact], [Resources: Investigation Guide] |8.4.0 |205
+|<<google-workspace-admin-role-deletion, Google Workspace Admin Role Deletion>> |Detects when a custom admin role is deleted. An adversary may delete a custom admin role in order to impact the permissions or capabilities of system administrators. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Impact], [Resources: Investigation Guide] |None |205
 
-|<<google-workspace-bitlocker-setting-disabled, Google Workspace Bitlocker Setting Disabled>> |Google Workspace administrators whom manage Windows devices and have Windows device management enabled may also enable BitLocker drive encryption to mitigate unauthorized data access on lost or stolen computers. Adversaries with valid account access may disable BitLocker to access sensitive data on an endpoint added to Google Workspace device management. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Defense Evasion], [Resources: Investigation Guide] |8.4.0 |106
+|<<google-workspace-bitlocker-setting-disabled, Google Workspace Bitlocker Setting Disabled>> |Google Workspace administrators whom manage Windows devices and have Windows device management enabled may also enable BitLocker drive encryption to mitigate unauthorized data access on lost or stolen computers. Adversaries with valid account access may disable BitLocker to access sensitive data on an endpoint added to Google Workspace device management. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Defense Evasion], [Resources: Investigation Guide] |None |106
 
-|<<google-workspace-custom-admin-role-created, Google Workspace Custom Admin Role Created>> |Detects when a custom admin role is created in Google Workspace. An adversary may create a custom admin role in order to elevate the permissions of other user accounts and persist in their target’s environment. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |8.4.0 |205
+|<<google-workspace-custom-admin-role-created, Google Workspace Custom Admin Role Created>> |Detects when a custom admin role is created in Google Workspace. An adversary may create a custom admin role in order to elevate the permissions of other user accounts and persist in their target’s environment. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |None |205
 
-|<<google-workspace-custom-gmail-route-created-or-modified, Google Workspace Custom Gmail Route Created or Modified>> |Detects when a custom Gmail route is added or modified in Google Workspace. Adversaries can add a custom e-mail route for outbound mail to route these e-mails to their own inbox of choice for data gathering. This allows adversaries to capture sensitive information from e-mail and potential attachments, such as invoices or payment documents. By default, all email from current Google Workspace users with accounts are routed through a domain's mail server for inbound and outbound mail. |[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Collection], [Resources: Investigation Guide] |8.4.0 |106
+|<<google-workspace-custom-gmail-route-created-or-modified, Google Workspace Custom Gmail Route Created or Modified>> |Detects when a custom Gmail route is added or modified in Google Workspace. Adversaries can add a custom e-mail route for outbound mail to route these e-mails to their own inbox of choice for data gathering. This allows adversaries to capture sensitive information from e-mail and potential attachments, such as invoices or payment documents. By default, all email from current Google Workspace users with accounts are routed through a domain's mail server for inbound and outbound mail. |[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Collection], [Resources: Investigation Guide] |None |106
 
-|<<google-workspace-drive-encryption-key-s-accessed-from-anonymous-user, Google Workspace Drive Encryption Key(s) Accessed from Anonymous User>> |Detects when an external (anonymous) user has viewed, copied or downloaded an encryption key file from a Google Workspace drive. Adversaries may gain access to encryption keys stored in private drives from rogue access links that do not have an expiration. Access to encryption keys may allow adversaries to access sensitive data or authenticate on behalf of users. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Credential Access] |8.4.0 |3
+|<<google-workspace-drive-encryption-key-s-accessed-from-anonymous-user, Google Workspace Drive Encryption Key(s) Accessed from Anonymous User>> |Detects when an external (anonymous) user has viewed, copied or downloaded an encryption key file from a Google Workspace drive. Adversaries may gain access to encryption keys stored in private drives from rogue access links that do not have an expiration. Access to encryption keys may allow adversaries to access sensitive data or authenticate on behalf of users. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Credential Access] |None |3
 
-|<<google-workspace-mfa-enforcement-disabled, Google Workspace MFA Enforcement Disabled>> |Detects when multi-factor authentication (MFA) enforcement is disabled for Google Workspace users. An adversary may disable MFA enforcement in order to weaken an organization’s security controls. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Impact], [Resources: Investigation Guide] |8.4.0 |207
+|<<google-workspace-mfa-enforcement-disabled, Google Workspace MFA Enforcement Disabled>> |Detects when multi-factor authentication (MFA) enforcement is disabled for Google Workspace users. An adversary may disable MFA enforcement in order to weaken an organization’s security controls. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Impact], [Resources: Investigation Guide] |None |207
 
-|<<google-workspace-object-copied-from-external-drive-and-access-granted-to-custom-application, Google Workspace Object Copied from External Drive and Access Granted to Custom Application>> |Detects when a user copies a Google spreadsheet, form, document or script from an external drive. Sequence logic has been added to also detect when a user grants a custom Google application permission via OAuth shortly after. An adversary may send a phishing email to the victim with a Drive object link where "copy" is included in the URI, thus copying the object to the victim's drive. If a container-bound script exists within the object, execution will require permission access via OAuth in which the user has to accept. |[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Initial Access], [Resources: Investigation Guide] |8.4.0 |4
+|<<google-workspace-object-copied-from-external-drive-and-access-granted-to-custom-application, Google Workspace Object Copied from External Drive and Access Granted to Custom Application>> |Detects when a user copies a Google spreadsheet, form, document or script from an external drive. Sequence logic has been added to also detect when a user grants a custom Google application permission via OAuth shortly after. An adversary may send a phishing email to the victim with a Drive object link where "copy" is included in the URI, thus copying the object to the victim's drive. If a container-bound script exists within the object, execution will require permission access via OAuth in which the user has to accept. |[Domain: Cloud], [Data Source: Google Workspace], [Tactic: Initial Access], [Resources: Investigation Guide] |None |4
 
-|<<google-workspace-password-policy-modified, Google Workspace Password Policy Modified>> |Detects when a Google Workspace password policy is modified. An adversary may attempt to modify a password policy in order to weaken an organization’s security controls. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Resources: Investigation Guide] |8.4.0 |205
+|<<google-workspace-password-policy-modified, Google Workspace Password Policy Modified>> |Detects when a Google Workspace password policy is modified. An adversary may attempt to modify a password policy in order to weaken an organization’s security controls. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Resources: Investigation Guide] |None |205
 
-|<<google-workspace-restrictions-for-google-marketplace-modified-to-allow-any-app, Google Workspace Restrictions for Google Marketplace Modified to Allow Any App>> |Detects when the Google Marketplace restrictions are changed to allow any application for users in Google Workspace. Malicious APKs created by adversaries may be uploaded to the Google marketplace but not installed on devices managed within Google Workspace. Administrators should set restrictions to not allow any application from the marketplace for security reasons. Adversaries may enable any app to be installed and executed on mobile devices within a Google Workspace environment prior to distributing the malicious APK to the end user. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Defense Evasion], [Resources: Investigation Guide] |8.4.0 |106
+|<<google-workspace-restrictions-for-google-marketplace-modified-to-allow-any-app, Google Workspace Restrictions for Google Marketplace Modified to Allow Any App>> |Detects when the Google Marketplace restrictions are changed to allow any application for users in Google Workspace. Malicious APKs created by adversaries may be uploaded to the Google marketplace but not installed on devices managed within Google Workspace. Administrators should set restrictions to not allow any application from the marketplace for security reasons. Adversaries may enable any app to be installed and executed on mobile devices within a Google Workspace environment prior to distributing the malicious APK to the end user. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Defense Evasion], [Resources: Investigation Guide] |None |106
 
-|<<google-workspace-role-modified, Google Workspace Role Modified>> |Detects when a custom admin role or its permissions are modified. An adversary may modify a custom admin role in order to elevate the permissions of other user accounts and persist in their target’s environment. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |8.4.0 |205
+|<<google-workspace-role-modified, Google Workspace Role Modified>> |Detects when a custom admin role or its permissions are modified. An adversary may modify a custom admin role in order to elevate the permissions of other user accounts and persist in their target’s environment. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |None |205
 
-|<<google-workspace-suspended-user-account-renewed, Google Workspace Suspended User Account Renewed>> |Detects when a previously suspended user's account is renewed in Google Workspace. An adversary may renew a suspended user account to maintain access to the Google Workspace organization with a valid account. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |8.4.0 |2
+|<<google-workspace-suspended-user-account-renewed, Google Workspace Suspended User Account Renewed>> |Detects when a previously suspended user's account is renewed in Google Workspace. An adversary may renew a suspended user account to maintain access to the Google Workspace organization with a valid account. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |None |2
 
-|<<google-workspace-user-organizational-unit-changed, Google Workspace User Organizational Unit Changed>> |Users in Google Workspace are typically assigned a specific organizational unit that grants them permissions to certain services and roles that are inherited from this organizational unit. Adversaries may compromise a valid account and change which organizational account the user belongs to which then could allow them to inherit permissions to applications and resources inaccessible prior to. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Persistence], [Resources: Investigation Guide] |8.4.0 |106
+|<<google-workspace-user-organizational-unit-changed, Google Workspace User Organizational Unit Changed>> |Users in Google Workspace are typically assigned a specific organizational unit that grants them permissions to certain services and roles that are inherited from this organizational unit. Adversaries may compromise a valid account and change which organizational account the user belongs to which then could allow them to inherit permissions to applications and resources inaccessible prior to. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Configuration Audit], [Tactic: Persistence], [Resources: Investigation Guide] |None |106
 
-|<<group-policy-abuse-for-privilege-addition, Group Policy Abuse for Privilege Addition>> |Detects the first occurrence of a modification to Group Policy Object Attributes to add privileges to user accounts or use them to add users as local admins. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |8.3.0 |109
+|<<group-policy-abuse-for-privilege-addition, Group Policy Abuse for Privilege Addition>> |Detects the first occurrence of a modification to Group Policy Object Attributes to add privileges to user accounts or use them to add users as local admins. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |None |109
 
-|<<group-policy-discovery-via-microsoft-gpresult-utility, Group Policy Discovery via Microsoft GPResult Utility>> |Detects the usage of gpresult.exe to query group policy objects. Attackers may query group policy objects during the reconnaissance phase after compromising a system to gain a better understanding of the active directory environment and possible methods to escalate privileges or move laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |8
+|<<group-policy-discovery-via-microsoft-gpresult-utility, Group Policy Discovery via Microsoft GPResult Utility>> |Detects the usage of gpresult.exe to query group policy objects. Attackers may query group policy objects during the reconnaissance phase after compromising a system to gain a better understanding of the active directory environment and possible methods to escalate privileges or move laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |8
 
-|<<halfbaked-command-and-control-beacon, Halfbaked Command and Control Beacon>> |Halfbaked is a malware family used to establish persistence in a contested network. This rule detects a network activity algorithm leveraged by Halfbaked implant beacons for command and control. |[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |8.3.0 |104
+|<<halfbaked-command-and-control-beacon, Halfbaked Command and Control Beacon>> |Halfbaked is a malware family used to establish persistence in a contested network. This rule detects a network activity algorithm leveraged by Halfbaked implant beacons for command and control. |[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |None |104
 
-|<<hidden-files-and-directories-via-hidden-flag, Hidden Files and Directories via Hidden Flag>> |Identify activity related where adversaries can add the 'hidden' flag to files to hide them from the user in an attempt to evade detection. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |2
+|<<hidden-files-and-directories-via-hidden-flag, Hidden Files and Directories via Hidden Flag>> |Identify activity related where adversaries can add the 'hidden' flag to files to hide them from the user in an attempt to evade detection. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |2
 
-|<<high-mean-of-process-arguments-in-an-rdp-session, High Mean of Process Arguments in an RDP Session>> |A machine learning job has detected unusually high number of process arguments in an RDP session. Executing sophisticated attacks such as lateral movement can involve the use of complex commands, obfuscation mechanisms, redirection and piping, which in turn increases the number of arguments in a command. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<high-mean-of-process-arguments-in-an-rdp-session, High Mean of Process Arguments in an RDP Session>> |A machine learning job has detected unusually high number of process arguments in an RDP session. Executing sophisticated attacks such as lateral movement can involve the use of complex commands, obfuscation mechanisms, redirection and piping, which in turn increases the number of arguments in a command. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<high-mean-of-rdp-session-duration, High Mean of RDP Session Duration>> |A machine learning job has detected unusually high mean of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<high-mean-of-rdp-session-duration, High Mean of RDP Session Duration>> |A machine learning job has detected unusually high mean of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<high-number-of-cloned-github-repos-from-pat, High Number of Cloned GitHub Repos From PAT>> |Detects a high number of unique private repo clone events originating from a single personal access token within a short time period. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Data Source: Github] |8.8.0 |1
+|<<high-number-of-cloned-github-repos-from-pat, High Number of Cloned GitHub Repos From PAT>> |Detects a high number of unique private repo clone events originating from a single personal access token within a short time period. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Execution], [Data Source: Github] |None |1
 
 |<<high-number-of-okta-user-password-reset-or-unlock-attempts, High Number of Okta User Password Reset or Unlock Attempts>> |Identifies a high number of Okta user password reset or account unlock attempts. An adversary may attempt to obtain unauthorized access to Okta user accounts using these methods and attempt to blend in with normal activity in their target's environment and evade detection. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Defense Evasion] |8.10.0 |208
 
-|<<high-number-of-process-terminations, High Number of Process Terminations>> |This rule identifies a high number (10) of process terminations via pkill from the same host within a short time period. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |112
+|<<high-number-of-process-terminations, High Number of Process Terminations>> |This rule identifies a high number (10) of process terminations via pkill from the same host within a short time period. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |112
+
+|<<high-number-of-process-and-or-service-terminations, High Number of Process and/or Service Terminations>> |This rule identifies a high number (10) of process terminations (stop, delete, or suspend) from the same host within a short time period. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<high-number-of-process-and-or-service-terminations, High Number of Process and/or Service Terminations>> |This rule identifies a high number (10) of process terminations (stop, delete, or suspend) from the same host within a short time period. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<high-variance-in-rdp-session-duration, High Variance in RDP Session Duration>> |A machine learning job has detected unusually high variance of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<high-variance-in-rdp-session-duration, High Variance in RDP Session Duration>> |A machine learning job has detected unusually high variance of RDP session duration. Long RDP sessions can be used to evade detection mechanisms via session persistence, and might be used to perform tasks such as lateral movement, that might require uninterrupted access to a compromised machine. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<host-files-system-changes-via-windows-subsystem-for-linux, Host Files System Changes via Windows Subsystem for Linux>> |Detects files creation and modification on the host system from the the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |7
 
-|<<host-files-system-changes-via-windows-subsystem-for-linux, Host Files System Changes via Windows Subsystem for Linux>> |Detects files creation and modification on the host system from the the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |7
+|<<hosts-file-modified, Hosts File Modified>> |The hosts file on endpoints is used to control manual IP address to hostname resolutions. The hosts file is the first point of lookup for DNS hostname resolution so if adversaries can modify the endpoint hosts file, they can route traffic to malicious infrastructure. This rule detects modifications to the hosts file on Microsoft Windows, Linux (Ubuntu or RHEL) and macOS systems. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |108
 
-|<<hosts-file-modified, Hosts File Modified>> |The hosts file on endpoints is used to control manual IP address to hostname resolutions. The hosts file is the first point of lookup for DNS hostname resolution so if adversaries can modify the endpoint hosts file, they can route traffic to malicious infrastructure. This rule detects modifications to the hosts file on Microsoft Windows, Linux (Ubuntu or RHEL) and macOS systems. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |108
+|<<hping-process-activity, Hping Process Activity>> |Hping ran on a Linux host. Hping is a FOSS command-line packet analyzer and has the ability to construct network packets for a wide variety of network security testing applications, including scanning and firewall auditing. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |108
 
-|<<hping-process-activity, Hping Process Activity>> |Hping ran on a Linux host. Hping is a FOSS command-line packet analyzer and has the ability to construct network packets for a wide variety of network security testing applications, including scanning and firewall auditing. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |108
+|<<iis-http-logging-disabled, IIS HTTP Logging Disabled>> |Identifies when Internet Information Services (IIS) HTTP Logging is disabled on a server. An attacker with IIS server access via a webshell or other mechanism can disable HTTP Logging as an effective anti-forensics measure. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |110
 
-|<<iis-http-logging-disabled, IIS HTTP Logging Disabled>> |Identifies when Internet Information Services (IIS) HTTP Logging is disabled on a server. An attacker with IIS server access via a webshell or other mechanism can disable HTTP Logging as an effective anti-forensics measure. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |110
+|<<ipsec-nat-traversal-port-activity, IPSEC NAT Traversal Port Activity>> |This rule detects events that could be describing IPSEC NAT Traversal traffic. IPSEC is a VPN technology that allows one system to talk to another using encrypted tunnels. NAT Traversal enables these tunnels to communicate over the Internet where one of the sides is behind a NAT router gateway. This may be common on your network, but this technique is also used by threat actors to avoid detection. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |None |104
 
-|<<ipsec-nat-traversal-port-activity, IPSEC NAT Traversal Port Activity>> |This rule detects events that could be describing IPSEC NAT Traversal traffic. IPSEC is a VPN technology that allows one system to talk to another using encrypted tunnels. NAT Traversal enables these tunnels to communicate over the Internet where one of the sides is behind a NAT router gateway. This may be common on your network, but this technique is also used by threat actors to avoid detection. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |8.3.0 |104
+|<<image-file-execution-options-injection, Image File Execution Options Injection>> |The Debugger and SilentProcessExit registry keys can allow an adversary to intercept the execution of files, causing a different process to be executed. This functionality can be abused by an adversary to establish persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<image-file-execution-options-injection, Image File Execution Options Injection>> |The Debugger and SilentProcessExit registry keys can allow an adversary to intercept the execution of files, causing a different process to be executed. This functionality can be abused by an adversary to establish persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<image-loaded-with-invalid-signature, Image Loaded with Invalid Signature>> |Identifies binaries that are loaded and with an invalid code signature. This may indicate an attempt to masquerade as a signed binary. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |None |2
 
-|<<image-loaded-with-invalid-signature, Image Loaded with Invalid Signature>> |Identifies binaries that are loaded and with an invalid code signature. This may indicate an attempt to masquerade as a signed binary. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |2
+|<<imageload-via-windows-update-auto-update-client, ImageLoad via Windows Update Auto Update Client>> |Identifies abuse of the Windows Update Auto Update Client (wuauclt.exe) to load an arbitrary DLL. This behavior is used as a defense evasion technique to blend-in malicious activity with legitimate Windows software. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<imageload-via-windows-update-auto-update-client, ImageLoad via Windows Update Auto Update Client>> |Identifies abuse of the Windows Update Auto Update Client (wuauclt.exe) to load an arbitrary DLL. This behavior is used as a defense evasion technique to blend-in malicious activity with legitimate Windows software. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<inbound-connection-to-an-unsecure-elasticsearch-node, Inbound Connection to an Unsecure Elasticsearch Node>> |Identifies Elasticsearch nodes that do not have Transport Layer Security (TLS), and/or lack authentication, and are accepting inbound network connections over the default Elasticsearch port. |[Use Case: Threat Detection], [Tactic: Initial Access], [Domain: Endpoint] |None |104
 
-|<<inbound-connection-to-an-unsecure-elasticsearch-node, Inbound Connection to an Unsecure Elasticsearch Node>> |Identifies Elasticsearch nodes that do not have Transport Layer Security (TLS), and/or lack authentication, and are accepting inbound network connections over the default Elasticsearch port. |[Use Case: Threat Detection], [Tactic: Initial Access], [Domain: Endpoint] |8.3.0 |104
+|<<incoming-dcom-lateral-movement-via-mshta, Incoming DCOM Lateral Movement via MSHTA>> |Identifies the use of Distributed Component Object Model (DCOM) to execute commands from a remote host, which are launched via the HTA Application COM Object. This behavior may indicate an attacker abusing a DCOM application to move laterally while attempting to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<incoming-dcom-lateral-movement-via-mshta, Incoming DCOM Lateral Movement via MSHTA>> |Identifies the use of Distributed Component Object Model (DCOM) to execute commands from a remote host, which are launched via the HTA Application COM Object. This behavior may indicate an attacker abusing a DCOM application to move laterally while attempting to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<incoming-dcom-lateral-movement-with-mmc, Incoming DCOM Lateral Movement with MMC>> |Identifies the use of Distributed Component Object Model (DCOM) to run commands from a remote host, which are launched via the MMC20 Application COM Object. This behavior may indicate an attacker abusing a DCOM application to move laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<incoming-dcom-lateral-movement-with-mmc, Incoming DCOM Lateral Movement with MMC>> |Identifies the use of Distributed Component Object Model (DCOM) to run commands from a remote host, which are launched via the MMC20 Application COM Object. This behavior may indicate an attacker abusing a DCOM application to move laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<incoming-dcom-lateral-movement-with-shellbrowserwindow-or-shellwindows, Incoming DCOM Lateral Movement with ShellBrowserWindow or ShellWindows>> |Identifies use of Distributed Component Object Model (DCOM) to run commands from a remote host, which are launched via the ShellBrowserWindow or ShellWindows Application COM Object. This behavior may indicate an attacker abusing a DCOM application to stealthily move laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<incoming-dcom-lateral-movement-with-shellbrowserwindow-or-shellwindows, Incoming DCOM Lateral Movement with ShellBrowserWindow or ShellWindows>> |Identifies use of Distributed Component Object Model (DCOM) to run commands from a remote host, which are launched via the ShellBrowserWindow or ShellWindows Application COM Object. This behavior may indicate an attacker abusing a DCOM application to stealthily move laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<incoming-execution-via-powershell-remoting, Incoming Execution via PowerShell Remoting>> |Identifies remote execution via Windows PowerShell remoting. Windows PowerShell remoting allows a user to run any Windows PowerShell command on one or more remote computers. This could be an indication of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<incoming-execution-via-powershell-remoting, Incoming Execution via PowerShell Remoting>> |Identifies remote execution via Windows PowerShell remoting. Windows PowerShell remoting allows a user to run any Windows PowerShell command on one or more remote computers. This could be an indication of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<incoming-execution-via-winrm-remote-shell, Incoming Execution via WinRM Remote Shell>> |Identifies remote execution via Windows Remote Management (WinRM) remote shell on a target host. This could be an indication of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<incoming-execution-via-winrm-remote-shell, Incoming Execution via WinRM Remote Shell>> |Identifies remote execution via Windows Remote Management (WinRM) remote shell on a target host. This could be an indication of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<indirect-command-execution-via-forfiles-pcalua, Indirect Command Execution via Forfiles/Pcalua>> |Identifies indirect command execution via Program Compatibility Assistant (pcalua.exe) or forfiles.exe. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |None |2
 
-|<<indirect-command-execution-via-forfiles-pcalua, Indirect Command Execution via Forfiles/Pcalua>> |Identifies indirect command execution via Program Compatibility Assistant (pcalua.exe) or forfiles.exe. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<ingress-transfer-via-windows-bits, Ingress Transfer via Windows BITS>> |Identifies downloads of executable and archive files via the Windows Background Intelligent Transfer Service (BITS). Adversaries could leverage Windows BITS transfer jobs to download remote payloads. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Command and Control], [Data Source: Elastic Defend] |None |7
 
-|<<ingress-transfer-via-windows-bits, Ingress Transfer via Windows BITS>> |Identifies downloads of executable and archive files via the Windows Background Intelligent Transfer Service (BITS). Adversaries could leverage Windows BITS transfer jobs to download remote payloads. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Command and Control], [Data Source: Elastic Defend] |8.3.0 |7
+|<<insecure-aws-ec2-vpc-security-group-ingress-rule-added, Insecure AWS EC2 VPC Security Group Ingress Rule Added>> |Identifies when a specified inbound (ingress) rule is added or adjusted for a VPC security group in AWS EC2. This rule detects when a security group rule is added that allows traffic from any IP address or from a specific IP address to common remote access ports, such as 22 (SSH) or 3389 (RDP). Adversaries may add these rules to allow remote access to VPC instances from any location, increasing the attack surface and potentially exposing the instances to unauthorized access. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS EC2], [Use Case: Threat Detection], [Tactic: Defense Evasion] |8.9.0 |1
 
-|<<installutil-activity, InstallUtil Activity>> |InstallUtil is a command-line utility that allows for installation and uninstallation of resources by executing specific installer components specified in .NET binaries. Adversaries may use InstallUtil to proxy the execution of code through a trusted Windows utility. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<installutil-activity, InstallUtil Activity>> |InstallUtil is a command-line utility that allows for installation and uninstallation of resources by executing specific installer components specified in .NET binaries. Adversaries may use InstallUtil to proxy the execution of code through a trusted Windows utility. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |None |2
 
-|<<installutil-process-making-network-connections, InstallUtil Process Making Network Connections>> |Identifies InstallUtil.exe making outbound network connections. This may indicate adversarial activity as InstallUtil is often leveraged by adversaries to execute code and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<installutil-process-making-network-connections, InstallUtil Process Making Network Connections>> |Identifies InstallUtil.exe making outbound network connections. This may indicate adversarial activity as InstallUtil is often leveraged by adversaries to execute code and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<installation-of-custom-shim-databases, Installation of Custom Shim Databases>> |Identifies the installation of custom Application Compatibility Shim databases. This Windows functionality has been abused by attackers to stealthily gain persistence and arbitrary code execution in legitimate Windows processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<installation-of-custom-shim-databases, Installation of Custom Shim Databases>> |Identifies the installation of custom Application Compatibility Shim databases. This Windows functionality has been abused by attackers to stealthily gain persistence and arbitrary code execution in legitimate Windows processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<installation-of-security-support-provider, Installation of Security Support Provider>> |Identifies registry modifications related to the Windows Security Support Provider (SSP) configuration. Adversaries may abuse this to establish persistence in an environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<installation-of-security-support-provider, Installation of Security Support Provider>> |Identifies registry modifications related to the Windows Security Support Provider (SSP) configuration. Adversaries may abuse this to establish persistence in an environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<interactive-exec-command-launched-against-a-running-container, Interactive Exec Command Launched Against A Running Container>> |This rule detects interactive 'exec' events launched against a container using the 'exec' command. Using the 'exec' command in a pod allows a user to establish a temporary shell session and execute any process/command inside the container. This rule specifically targets higher-risk interactive commands that allow real-time interaction with a container's shell. A malicious actor could use this level of access to further compromise the container environment or attempt a container breakout. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |8.8.0 |2
+|<<interactive-exec-command-launched-against-a-running-container, Interactive Exec Command Launched Against A Running Container>> |This rule detects interactive 'exec' events launched against a container using the 'exec' command. Using the 'exec' command in a pod allows a user to establish a temporary shell session and execute any process/command inside the container. This rule specifically targets higher-risk interactive commands that allow real-time interaction with a container's shell. A malicious actor could use this level of access to further compromise the container environment or attempt a container breakout. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |None |2
 
-|<<interactive-logon-by-an-unusual-process, Interactive Logon by an Unusual Process>> |Identifies interactive logon attempt with alternate credentials and by an unusual process. Adversaries may create a new token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |3
+|<<interactive-logon-by-an-unusual-process, Interactive Logon by an Unusual Process>> |Identifies interactive logon attempt with alternate credentials and by an unusual process. Adversaries may create a new token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |3
 
-|<<interactive-terminal-spawned-via-perl, Interactive Terminal Spawned via Perl>> |Identifies when a terminal (tty) is spawned via Perl. Attackers may upgrade a simple reverse shell to a fully interactive tty after obtaining initial access to a host. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |108
+|<<interactive-terminal-spawned-via-perl, Interactive Terminal Spawned via Perl>> |Identifies when a terminal (tty) is spawned via Perl. Attackers may upgrade a simple reverse shell to a fully interactive tty after obtaining initial access to a host. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |108
 
-|<<interactive-terminal-spawned-via-python, Interactive Terminal Spawned via Python>> |Identifies when a terminal (tty) is spawned via Python. Attackers may upgrade a simple reverse shell to a fully interactive tty after obtaining initial access to a host. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<interactive-terminal-spawned-via-python, Interactive Terminal Spawned via Python>> |Identifies when a terminal (tty) is spawned via Python. Attackers may upgrade a simple reverse shell to a fully interactive tty after obtaining initial access to a host. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<krbtgt-delegation-backdoor, KRBTGT Delegation Backdoor>> |Identifies the modification of the msDS-AllowedToDelegateTo attribute to KRBTGT. Attackers can use this technique to maintain persistence to the domain by having the ability to request tickets for the KRBTGT service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |8.3.0 |107
+|<<krbtgt-delegation-backdoor, KRBTGT Delegation Backdoor>> |Identifies the modification of the msDS-AllowedToDelegateTo attribute to KRBTGT. Attackers can use this technique to maintain persistence to the domain by having the ability to request tickets for the KRBTGT service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |None |107
 
-|<<kerberos-cached-credentials-dumping, Kerberos Cached Credentials Dumping>> |Identifies the use of the Kerberos credential cache (kcc) utility to dump locally cached Kerberos tickets. Adversaries may attempt to dump credential material in the form of tickets that can be leveraged for lateral movement. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.3.0 |106
+|<<kerberos-cached-credentials-dumping, Kerberos Cached Credentials Dumping>> |Identifies the use of the Kerberos credential cache (kcc) utility to dump locally cached Kerberos tickets. Adversaries may attempt to dump credential material in the form of tickets that can be leveraged for lateral movement. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |106
 
-|<<kerberos-pre-authentication-disabled-for-user, Kerberos Pre-authentication Disabled for User>> |Identifies the modification of an account's Kerberos pre-authentication options. An adversary with GenericWrite/GenericAll rights over the account can maliciously modify these settings to perform offline password cracking attacks such as AS-REP roasting. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |8.3.0 |110
+|<<kerberos-pre-authentication-disabled-for-user, Kerberos Pre-authentication Disabled for User>> |Identifies the modification of an account's Kerberos pre-authentication options. An adversary with GenericWrite/GenericAll rights over the account can maliciously modify these settings to perform offline password cracking attacks such as AS-REP roasting. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |None |110
 
-|<<kerberos-traffic-from-unusual-process, Kerberos Traffic from Unusual Process>> |Identifies network connections to the standard Kerberos port from an unusual process. On Windows, the only process that normally performs Kerberos traffic from a domain joined host is lsass.exe. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |110
+|<<kerberos-traffic-from-unusual-process, Kerberos Traffic from Unusual Process>> |Identifies network connections to the standard Kerberos port from an unusual process. On Windows, the only process that normally performs Kerberos traffic from a domain joined host is lsass.exe. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |110
 
-|<<kernel-driver-load, Kernel Driver Load>> |Detects the loading of a Linux kernel module through system calls. Threat actors may leverage Linux kernel modules to load a rootkit on a system providing them with complete control and the ability to hide from security products. As other rules monitor for the addition of Linux kernel modules through system utilities or .ko files, this rule covers the gap that evasive rootkits leverage by monitoring for kernel module additions on the lowest level through auditd_manager. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |8.3.0 |4
+|<<kernel-driver-load, Kernel Driver Load>> |Detects the loading of a Linux kernel module through system calls. Threat actors may leverage Linux kernel modules to load a rootkit on a system providing them with complete control and the ability to hide from security products. As other rules monitor for the addition of Linux kernel modules through system utilities or .ko files, this rule covers the gap that evasive rootkits leverage by monitoring for kernel module additions on the lowest level through auditd_manager. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |None |4
 
-|<<kernel-driver-load-by-non-root-user, Kernel Driver Load by non-root User>> |Detects the loading of a Linux kernel module by a non-root user through system calls. Threat actors may leverage Linux kernel modules to load a rootkit on a system providing them with complete control and the ability to hide from security products. As other rules monitor for the addition of Linux kernel modules through system utilities or .ko files, this rule covers the gap that evasive rootkits leverage by monitoring for kernel module additions on the lowest level through auditd_manager. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |8.3.0 |3
+|<<kernel-driver-load-by-non-root-user, Kernel Driver Load by non-root User>> |Detects the loading of a Linux kernel module by a non-root user through system calls. Threat actors may leverage Linux kernel modules to load a rootkit on a system providing them with complete control and the ability to hide from security products. As other rules monitor for the addition of Linux kernel modules through system utilities or .ko files, this rule covers the gap that evasive rootkits leverage by monitoring for kernel module additions on the lowest level through auditd_manager. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |None |3
 
-|<<kernel-load-or-unload-via-kexec-detected, Kernel Load or Unload via Kexec Detected>> |This detection rule identifies the usage of kexec, helping to uncover unauthorized kernel replacements and potential compromise of the system's integrity. Kexec is a Linux feature that enables the loading and execution of a different kernel without going through the typical boot process. Malicious actors can abuse kexec to bypass security measures, escalate privileges, establish persistence or hide their activities by loading a malicious kernel, enabling them to tamper with the system's trusted state, allowing e.g. a VM Escape. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |6
+|<<kernel-load-or-unload-via-kexec-detected, Kernel Load or Unload via Kexec Detected>> |This detection rule identifies the usage of kexec, helping to uncover unauthorized kernel replacements and potential compromise of the system's integrity. Kexec is a Linux feature that enables the loading and execution of a different kernel without going through the typical boot process. Malicious actors can abuse kexec to bypass security measures, escalate privileges, establish persistence or hide their activities by loading a malicious kernel, enabling them to tamper with the system's trusted state, allowing e.g. a VM Escape. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |6
 
-|<<kernel-module-load-via-insmod, Kernel Module Load via insmod>> |Detects the use of the insmod binary to load a Linux kernel object file. Threat actors can use this binary, given they have root privileges, to load a rootkit on a system providing them with complete control and the ability to hide from security products. Manually loading a kernel module in this manner should not be at all common and can indicate suspcious or malicious behavior. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Rootkit], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |109
+|<<kernel-module-load-via-insmod, Kernel Module Load via insmod>> |Detects the use of the insmod binary to load a Linux kernel object file. Threat actors can use this binary, given they have root privileges, to load a rootkit on a system providing them with complete control and the ability to hide from security products. Manually loading a kernel module in this manner should not be at all common and can indicate suspcious or malicious behavior. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Rootkit], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |109
 
-|<<kernel-module-removal, Kernel Module Removal>> |Kernel modules are pieces of code that can be loaded and unloaded into the kernel upon demand. They extend the functionality of the kernel without the need to reboot the system. This rule identifies attempts to remove a kernel module. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<kernel-module-removal, Kernel Module Removal>> |Kernel modules are pieces of code that can be loaded and unloaded into the kernel upon demand. They extend the functionality of the kernel without the need to reboot the system. This rule identifies attempts to remove a kernel module. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<keychain-password-retrieval-via-command-line, Keychain Password Retrieval via Command Line>> |Adversaries may collect keychain storage data from a system to in order to acquire credentials. Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features, including Wi-Fi and website passwords, secure notes, certificates, and Kerberos. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.3.0 |108
+|<<keychain-password-retrieval-via-command-line, Keychain Password Retrieval via Command Line>> |Adversaries may collect keychain storage data from a system to in order to acquire credentials. Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features, including Wi-Fi and website passwords, secure notes, certificates, and Kerberos. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |108
 
-|<<kirbi-file-creation, Kirbi File Creation>> |Identifies the creation of .kirbi files. The creation of this kind of file is an indicator of an attacker running Kerberos ticket dump utilities, such as Mimikatz, and precedes attacks such as Pass-The-Ticket (PTT), which allows the attacker to impersonate users using Kerberos tickets. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |5
+|<<kirbi-file-creation, Kirbi File Creation>> |Identifies the creation of .kirbi files. The creation of this kind of file is an indicator of an attacker running Kerberos ticket dump utilities, such as Mimikatz, and precedes attacks such as Pass-The-Ticket (PTT), which allows the attacker to impersonate users using Kerberos tickets. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |107
 
-|<<kubernetes-anonymous-request-authorized, Kubernetes Anonymous Request Authorized>> |This rule detects when an unauthenticated user request is authorized within the cluster. Attackers may attempt to use anonymous accounts to gain initial access to the cluster or to avoid attribution of their activities within the cluster. This rule excludes the /healthz, /livez and /readyz endpoints which are commonly accessed anonymously. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Initial Access], [Tactic: Defense Evasion] |8.4.0 |6
+|<<kubernetes-anonymous-request-authorized, Kubernetes Anonymous Request Authorized>> |This rule detects when an unauthenticated user request is authorized within the cluster. Attackers may attempt to use anonymous accounts to gain initial access to the cluster or to avoid attribution of their activities within the cluster. This rule excludes the /healthz, /livez and /readyz endpoints which are commonly accessed anonymously. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Initial Access], [Tactic: Defense Evasion] |None |6
 
-|<<kubernetes-container-created-with-excessive-linux-capabilities, Kubernetes Container Created with Excessive Linux Capabilities>> |This rule detects a container deployed with one or more dangerously permissive Linux capabilities. An attacker with the ability to deploy a container with added capabilities could use this for further execution, lateral movement, or privilege escalation within a cluster. The capabilities detected in this rule have been used in container escapes to the host machine. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |8.4.0 |4
+|<<kubernetes-container-created-with-excessive-linux-capabilities, Kubernetes Container Created with Excessive Linux Capabilities>> |This rule detects a container deployed with one or more dangerously permissive Linux capabilities. An attacker with the ability to deploy a container with added capabilities could use this for further execution, lateral movement, or privilege escalation within a cluster. The capabilities detected in this rule have been used in container escapes to the host machine. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |None |4
 
-|<<kubernetes-denied-service-account-request, Kubernetes Denied Service Account Request>> |This rule detects when a service account makes an unauthorized request for resources from the API server. Service accounts follow a very predictable pattern of behavior. A service account should never send an unauthorized request to the API server. This behavior is likely an indicator of compromise or of a problem within the cluster. An adversary may have gained access to credentials/tokens and this could be an attempt to access or create resources to facilitate further movement or execution within the cluster. |[Data Source: Kubernetes], [Tactic: Discovery] |8.4.0 |5
+|<<kubernetes-denied-service-account-request, Kubernetes Denied Service Account Request>> |This rule detects when a service account makes an unauthorized request for resources from the API server. Service accounts follow a very predictable pattern of behavior. A service account should never send an unauthorized request to the API server. This behavior is likely an indicator of compromise or of a problem within the cluster. An adversary may have gained access to credentials/tokens and this could be an attempt to access or create resources to facilitate further movement or execution within the cluster. |[Data Source: Kubernetes], [Tactic: Discovery] |None |5
 
-|<<kubernetes-exposed-service-created-with-type-nodeport, Kubernetes Exposed Service Created With Type NodePort>> |This rule detects an attempt to create or modify a service as type NodePort. The NodePort service allows a user to externally expose a set of labeled pods to the internet. This creates an open port on every worker node in the cluster that has a pod for that service. When external traffic is received on that open port, it directs it to the specific pod through the service representing it. A malicious user can configure a service as type Nodeport in order to intercept traffic from other pods or nodes, bypassing firewalls and other network security measures configured for load balancers within a cluster. This creates a direct method of communication between the cluster and the outside world, which could be used for more malicious behavior and certainly widens the attack surface of your cluster. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Persistence] |8.4.0 |203
+|<<kubernetes-exposed-service-created-with-type-nodeport, Kubernetes Exposed Service Created With Type NodePort>> |This rule detects an attempt to create or modify a service as type NodePort. The NodePort service allows a user to externally expose a set of labeled pods to the internet. This creates an open port on every worker node in the cluster that has a pod for that service. When external traffic is received on that open port, it directs it to the specific pod through the service representing it. A malicious user can configure a service as type Nodeport in order to intercept traffic from other pods or nodes, bypassing firewalls and other network security measures configured for load balancers within a cluster. This creates a direct method of communication between the cluster and the outside world, which could be used for more malicious behavior and certainly widens the attack surface of your cluster. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Persistence] |None |203
 
-|<<kubernetes-pod-created-with-hostipc, Kubernetes Pod Created With HostIPC>> |This rule detects an attempt to create or modify a pod using the host IPC namespace. This gives access to data used by any pod that also use the hosts IPC namespace. If any process on the host or any processes in a pod uses the hosts inter-process communication mechanisms (shared memory, semaphore arrays, message queues, etc.), an attacker can read/write to those same mechanisms. They may look for files in /dev/shm or use ipcs to check for any IPC facilities being used. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |8.4.0 |203
+|<<kubernetes-pod-created-with-hostipc, Kubernetes Pod Created With HostIPC>> |This rule detects an attempt to create or modify a pod using the host IPC namespace. This gives access to data used by any pod that also use the hosts IPC namespace. If any process on the host or any processes in a pod uses the hosts inter-process communication mechanisms (shared memory, semaphore arrays, message queues, etc.), an attacker can read/write to those same mechanisms. They may look for files in /dev/shm or use ipcs to check for any IPC facilities being used. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |None |203
 
-|<<kubernetes-pod-created-with-hostnetwork, Kubernetes Pod Created With HostNetwork>> |This rules detects an attempt to create or modify a pod attached to the host network. HostNetwork allows a pod to use the node network namespace. Doing so gives the pod access to any service running on localhost of the host. An attacker could use this access to snoop on network activity of other pods on the same node or bypass restrictive network policies applied to its given namespace. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |8.4.0 |203
+|<<kubernetes-pod-created-with-hostnetwork, Kubernetes Pod Created With HostNetwork>> |This rules detects an attempt to create or modify a pod attached to the host network. HostNetwork allows a pod to use the node network namespace. Doing so gives the pod access to any service running on localhost of the host. An attacker could use this access to snoop on network activity of other pods on the same node or bypass restrictive network policies applied to its given namespace. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |None |203
 
-|<<kubernetes-pod-created-with-hostpid, Kubernetes Pod Created With HostPID>> |This rule detects an attempt to create or modify a pod attached to the host PID namespace. HostPID allows a pod to access all the processes running on the host and could allow an attacker to take malicious action. When paired with ptrace this can be used to escalate privileges outside of the container. When paired with a privileged container, the pod can see all of the processes on the host. An attacker can enter the init system (PID 1) on the host. From there, they could execute a shell and continue to escalate privileges to root. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |8.4.0 |203
+|<<kubernetes-pod-created-with-hostpid, Kubernetes Pod Created With HostPID>> |This rule detects an attempt to create or modify a pod attached to the host PID namespace. HostPID allows a pod to access all the processes running on the host and could allow an attacker to take malicious action. When paired with ptrace this can be used to escalate privileges outside of the container. When paired with a privileged container, the pod can see all of the processes on the host. An attacker can enter the init system (PID 1) on the host. From there, they could execute a shell and continue to escalate privileges to root. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |None |203
 
-|<<kubernetes-pod-created-with-a-sensitive-hostpath-volume, Kubernetes Pod created with a Sensitive hostPath Volume>> |This rule detects when a pod is created with a sensitive volume of type hostPath. A hostPath volume type mounts a sensitive file or folder from the node to the container. If the container gets compromised, the attacker can use this mount for gaining access to the node. There are many ways a container with unrestricted access to the host filesystem can escalate privileges, including reading data from other containers, and accessing tokens of more privileged pods. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |8.4.0 |203
+|<<kubernetes-pod-created-with-a-sensitive-hostpath-volume, Kubernetes Pod created with a Sensitive hostPath Volume>> |This rule detects when a pod is created with a sensitive volume of type hostPath. A hostPath volume type mounts a sensitive file or folder from the node to the container. If the container gets compromised, the attacker can use this mount for gaining access to the node. There are many ways a container with unrestricted access to the host filesystem can escalate privileges, including reading data from other containers, and accessing tokens of more privileged pods. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |None |203
 
-|<<kubernetes-privileged-pod-created, Kubernetes Privileged Pod Created>> |This rule detects when a user creates a pod/container running in privileged mode. A highly privileged container has access to the node's resources and breaks the isolation between containers. If compromised, an attacker can use the privileged container to gain access to the underlying host. Gaining access to the host may provide the adversary with the opportunity to achieve follow-on objectives, such as establishing persistence, moving laterally within the environment, or setting up a command and control channel on the host. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |8.4.0 |203
+|<<kubernetes-privileged-pod-created, Kubernetes Privileged Pod Created>> |This rule detects when a user creates a pod/container running in privileged mode. A highly privileged container has access to the node's resources and breaks the isolation between containers. If compromised, an attacker can use the privileged container to gain access to the underlying host. Gaining access to the host may provide the adversary with the opportunity to achieve follow-on objectives, such as establishing persistence, moving laterally within the environment, or setting up a command and control channel on the host. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |None |203
 
-|<<kubernetes-suspicious-assignment-of-controller-service-account, Kubernetes Suspicious Assignment of Controller Service Account>> |This rule detects a request to attach a controller service account to an existing or new pod running in the kube-system namespace. By default, controllers running as part of the API Server utilize admin-equivalent service accounts hosted in the kube-system namespace. Controller service accounts aren't normally assigned to running pods and could indicate adversary behavior within the cluster. An attacker that can create or modify pods or pod controllers in the kube-system namespace, can assign one of these admin-equivalent service accounts to a pod and abuse their powerful token to escalate privileges and gain complete cluster control. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |8.4.0 |6
+|<<kubernetes-suspicious-assignment-of-controller-service-account, Kubernetes Suspicious Assignment of Controller Service Account>> |This rule detects a request to attach a controller service account to an existing or new pod running in the kube-system namespace. By default, controllers running as part of the API Server utilize admin-equivalent service accounts hosted in the kube-system namespace. Controller service accounts aren't normally assigned to running pods and could indicate adversary behavior within the cluster. An attacker that can create or modify pods or pod controllers in the kube-system namespace, can assign one of these admin-equivalent service accounts to a pod and abuse their powerful token to escalate privileges and gain complete cluster control. |[Data Source: Kubernetes], [Tactic: Execution], [Tactic: Privilege Escalation] |None |6
 
-|<<kubernetes-suspicious-self-subject-review, Kubernetes Suspicious Self-Subject Review>> |This rule detects when a service account or node attempts to enumerate their own permissions via the selfsubjectaccessreview or selfsubjectrulesreview APIs. This is highly unusual behavior for non-human identities like service accounts and nodes. An adversary may have gained access to credentials/tokens and this could be an attempt to determine what privileges they have to facilitate further movement or execution within the cluster. |[Data Source: Kubernetes], [Tactic: Discovery] |8.4.0 |203
+|<<kubernetes-suspicious-self-subject-review, Kubernetes Suspicious Self-Subject Review>> |This rule detects when a service account or node attempts to enumerate their own permissions via the selfsubjectaccessreview or selfsubjectrulesreview APIs. This is highly unusual behavior for non-human identities like service accounts and nodes. An adversary may have gained access to credentials/tokens and this could be an attempt to determine what privileges they have to facilitate further movement or execution within the cluster. |[Data Source: Kubernetes], [Tactic: Discovery] |None |203
 
-|<<kubernetes-user-exec-into-pod, Kubernetes User Exec into Pod>> |This rule detects a user attempt to establish a shell session into a pod using the 'exec' command. Using the 'exec' command in a pod allows a user to establish a temporary shell session and execute any process/commands in the pod. An adversary may call bash to gain a persistent interactive shell which will allow access to any data the pod has permissions to, including secrets. |[Data Source: Kubernetes], [Tactic: Execution] |8.4.0 |203
+|<<kubernetes-user-exec-into-pod, Kubernetes User Exec into Pod>> |This rule detects a user attempt to establish a shell session into a pod using the 'exec' command. Using the 'exec' command in a pod allows a user to establish a temporary shell session and execute any process/commands in the pod. An adversary may call bash to gain a persistent interactive shell which will allow access to any data the pod has permissions to, including secrets. |[Data Source: Kubernetes], [Tactic: Execution] |None |203
 
-|<<lsass-memory-dump-creation, LSASS Memory Dump Creation>> |Identifies the creation of a Local Security Authority Subsystem Service (lsass.exe) default memory dump. This may indicate a credential access attempt via trusted system utilities such as Task Manager (taskmgr.exe) and SQL Dumper (sqldumper.exe) or known pentesting tools such as Dumpert and AndrewSpecial. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<lsass-memory-dump-creation, LSASS Memory Dump Creation>> |Identifies the creation of a Local Security Authority Subsystem Service (lsass.exe) default memory dump. This may indicate a credential access attempt via trusted system utilities such as Task Manager (taskmgr.exe) and SQL Dumper (sqldumper.exe) or known pentesting tools such as Dumpert and AndrewSpecial. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<lsass-memory-dump-handle-access, LSASS Memory Dump Handle Access>> |Identifies handle requests for the Local Security Authority Subsystem Service (LSASS) object access with specific access masks that many tools with a capability to dump memory to disk use (0x1fffff, 0x1010, 0x120089). This rule is tool agnostic as it has been validated against a host of various LSASS dump tools such as SharpDump, Procdump, Mimikatz, Comsvcs etc. It detects this behavior at a low level and does not depend on a specific tool or dump file name. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide] |8.3.0 |110
+|<<lsass-memory-dump-handle-access, LSASS Memory Dump Handle Access>> |Identifies handle requests for the Local Security Authority Subsystem Service (LSASS) object access with specific access masks that many tools with a capability to dump memory to disk use (0x1fffff, 0x1010, 0x120089). This rule is tool agnostic as it has been validated against a host of various LSASS dump tools such as SharpDump, Procdump, Mimikatz, Comsvcs etc. It detects this behavior at a low level and does not depend on a specific tool or dump file name. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide] |None |110
 
-|<<lsass-process-access-via-windows-api, LSASS Process Access via Windows API>> |Identifies access attempts to the LSASS handle, which may indicate an attempt to dump credentials from LSASS memory. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Execution], [Data Source: Elastic Defend] |8.7.0 |7
+|<<lsass-process-access-via-windows-api, LSASS Process Access via Windows API>> |Identifies access attempts to the LSASS handle, which may indicate an attempt to dump credentials from LSASS memory. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Execution], [Data Source: Elastic Defend] |None |7
 
-|<<lateral-movement-via-startup-folder, Lateral Movement via Startup Folder>> |Identifies suspicious file creations in the startup folder of a remote system. An adversary could abuse this to move laterally by dropping a malicious script or executable that will be executed after a reboot or user logon. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<lateral-movement-via-startup-folder, Lateral Movement via Startup Folder>> |Identifies suspicious file creations in the startup folder of a remote system. An adversary could abuse this to move laterally by dropping a malicious script or executable that will be executed after a reboot or user logon. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<launch-agent-creation-or-modification-and-immediate-loading, Launch Agent Creation or Modification and Immediate Loading>> |An adversary can establish persistence by installing a new launch agent that executes at login by using launchd or launchctl to load a plist into the appropriate directories. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<launch-agent-creation-or-modification-and-immediate-loading, Launch Agent Creation or Modification and Immediate Loading>> |An adversary can establish persistence by installing a new launch agent that executes at login by using launchd or launchctl to load a plist into the appropriate directories. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<launchdaemon-creation-or-modification-and-immediate-loading, LaunchDaemon Creation or Modification and Immediate Loading>> |Indicates the creation or modification of a launch daemon, which adversaries may use to repeatedly execute malicious payloads as part of persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<launchdaemon-creation-or-modification-and-immediate-loading, LaunchDaemon Creation or Modification and Immediate Loading>> |Indicates the creation or modification of a launch daemon, which adversaries may use to repeatedly execute malicious payloads as part of persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<linux-group-creation, Linux Group Creation>> |Identifies attempts to create a new group. Attackers may create new groups to establish persistence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide] |8.3.0 |5
+|<<linux-group-creation, Linux Group Creation>> |Identifies attempts to create a new group. Attackers may create new groups to establish persistence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide] |None |5
 
-|<<linux-process-hooking-via-gdb, Linux Process Hooking via GDB>> |This rule monitors for potential memory dumping through gdb. Attackers may leverage memory dumping techniques to attempt secret extraction from privileged processes. Tools that display this behavior include "truffleproc" and "bash-memory-dump". This behavior should not happen by default, and should be investigated thoroughly. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |3
+|<<linux-process-hooking-via-gdb, Linux Process Hooking via GDB>> |This rule monitors for potential memory dumping through gdb. Attackers may leverage memory dumping techniques to attempt secret extraction from privileged processes. Tools that display this behavior include "truffleproc" and "bash-memory-dump". This behavior should not happen by default, and should be investigated thoroughly. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |3
 
-|<<linux-restricted-shell-breakout-via-linux-binary-s, Linux Restricted Shell Breakout via Linux Binary(s)>> |Identifies the abuse of a Linux binary to break out of a restricted shell or environment by spawning an interactive system shell. The activity of spawning a shell from a binary is not common behavior for a user or system administrator, and may indicate an attempt to evade detection, increase capabilities or enhance the stability of an adversary. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<linux-restricted-shell-breakout-via-linux-binary-s, Linux Restricted Shell Breakout via Linux Binary(s)>> |Identifies the abuse of a Linux binary to break out of a restricted shell or environment by spawning an interactive system shell. The activity of spawning a shell from a binary is not common behavior for a user or system administrator, and may indicate an attempt to evade detection, increase capabilities or enhance the stability of an adversary. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<linux-system-information-discovery, Linux System Information Discovery>> |Enrich process events with uname and other command lines that imply Linux system information discovery. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |3
+|<<linux-system-information-discovery, Linux System Information Discovery>> |Enrich process events with uname and other command lines that imply Linux system information discovery. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |3
 
-|<<linux-user-account-creation, Linux User Account Creation>> |Identifies attempts to create new users. Attackers may add new users to establish persistence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide] |8.3.0 |5
+|<<linux-user-account-creation, Linux User Account Creation>> |Identifies attempts to create new users. Attackers may add new users to establish persistence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide] |None |5
 
-|<<linux-user-added-to-privileged-group, Linux User Added to Privileged Group>> |Identifies attempts to add a user to a privileged group. Attackers may add users to a privileged group in order to establish persistence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |6
+|<<linux-user-added-to-privileged-group, Linux User Added to Privileged Group>> |Identifies attempts to add a user to a privileged group. Attackers may add users to a privileged group in order to establish persistence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |6
 
-|<<linux-init-pid-1-secret-dump-via-gdb, Linux init (PID 1) Secret Dump via GDB>> |This rule monitors for the potential memory dump of the init process (PID 1) through gdb. Attackers may leverage memory dumping techniques to attempt secret extraction from privileged processes. Tools that display this behavior include "truffleproc" and "bash-memory-dump". This behavior should not happen by default, and should be investigated thoroughly. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |6
+|<<linux-init-pid-1-secret-dump-via-gdb, Linux init (PID 1) Secret Dump via GDB>> |This rule monitors for the potential memory dump of the init process (PID 1) through gdb. Attackers may leverage memory dumping techniques to attempt secret extraction from privileged processes. Tools that display this behavior include "truffleproc" and "bash-memory-dump". This behavior should not happen by default, and should be investigated thoroughly. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |6
 
-|<<local-account-tokenfilter-policy-disabled, Local Account TokenFilter Policy Disabled>> |Identifies registry modification to the LocalAccountTokenFilterPolicy policy. If this value exists (which doesn't by default) and is set to 1, then remote connections from all local members of Administrators are granted full high-integrity tokens during negotiation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |8
+|<<local-account-tokenfilter-policy-disabled, Local Account TokenFilter Policy Disabled>> |Identifies registry modification to the LocalAccountTokenFilterPolicy policy. If this value exists (which doesn't by default) and is set to 1, then remote connections from all local members of Administrators are granted full high-integrity tokens during negotiation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |110
 
-|<<local-scheduled-task-creation, Local Scheduled Task Creation>> |Indicates the creation of a scheduled task. Adversaries can use these to establish persistence, move laterally, and/or escalate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<local-scheduled-task-creation, Local Scheduled Task Creation>> |Indicates the creation of a scheduled task. Adversaries can use these to establish persistence, move laterally, and/or escalate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
 |<<mfa-deactivation-with-no-re-activation-for-okta-user-account, MFA Deactivation with no Re-Activation for Okta User Account>> |Detects multi-factor authentication (MFA) deactivation with no subsequent re-activation for an Okta user account. An adversary may deactivate MFA for an Okta user account in order to weaken the authentication requirements for the account. |[Tactic: Persistence], [Use Case: Identity and Access Audit], [Data Source: Okta], [Domain: Cloud] |8.10.0 |207
 
-|<<mfa-disabled-for-google-workspace-organization, MFA Disabled for Google Workspace Organization>> |Detects when multi-factor authentication (MFA) is disabled for a Google Workspace organization. An adversary may attempt to modify a password policy in order to weaken an organization’s security controls. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Resources: Investigation Guide] |8.4.0 |205
+|<<mfa-disabled-for-google-workspace-organization, MFA Disabled for Google Workspace Organization>> |Detects when multi-factor authentication (MFA) is disabled for a Google Workspace organization. An adversary may attempt to modify a password policy in order to weaken an organization’s security controls. |[Domain: Cloud], [Data Source: Google Workspace], [Use Case: Identity and Access Audit], [Tactic: Persistence], [Resources: Investigation Guide] |None |205
 
-|<<ms-office-macro-security-registry-modifications, MS Office Macro Security Registry Modifications>> |Microsoft Office Products offer options for users and developers to control the security settings for running and using Macros. Adversaries may abuse these security settings to modify the default behavior of the Office Application to trust future macros and/or disable security warnings, which could increase their chances of establishing persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Sysmon] |8.3.0 |107
+|<<ms-office-macro-security-registry-modifications, MS Office Macro Security Registry Modifications>> |Microsoft Office Products offer options for users and developers to control the security settings for running and using Macros. Adversaries may abuse these security settings to modify the default behavior of the Office Application to trust future macros and/or disable security warnings, which could increase their chances of establishing persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Sysmon] |None |107
 
-|<<macos-installer-package-spawns-network-event, MacOS Installer Package Spawns Network Event>> |Detects the execution of a MacOS installer package with an abnormal child process (e.g bash) followed immediately by a network connection via a suspicious process (e.g curl). Threat actors will build and distribute malicious MacOS installer packages, which have a .pkg extension, many times imitating valid software in order to persuade and infect their victims often using the package files (e.g pre/post install scripts etc.) to download additional tools or malicious software. If this rule fires it should indicate the installation of a malicious or suspicious package. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Command and Control], [Data Source: Elastic Defend] |8.3.0 |107
+|<<macos-installer-package-spawns-network-event, MacOS Installer Package Spawns Network Event>> |Detects the execution of a MacOS installer package with an abnormal child process (e.g bash) followed immediately by a network connection via a suspicious process (e.g curl). Threat actors will build and distribute malicious MacOS installer packages, which have a .pkg extension, many times imitating valid software in order to persuade and infect their victims often using the package files (e.g pre/post install scripts etc.) to download additional tools or malicious software. If this rule fires it should indicate the installation of a malicious or suspicious package. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Command and Control], [Data Source: Elastic Defend] |None |107
 
-|<<machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain, Machine Learning Detected DGA activity using a known SUNBURST DNS domain>> |A supervised machine learning model has identified a DNS question name that used by the SUNBURST malware and is predicted to be the result of a Domain Generation Algorithm. |[Domain: Network], [Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |8.9.0 |3
+|<<machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain, Machine Learning Detected DGA activity using a known SUNBURST DNS domain>> |A supervised machine learning model has identified a DNS question name that used by the SUNBURST malware and is predicted to be the result of a Domain Generation Algorithm. |[Domain: Network], [Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |None |4
 
-|<<machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain, Machine Learning Detected a DNS Request Predicted to be a DGA Domain>> |A supervised machine learning model has identified a DNS question name that is predicted to be the result of a Domain Generation Algorithm (DGA), which could indicate command and control network activity. |[Domain: Network], [Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |8.9.0 |3
+|<<machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain, Machine Learning Detected a DNS Request Predicted to be a DGA Domain>> |A supervised machine learning model has identified a DNS question name that is predicted to be the result of a Domain Generation Algorithm (DGA), which could indicate command and control network activity. |[Domain: Network], [Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |None |4
 
-|<<machine-learning-detected-a-dns-request-with-a-high-dga-probability-score, Machine Learning Detected a DNS Request With a High DGA Probability Score>> |A supervised machine learning model has identified a DNS question name with a high probability of sourcing from a Domain Generation Algorithm (DGA), which could indicate command and control network activity. |[Domain: Network], [Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |8.9.0 |3
+|<<machine-learning-detected-a-dns-request-with-a-high-dga-probability-score, Machine Learning Detected a DNS Request With a High DGA Probability Score>> |A supervised machine learning model has identified a DNS question name with a high probability of sourcing from a Domain Generation Algorithm (DGA), which could indicate command and control network activity. |[Domain: Network], [Domain: Endpoint], [Data Source: Elastic Defend], [Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |None |4
 
-|<<machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity, Machine Learning Detected a Suspicious Windows Event Predicted to be Malicious Activity>> |A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious. |[OS: Windows], [Data Source: Elastic Endgame], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |8.9.0 |4
+|<<machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity, Machine Learning Detected a Suspicious Windows Event Predicted to be Malicious Activity>> |A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious. |[OS: Windows], [Data Source: Elastic Endgame], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |None |5
 
-|<<machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score, Machine Learning Detected a Suspicious Windows Event with a High Malicious Probability Score>> |A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious. |[OS: Windows], [Data Source: Elastic Endgame], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |8.9.0 |4
+|<<machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score, Machine Learning Detected a Suspicious Windows Event with a High Malicious Probability Score>> |A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious. |[OS: Windows], [Data Source: Elastic Endgame], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |None |5
 
-|<<malware-detected-elastic-endgame, Malware - Detected - Elastic Endgame>> |Elastic Endgame detected Malware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |8.3.0 |103
+|<<malware-detected-elastic-endgame, Malware - Detected - Elastic Endgame>> |Elastic Endgame detected Malware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |None |103
 
-|<<malware-prevented-elastic-endgame, Malware - Prevented - Elastic Endgame>> |Elastic Endgame prevented Malware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |8.3.0 |103
+|<<malware-prevented-elastic-endgame, Malware - Prevented - Elastic Endgame>> |Elastic Endgame prevented Malware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |None |103
 
-|<<masquerading-space-after-filename, Masquerading Space After Filename>> |This rules identifies a process created from an executable with a space appended to the end of the filename. This may indicate an attempt to masquerade a malicious file as benign to gain user execution. When a space is added to the end of certain files, the OS will execute the file according to it's true filetype instead of it's extension. Adversaries can hide a program's true filetype by changing the extension of the file. They can then add a space to the end of the name so that the OS automatically executes the file when it's double-clicked. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |6
+|<<masquerading-space-after-filename, Masquerading Space After Filename>> |This rules identifies a process created from an executable with a space appended to the end of the filename. This may indicate an attempt to masquerade a malicious file as benign to gain user execution. When a space is added to the end of certain files, the OS will execute the file according to it's true filetype instead of it's extension. Adversaries can hide a program's true filetype by changing the extension of the file. They can then add a space to the end of the name so that the OS automatically executes the file when it's double-clicked. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |6
 
-|<<member-removed-from-github-organization, Member Removed From GitHub Organization>> |A member was removed or their invitation to join was removed from a GitHub Organization. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Rule Type: BBR], [Data Source: Github] |8.3.0 |1
+|<<member-removed-from-github-organization, Member Removed From GitHub Organization>> |A member was removed or their invitation to join was removed from a GitHub Organization. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Impact], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<memory-dump-file-with-unusual-extension, Memory Dump File with Unusual Extension>> |Identifies the creation of a memory dump file with an unusual extension, which can indicate an attempt to disguise a memory dump as another file type to bypass security defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |2
+|<<memory-dump-file-with-unusual-extension, Memory Dump File with Unusual Extension>> |Identifies the creation of a memory dump file with an unusual extension, which can indicate an attempt to disguise a memory dump as another file type to bypass security defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |None |2
 
-|<<microsoft-365-exchange-anti-phish-policy-deletion, Microsoft 365 Exchange Anti-Phish Policy Deletion>> |Identifies the deletion of an anti-phishing policy in Microsoft 365. By default, Microsoft 365 includes built-in features that help protect users from phishing attacks. Anti-phishing polices increase this protection by refining settings to better detect and prevent attacks. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |8.8.0 |206
+|<<microsoft-365-exchange-anti-phish-policy-deletion, Microsoft 365 Exchange Anti-Phish Policy Deletion>> |Identifies the deletion of an anti-phishing policy in Microsoft 365. By default, Microsoft 365 includes built-in features that help protect users from phishing attacks. Anti-phishing polices increase this protection by refining settings to better detect and prevent attacks. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |None |206
 
-|<<microsoft-365-exchange-anti-phish-rule-modification, Microsoft 365 Exchange Anti-Phish Rule Modification>> |Identifies the modification of an anti-phishing rule in Microsoft 365. By default, Microsoft 365 includes built-in features that help protect users from phishing attacks. Anti-phishing rules increase this protection by refining settings to better detect and prevent attacks. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |8.8.0 |206
+|<<microsoft-365-exchange-anti-phish-rule-modification, Microsoft 365 Exchange Anti-Phish Rule Modification>> |Identifies the modification of an anti-phishing rule in Microsoft 365. By default, Microsoft 365 includes built-in features that help protect users from phishing attacks. Anti-phishing rules increase this protection by refining settings to better detect and prevent attacks. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |None |206
 
-|<<microsoft-365-exchange-dkim-signing-configuration-disabled, Microsoft 365 Exchange DKIM Signing Configuration Disabled>> |Identifies when a DomainKeys Identified Mail (DKIM) signing configuration is disabled in Microsoft 365. With DKIM in Microsoft 365, messages that are sent from Exchange Online will be cryptographically signed. This will allow the receiving email system to validate that the messages were generated by a server that the organization authorized and were not spoofed. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Persistence] |8.8.0 |206
+|<<microsoft-365-exchange-dkim-signing-configuration-disabled, Microsoft 365 Exchange DKIM Signing Configuration Disabled>> |Identifies when a DomainKeys Identified Mail (DKIM) signing configuration is disabled in Microsoft 365. With DKIM in Microsoft 365, messages that are sent from Exchange Online will be cryptographically signed. This will allow the receiving email system to validate that the messages were generated by a server that the organization authorized and were not spoofed. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Persistence] |None |206
 
-|<<microsoft-365-exchange-dlp-policy-removed, Microsoft 365 Exchange DLP Policy Removed>> |Identifies when a Data Loss Prevention (DLP) policy is removed in Microsoft 365. An adversary may remove a DLP policy to evade existing DLP monitoring. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.8.0 |206
+|<<microsoft-365-exchange-dlp-policy-removed, Microsoft 365 Exchange DLP Policy Removed>> |Identifies when a Data Loss Prevention (DLP) policy is removed in Microsoft 365. An adversary may remove a DLP policy to evade existing DLP monitoring. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |206
 
-|<<microsoft-365-exchange-malware-filter-policy-deletion, Microsoft 365 Exchange Malware Filter Policy Deletion>> |Identifies when a malware filter policy has been deleted in Microsoft 365. A malware filter policy is used to alert administrators that an internal user sent a message that contained malware. This may indicate an account or machine compromise that would need to be investigated. Deletion of a malware filter policy may be done to evade detection. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.8.0 |206
+|<<microsoft-365-exchange-malware-filter-policy-deletion, Microsoft 365 Exchange Malware Filter Policy Deletion>> |Identifies when a malware filter policy has been deleted in Microsoft 365. A malware filter policy is used to alert administrators that an internal user sent a message that contained malware. This may indicate an account or machine compromise that would need to be investigated. Deletion of a malware filter policy may be done to evade detection. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |206
 
-|<<microsoft-365-exchange-malware-filter-rule-modification, Microsoft 365 Exchange Malware Filter Rule Modification>> |Identifies when a malware filter rule has been deleted or disabled in Microsoft 365. An adversary or insider threat may want to modify a malware filter rule to evade detection. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.8.0 |206
+|<<microsoft-365-exchange-malware-filter-rule-modification, Microsoft 365 Exchange Malware Filter Rule Modification>> |Identifies when a malware filter rule has been deleted or disabled in Microsoft 365. An adversary or insider threat may want to modify a malware filter rule to evade detection. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |206
 
-|<<microsoft-365-exchange-management-group-role-assignment, Microsoft 365 Exchange Management Group Role Assignment>> |Identifies when a new role is assigned to a management group in Microsoft 365. An adversary may attempt to add a role in order to maintain persistence in an environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.8.0 |206
+|<<microsoft-365-exchange-management-group-role-assignment, Microsoft 365 Exchange Management Group Role Assignment>> |Identifies when a new role is assigned to a management group in Microsoft 365. An adversary may attempt to add a role in order to maintain persistence in an environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Persistence] |None |206
 
-|<<microsoft-365-exchange-safe-attachment-rule-disabled, Microsoft 365 Exchange Safe Attachment Rule Disabled>> |Identifies when a safe attachment rule is disabled in Microsoft 365. Safe attachment rules can extend malware protections to include routing all messages and attachments without a known malware signature to a special hypervisor environment. An adversary or insider threat may disable a safe attachment rule to exfiltrate data or evade defenses. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |8.8.0 |206
+|<<microsoft-365-exchange-safe-attachment-rule-disabled, Microsoft 365 Exchange Safe Attachment Rule Disabled>> |Identifies when a safe attachment rule is disabled in Microsoft 365. Safe attachment rules can extend malware protections to include routing all messages and attachments without a known malware signature to a special hypervisor environment. An adversary or insider threat may disable a safe attachment rule to exfiltrate data or evade defenses. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Defense Evasion] |None |206
 
-|<<microsoft-365-exchange-safe-link-policy-disabled, Microsoft 365 Exchange Safe Link Policy Disabled>> |Identifies when a Safe Link policy is disabled in Microsoft 365. Safe Link policies for Office applications extend phishing protection to documents that contain hyperlinks, even after they have been delivered to a user. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |8.8.0 |206
+|<<microsoft-365-exchange-safe-link-policy-disabled, Microsoft 365 Exchange Safe Link Policy Disabled>> |Identifies when a Safe Link policy is disabled in Microsoft 365. Safe Link policies for Office applications extend phishing protection to documents that contain hyperlinks, even after they have been delivered to a user. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Initial Access] |None |206
 
-|<<microsoft-365-exchange-transport-rule-creation, Microsoft 365 Exchange Transport Rule Creation>> |Identifies a transport rule creation in Microsoft 365. As a best practice, Exchange Online mail transport rules should not be set to forward email to domains outside of your organization. An adversary may create transport rules to exfiltrate data. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Exfiltration] |8.8.0 |206
+|<<microsoft-365-exchange-transport-rule-creation, Microsoft 365 Exchange Transport Rule Creation>> |Identifies a transport rule creation in Microsoft 365. As a best practice, Exchange Online mail transport rules should not be set to forward email to domains outside of your organization. An adversary may create transport rules to exfiltrate data. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Exfiltration] |None |206
 
-|<<microsoft-365-exchange-transport-rule-modification, Microsoft 365 Exchange Transport Rule Modification>> |Identifies when a transport rule has been disabled or deleted in Microsoft 365. Mail flow rules (also known as transport rules) are used to identify and take action on messages that flow through your organization. An adversary or insider threat may modify a transport rule to exfiltrate data or evade defenses. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Exfiltration] |8.8.0 |206
+|<<microsoft-365-exchange-transport-rule-modification, Microsoft 365 Exchange Transport Rule Modification>> |Identifies when a transport rule has been disabled or deleted in Microsoft 365. Mail flow rules (also known as transport rules) are used to identify and take action on messages that flow through your organization. An adversary or insider threat may modify a transport rule to exfiltrate data or evade defenses. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Exfiltration] |None |206
 
-|<<microsoft-365-global-administrator-role-assigned, Microsoft 365 Global Administrator Role Assigned>> |In Azure Active Directory (Azure AD), permissions to manage resources are assigned using roles. The Global Administrator is a role that enables users to have access to all administrative features in Azure AD and services that use Azure AD identities like the Microsoft 365 Defender portal, the Microsoft 365 compliance center, Exchange, SharePoint Online, and Skype for Business Online. Attackers can add users as Global Administrators to maintain access and manage all subscriptions and their settings and resources. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Persistence] |8.8.0 |206
+|<<microsoft-365-global-administrator-role-assigned, Microsoft 365 Global Administrator Role Assigned>> |In Azure Active Directory (Azure AD), permissions to manage resources are assigned using roles. The Global Administrator is a role that enables users to have access to all administrative features in Azure AD and services that use Azure AD identities like the Microsoft 365 Defender portal, the Microsoft 365 compliance center, Exchange, SharePoint Online, and Skype for Business Online. Attackers can add users as Global Administrators to maintain access and manage all subscriptions and their settings and resources. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Persistence] |None |206
 
 |<<microsoft-365-impossible-travel-activity, Microsoft 365 Impossible travel activity>> |Identifies when a Microsoft Cloud App Security reported a risky sign-in attempt due to a login associated with an impossible travel. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |None |1
 
-|<<microsoft-365-inbox-forwarding-rule-created, Microsoft 365 Inbox Forwarding Rule Created>> |Identifies when a new Inbox forwarding rule is created in Microsoft 365. Inbox rules process messages in the Inbox based on conditions and take actions. In this case, the rules will forward the emails to a defined address. Attackers can abuse Inbox Rules to intercept and exfiltrate email data without making organization-wide configuration changes or having the corresponding privileges. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Collection] |8.8.0 |206
+|<<microsoft-365-inbox-forwarding-rule-created, Microsoft 365 Inbox Forwarding Rule Created>> |Identifies when a new Inbox forwarding rule is created in Microsoft 365. Inbox rules process messages in the Inbox based on conditions and take actions. In this case, the rules will forward the emails to a defined address. Attackers can abuse Inbox Rules to intercept and exfiltrate email data without making organization-wide configuration changes or having the corresponding privileges. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Collection] |None |206
 
 |<<microsoft-365-mass-download-by-a-single-user, Microsoft 365 Mass download by a single user>> |Identifies when Microsoft Cloud App Security reports that a single user performs more than 50 downloads within 1 minute. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Exfiltration] |None |1
 
-|<<microsoft-365-potential-ransomware-activity, Microsoft 365 Potential ransomware activity>> |Identifies when Microsoft Cloud App Security reports that a user has uploaded files to the cloud that might be infected with ransomware. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Impact] |8.8.0 |206
+|<<microsoft-365-potential-ransomware-activity, Microsoft 365 Potential ransomware activity>> |Identifies when Microsoft Cloud App Security reports that a user has uploaded files to the cloud that might be infected with ransomware. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Impact] |None |206
 
-|<<microsoft-365-teams-custom-application-interaction-allowed, Microsoft 365 Teams Custom Application Interaction Allowed>> |Identifies when custom applications are allowed in Microsoft Teams. If an organization requires applications other than those available in the Teams app store, custom applications can be developed as packages and uploaded. An adversary may abuse this behavior to establish persistence in an environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |8.8.0 |207
+|<<microsoft-365-teams-custom-application-interaction-allowed, Microsoft 365 Teams Custom Application Interaction Allowed>> |Identifies when custom applications are allowed in Microsoft Teams. If an organization requires applications other than those available in the Teams app store, custom applications can be developed as packages and uploaded. An adversary may abuse this behavior to establish persistence in an environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |None |207
 
-|<<microsoft-365-teams-external-access-enabled, Microsoft 365 Teams External Access Enabled>> |Identifies when external access is enabled in Microsoft Teams. External access lets Teams and Skype for Business users communicate with other users that are outside their organization. An adversary may enable external access or add an allowed domain to exfiltrate data or maintain persistence in an environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |8.8.0 |206
+|<<microsoft-365-teams-external-access-enabled, Microsoft 365 Teams External Access Enabled>> |Identifies when external access is enabled in Microsoft Teams. External access lets Teams and Skype for Business users communicate with other users that are outside their organization. An adversary may enable external access or add an allowed domain to exfiltrate data or maintain persistence in an environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |None |206
 
-|<<microsoft-365-teams-guest-access-enabled, Microsoft 365 Teams Guest Access Enabled>> |Identifies when guest access is enabled in Microsoft Teams. Guest access in Teams allows people outside the organization to access teams and channels. An adversary may enable guest access to maintain persistence in an environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |8.8.0 |206
+|<<microsoft-365-teams-guest-access-enabled, Microsoft 365 Teams Guest Access Enabled>> |Identifies when guest access is enabled in Microsoft Teams. Guest access in Teams allows people outside the organization to access teams and channels. An adversary may enable guest access to maintain persistence in an environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |None |206
 
-|<<microsoft-365-unusual-volume-of-file-deletion, Microsoft 365 Unusual Volume of File Deletion>> |Identifies that a user has deleted an unusually large volume of files as reported by Microsoft Cloud App Security. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Impact] |8.8.0 |206
+|<<microsoft-365-unusual-volume-of-file-deletion, Microsoft 365 Unusual Volume of File Deletion>> |Identifies that a user has deleted an unusually large volume of files as reported by Microsoft Cloud App Security. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Impact] |None |206
 
-|<<microsoft-365-user-restricted-from-sending-email, Microsoft 365 User Restricted from Sending Email>> |Identifies when a user has been restricted from sending email due to exceeding sending limits of the service policies per the Security Compliance Center. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |8.8.0 |206
+|<<microsoft-365-user-restricted-from-sending-email, Microsoft 365 User Restricted from Sending Email>> |Identifies when a user has been restricted from sending email due to exceeding sending limits of the service policies per the Security Compliance Center. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |None |206
 
-|<<microsoft-build-engine-started-an-unusual-process, Microsoft Build Engine Started an Unusual Process>> |An instance of MSBuild, the Microsoft Build Engine, started a PowerShell script or the Visual C# Command Line Compiler. This technique is sometimes used to deploy a malicious payload using the Build Engine. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |8.6.0 |211
+|<<microsoft-build-engine-started-an-unusual-process, Microsoft Build Engine Started an Unusual Process>> |An instance of MSBuild, the Microsoft Build Engine, started a PowerShell script or the Visual C# Command Line Compiler. This technique is sometimes used to deploy a malicious payload using the Build Engine. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |None |211
 
-|<<microsoft-build-engine-started-by-a-script-process, Microsoft Build Engine Started by a Script Process>> |An instance of MSBuild, the Microsoft Build Engine, was started by a script or the Windows command interpreter. This behavior is unusual and is sometimes used by malicious payloads. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |8.6.0 |209
+|<<microsoft-build-engine-started-by-a-script-process, Microsoft Build Engine Started by a Script Process>> |An instance of MSBuild, the Microsoft Build Engine, was started by a script or the Windows command interpreter. This behavior is unusual and is sometimes used by malicious payloads. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |None |209
 
-|<<microsoft-build-engine-started-by-a-system-process, Microsoft Build Engine Started by a System Process>> |An instance of MSBuild, the Microsoft Build Engine, was started by Explorer or the WMI (Windows Management Instrumentation) subsystem. This behavior is unusual and is sometimes used by malicious payloads. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<microsoft-build-engine-started-by-a-system-process, Microsoft Build Engine Started by a System Process>> |An instance of MSBuild, the Microsoft Build Engine, was started by Explorer or the WMI (Windows Management Instrumentation) subsystem. This behavior is unusual and is sometimes used by malicious payloads. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<microsoft-build-engine-started-by-an-office-application, Microsoft Build Engine Started by an Office Application>> |An instance of MSBuild, the Microsoft Build Engine, was started by Excel or Word. This is unusual behavior for the Build Engine and could have been caused by an Excel or Word document executing a malicious script payload. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<microsoft-build-engine-started-by-an-office-application, Microsoft Build Engine Started by an Office Application>> |An instance of MSBuild, the Microsoft Build Engine, was started by Excel or Word. This is unusual behavior for the Build Engine and could have been caused by an Excel or Word document executing a malicious script payload. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<microsoft-build-engine-using-an-alternate-name, Microsoft Build Engine Using an Alternate Name>> |An instance of MSBuild, the Microsoft Build Engine, was started after being renamed. This is uncommon behavior and may indicate an attempt to run unnoticed or undetected. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |112
+|<<microsoft-build-engine-using-an-alternate-name, Microsoft Build Engine Using an Alternate Name>> |An instance of MSBuild, the Microsoft Build Engine, was started after being renamed. This is uncommon behavior and may indicate an attempt to run unnoticed or undetected. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |112
 
-|<<microsoft-exchange-server-um-spawning-suspicious-processes, Microsoft Exchange Server UM Spawning Suspicious Processes>> |Identifies suspicious processes being spawned by the Microsoft Exchange Server Unified Messaging (UM) service. This activity has been observed exploiting CVE-2021-26857. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |109
+|<<microsoft-exchange-server-um-spawning-suspicious-processes, Microsoft Exchange Server UM Spawning Suspicious Processes>> |Identifies suspicious processes being spawned by the Microsoft Exchange Server Unified Messaging (UM) service. This activity has been observed exploiting CVE-2021-26857. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |109
 
-|<<microsoft-exchange-server-um-writing-suspicious-files, Microsoft Exchange Server UM Writing Suspicious Files>> |Identifies suspicious files being written by the Microsoft Exchange Server Unified Messaging (UM) service. This activity has been observed exploiting CVE-2021-26858. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<microsoft-exchange-server-um-writing-suspicious-files, Microsoft Exchange Server UM Writing Suspicious Files>> |Identifies suspicious files being written by the Microsoft Exchange Server Unified Messaging (UM) service. This activity has been observed exploiting CVE-2021-26858. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<microsoft-exchange-transport-agent-install-script, Microsoft Exchange Transport Agent Install Script>> |Identifies the use of Cmdlets and methods related to Microsoft Exchange Transport Agents install. Adversaries may leverage malicious Microsoft Exchange Transport Agents to execute tasks in response to adversary-defined criteria, establishing persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: PowerShell Logs], [Rule Type: BBR] |8.3.0 |5
+|<<microsoft-exchange-transport-agent-install-script, Microsoft Exchange Transport Agent Install Script>> |Identifies the use of Cmdlets and methods related to Microsoft Exchange Transport Agents install. Adversaries may leverage malicious Microsoft Exchange Transport Agents to execute tasks in response to adversary-defined criteria, establishing persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: PowerShell Logs], [Rule Type: BBR] |None |5
 
-|<<microsoft-exchange-worker-spawning-suspicious-processes, Microsoft Exchange Worker Spawning Suspicious Processes>> |Identifies suspicious processes being spawned by the Microsoft Exchange Server worker process (w3wp). This activity may indicate exploitation activity or access to an existing web shell backdoor. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<microsoft-exchange-worker-spawning-suspicious-processes, Microsoft Exchange Worker Spawning Suspicious Processes>> |Identifies suspicious processes being spawned by the Microsoft Exchange Server worker process (w3wp). This activity may indicate exploitation activity or access to an existing web shell backdoor. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<microsoft-iis-connection-strings-decryption, Microsoft IIS Connection Strings Decryption>> |Identifies use of aspnet_regiis to decrypt Microsoft IIS connection strings. An attacker with Microsoft IIS web server access via a webshell or alike can decrypt and dump any hardcoded connection strings, such as the MSSQL service account password using aspnet_regiis command. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<microsoft-iis-connection-strings-decryption, Microsoft IIS Connection Strings Decryption>> |Identifies use of aspnet_regiis to decrypt Microsoft IIS connection strings. An attacker with Microsoft IIS web server access via a webshell or alike can decrypt and dump any hardcoded connection strings, such as the MSSQL service account password using aspnet_regiis command. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<microsoft-iis-service-account-password-dumped, Microsoft IIS Service Account Password Dumped>> |Identifies the Internet Information Services (IIS) command-line tool, AppCmd, being used to list passwords. An attacker with IIS web server access via a web shell can decrypt and dump the IIS AppPool service account password using AppCmd. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<microsoft-iis-service-account-password-dumped, Microsoft IIS Service Account Password Dumped>> |Identifies the Internet Information Services (IIS) command-line tool, AppCmd, being used to list passwords. An attacker with IIS web server access via a web shell can decrypt and dump the IIS AppPool service account password using AppCmd. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<microsoft-windows-defender-tampering, Microsoft Windows Defender Tampering>> |Identifies when one or more features on Microsoft Defender are disabled. Adversaries may disable or tamper with Microsoft Defender features to evade detection and conceal malicious behavior. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<microsoft-windows-defender-tampering, Microsoft Windows Defender Tampering>> |Identifies when one or more features on Microsoft Defender are disabled. Adversaries may disable or tamper with Microsoft Defender features to evade detection and conceal malicious behavior. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<mimikatz-memssp-log-file-detected, Mimikatz Memssp Log File Detected>> |Identifies the password log file from the default Mimikatz memssp module. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<mimikatz-memssp-log-file-detected, Mimikatz Memssp Log File Detected>> |Identifies the password log file from the default Mimikatz memssp module. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |211
 
-|<<modification-of-amsienable-registry-key, Modification of AmsiEnable Registry Key>> |Identifies modifications of the AmsiEnable registry key to 0, which disables the Antimalware Scan Interface (AMSI). An adversary can modify this key to disable AMSI protections. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<modification-of-amsienable-registry-key, Modification of AmsiEnable Registry Key>> |Identifies modifications of the AmsiEnable registry key to 0, which disables the Antimalware Scan Interface (AMSI). An adversary can modify this key to disable AMSI protections. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<modification-of-boot-configuration, Modification of Boot Configuration>> |Identifies use of bcdedit.exe to delete boot configuration data. This tactic is sometimes used as by malware or an attacker as a destructive technique. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<modification-of-boot-configuration, Modification of Boot Configuration>> |Identifies use of bcdedit.exe to delete boot configuration data. This tactic is sometimes used as by malware or an attacker as a destructive technique. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<modification-of-dynamic-linker-preload-shared-object, Modification of Dynamic Linker Preload Shared Object>> |Identifies modification of the dynamic linker preload shared object (ld.so.preload). Adversaries may execute malicious payloads by hijacking the dynamic linker used to load libraries. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |209
+|<<modification-of-dynamic-linker-preload-shared-object, Modification of Dynamic Linker Preload Shared Object>> |Identifies modification of the dynamic linker preload shared object (ld.so.preload). Adversaries may execute malicious payloads by hijacking the dynamic linker used to load libraries. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |209
 
-|<<modification-of-dynamic-linker-preload-shared-object-inside-a-container, Modification of Dynamic Linker Preload Shared Object Inside A Container>> |This rule detects the creation or modification of the dynamic linker preload shared object (ld.so.preload) inside a container. The Linux dynamic linker is used to load libraries needed by a program at runtime. Adversaries may hijack the dynamic linker by modifying the /etc/ld.so.preload file to point to malicious libraries. This behavior can be used to grant unauthorized access to system resources and has been used to evade detection of malicious processes in container environments. |[Data Source: Elastic Defend for Containers], [Domain: Container], [Tactic: Defense Evasion] |8.8.0 |1
+|<<modification-of-dynamic-linker-preload-shared-object-inside-a-container, Modification of Dynamic Linker Preload Shared Object Inside A Container>> |This rule detects the creation or modification of the dynamic linker preload shared object (ld.so.preload) inside a container. The Linux dynamic linker is used to load libraries needed by a program at runtime. Adversaries may hijack the dynamic linker by modifying the /etc/ld.so.preload file to point to malicious libraries. This behavior can be used to grant unauthorized access to system resources and has been used to evade detection of malicious processes in container environments. |[Data Source: Elastic Defend for Containers], [Domain: Container], [Tactic: Defense Evasion] |None |1
 
 |<<modification-of-environment-variable-via-unsigned-or-untrusted-parent, Modification of Environment Variable via Unsigned or Untrusted Parent>> |Identifies modifications to an environment variable using the built-in launchctl command. Adversaries may execute their own malicious payloads by hijacking certain environment variables to load arbitrary libraries or bypass certain restrictions. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.11.0 |206
 
-|<<modification-of-openssh-binaries, Modification of OpenSSH Binaries>> |Adversaries may modify SSH related binaries for persistence or credential access by patching sensitive functions to enable unauthorized access or by logging SSH credentials for exfiltration. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<modification-of-openssh-binaries, Modification of OpenSSH Binaries>> |Adversaries may modify SSH related binaries for persistence or credential access by patching sensitive functions to enable unauthorized access or by logging SSH credentials for exfiltration. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<modification-of-safari-settings-via-defaults-command, Modification of Safari Settings via Defaults Command>> |Identifies changes to the Safari configuration using the built-in defaults command. Adversaries may attempt to enable or disable certain Safari settings, such as enabling JavaScript from Apple Events to ease in the hijacking of the users browser. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |106
+|<<modification-of-safari-settings-via-defaults-command, Modification of Safari Settings via Defaults Command>> |Identifies changes to the Safari configuration using the built-in defaults command. Adversaries may attempt to enable or disable certain Safari settings, such as enabling JavaScript from Apple Events to ease in the hijacking of the users browser. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |106
 
-|<<modification-of-standard-authentication-module-or-configuration, Modification of Standard Authentication Module or Configuration>> |Adversaries may modify the standard authentication module for persistence via patching the normal authorization process or modifying the login configuration to allow unauthorized access or elevate privileges. |[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Data Source: Elastic Defend] |8.6.0 |204
+|<<modification-of-standard-authentication-module-or-configuration, Modification of Standard Authentication Module or Configuration>> |Adversaries may modify the standard authentication module for persistence via patching the normal authorization process or modifying the login configuration to allow unauthorized access or elevate privileges. |[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Data Source: Elastic Defend] |None |204
 
-|<<modification-of-wdigest-security-provider, Modification of WDigest Security Provider>> |Identifies attempts to modify the WDigest security provider in the registry to force the user's password to be stored in clear text in memory. This behavior can be indicative of an adversary attempting to weaken the security configuration of an endpoint. Once the UseLogonCredential value is modified, the adversary may attempt to dump clear text passwords from memory. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<modification-of-wdigest-security-provider, Modification of WDigest Security Provider>> |Identifies attempts to modify the WDigest security provider in the registry to force the user's password to be stored in clear text in memory. This behavior can be indicative of an adversary attempting to weaken the security configuration of an endpoint. Once the UseLogonCredential value is modified, the adversary may attempt to dump clear text passwords from memory. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<modification-of-the-mspkiaccountcredentials, Modification of the msPKIAccountCredentials>> |Identify the modification of the msPKIAccountCredentials attribute in an Active Directory User Object. Attackers can abuse the credentials roaming feature to overwrite an arbitrary file for privilege escalation. ms-PKI-AccountCredentials contains binary large objects (BLOBs) of encrypted credential objects from the credential manager store, private keys, certificates, and certificate requests. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Data Source: Active Directory], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring] |8.3.0 |9
+|<<modification-of-the-mspkiaccountcredentials, Modification of the msPKIAccountCredentials>> |Identify the modification of the msPKIAccountCredentials attribute in an Active Directory User Object. Attackers can abuse the credentials roaming feature to overwrite an arbitrary file for privilege escalation. ms-PKI-AccountCredentials contains binary large objects (BLOBs) of encrypted credential objects from the credential manager store, private keys, certificates, and certificate requests. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Data Source: Active Directory], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring] |None |9
 
 |<<modification-or-removal-of-an-okta-application-sign-on-policy, Modification or Removal of an Okta Application Sign-On Policy>> |Detects attempts to modify or delete a sign on policy for an Okta application. An adversary may attempt to modify or delete the sign on policy for an Okta application in order to remove or weaken an organization's security controls. |[Tactic: Persistence], [Use Case: Identity and Access Audit], [Data Source: Okta] |8.10.0 |206
 
-|<<mofcomp-activity, Mofcomp Activity>> |Managed Object Format (MOF) files can be compiled locally or remotely through mofcomp.exe. Attackers may leverage MOF files to build their own namespaces and classes into the Windows Management Instrumentation (WMI) repository, or establish persistence using WMI Event Subscription. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |2
+|<<mofcomp-activity, Mofcomp Activity>> |Managed Object Format (MOF) files can be compiled locally or remotely through mofcomp.exe. Attackers may leverage MOF files to build their own namespaces and classes into the Windows Management Instrumentation (WMI) repository, or establish persistence using WMI Event Subscription. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |2
 
 |<<mount-launched-inside-a-privileged-container, Mount Launched Inside a Privileged Container>> |This rule detects the use of the mount utility from inside a privileged container. The mount command is used to make a device or file system accessible to the system, and then to connect its root directory to a specified mount point on the local file system. When launched inside a privileged container--a container deployed with all the capabilities of the host machine-- an attacker can access sensitive host level files which could be used for further privilege escalation and container escapes to the host machine. Any usage of mount inside a running privileged container should be further investigated. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.10.0 |1
 
-|<<mounting-hidden-or-webdav-remote-shares, Mounting Hidden or WebDav Remote Shares>> |Identifies the use of net.exe to mount a WebDav or hidden remote share. This may indicate lateral movement or preparation for data exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<mounting-hidden-or-webdav-remote-shares, Mounting Hidden or WebDav Remote Shares>> |Identifies the use of net.exe to mount a WebDav or hidden remote share. This may indicate lateral movement or preparation for data exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<msbuild-making-network-connections, MsBuild Making Network Connections>> |Identifies MsBuild.exe making outbound network connections. This may indicate adversarial activity as MsBuild is often leveraged by adversaries to execute code and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<msbuild-making-network-connections, MsBuild Making Network Connections>> |Identifies MsBuild.exe making outbound network connections. This may indicate adversarial activity as MsBuild is often leveraged by adversaries to execute code and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<mshta-making-network-connections, Mshta Making Network Connections>> |Identifies Mshta.exe making outbound network connections. This may indicate adversarial activity, as Mshta is often leveraged by adversaries to execute malicious scripts and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<mshta-making-network-connections, Mshta Making Network Connections>> |Identifies Mshta.exe making outbound network connections. This may indicate adversarial activity, as Mshta is often leveraged by adversaries to execute malicious scripts and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<multi-factor-authentication-disabled-for-an-azure-user, Multi-Factor Authentication Disabled for an Azure User>> |Identifies when multi-factor authentication (MFA) is disabled for an Azure user account. An adversary may disable MFA for a user account in order to weaken the authentication requirements for the account. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |8.3.0 |105
+|<<multi-factor-authentication-disabled-for-an-azure-user, Multi-Factor Authentication Disabled for an Azure User>> |Identifies when multi-factor authentication (MFA) is disabled for an Azure user account. An adversary may disable MFA for a user account in order to weaken the authentication requirements for the account. |[Domain: Cloud], [Data Source: Azure], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Persistence] |None |105
 
-|<<multiple-alerts-involving-a-user, Multiple Alerts Involving a User>> |This rule uses alert data to determine when multiple different alerts involving the same user are triggered. Analysts can use this to prioritize triage and response, as these users are more likely to be compromised. |[Use Case: Threat Detection], [Rule Type: Higher-Order Rule] |8.3.0 |3
+|<<multiple-alerts-involving-a-user, Multiple Alerts Involving a User>> |This rule uses alert data to determine when multiple different alerts involving the same user are triggered. Analysts can use this to prioritize triage and response, as these users are more likely to be compromised. |[Use Case: Threat Detection], [Rule Type: Higher-Order Rule] |None |3
 
-|<<multiple-alerts-in-different-att-ck-tactics-on-a-single-host, Multiple Alerts in Different ATT&CK Tactics on a Single Host>> |This rule uses alert data to determine when multiple alerts in different phases of an attack involving the same host are triggered. Analysts can use this to prioritize triage and response, as these hosts are more likely to be compromised. |[Use Case: Threat Detection], [Rule Type: Higher-Order Rule] |8.3.0 |4
+|<<multiple-alerts-in-different-att-ck-tactics-on-a-single-host, Multiple Alerts in Different ATT&CK Tactics on a Single Host>> |This rule uses alert data to determine when multiple alerts in different phases of an attack involving the same host are triggered. Analysts can use this to prioritize triage and response, as these hosts are more likely to be compromised. |[Use Case: Threat Detection], [Rule Type: Higher-Order Rule] |None |4
 
-|<<multiple-logon-failure-followed-by-logon-success, Multiple Logon Failure Followed by Logon Success>> |Identifies multiple logon failures followed by a successful one from the same source address. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide] |8.3.0 |10
+|<<multiple-logon-failure-followed-by-logon-success, Multiple Logon Failure Followed by Logon Success>> |Identifies multiple logon failures followed by a successful one from the same source address. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide] |None |10
 
-|<<multiple-logon-failure-from-the-same-source-address, Multiple Logon Failure from the same Source Address>> |Identifies multiple consecutive logon failures from the same source address and within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide] |8.3.0 |9
+|<<multiple-logon-failure-from-the-same-source-address, Multiple Logon Failure from the same Source Address>> |Identifies multiple consecutive logon failures from the same source address and within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide] |None |9
 
 |<<multiple-okta-client-addresses-for-a-single-user-session, Multiple Okta Client Addresses for a Single User Session>> |Detects when a user has started multiple Okta sessions with the same user account and different session IDs. This may indicate an attacker has compromised a user's Okta account and is using it to access the organization's resources. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Initial Access] |8.10.0 |2
 
@@ -990,77 +996,77 @@ and their rule type is `machine_learning`.
 
 |<<multiple-okta-user-auth-events-with-same-device-token-hash-behind-a-proxy, Multiple Okta User Auth Events with Same Device Token Hash Behind a Proxy>> |Detects when Okta user authentication events are reported for multiple users with the same device token hash behind a proxy. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Credential Access] |8.10.0 |2
 
-|<<multiple-vault-web-credentials-read, Multiple Vault Web Credentials Read>> |Windows Credential Manager allows you to create, view, or delete saved credentials for signing into websites, connected applications, and networks. An adversary may abuse this to list or dump credentials stored in the Credential Manager for saved usernames and passwords. This may also be performed in preparation of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access] |8.3.0 |10
+|<<multiple-vault-web-credentials-read, Multiple Vault Web Credentials Read>> |Windows Credential Manager allows you to create, view, or delete saved credentials for signing into websites, connected applications, and networks. An adversary may abuse this to list or dump credentials stored in the Credential Manager for saved usernames and passwords. This may also be performed in preparation of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access] |None |10
 
-|<<my-first-rule, My First Rule>> |This rule helps you test and practice using alerts with Elastic Security as you get set up. It’s not a sign of threat activity. |[Use Case: Guided Onboarding] |8.7.0 |3
+|<<my-first-rule, My First Rule>> |This rule helps you test and practice using alerts with Elastic Security as you get set up. It’s not a sign of threat activity. |[Use Case: Guided Onboarding] |None |3
 
-|<<ntds-or-sam-database-file-copied, NTDS or SAM Database File Copied>> |Identifies a copy operation of the Active Directory Domain Database (ntds.dit) or Security Account Manager (SAM) files. Those files contain sensitive information including hashed domain and/or local credentials. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<ntds-or-sam-database-file-copied, NTDS or SAM Database File Copied>> |Identifies a copy operation of the Active Directory Domain Database (ntds.dit) or Security Account Manager (SAM) files. Those files contain sensitive information including hashed domain and/or local credentials. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<namespace-manipulation-using-unshare, Namespace Manipulation Using Unshare>> |Identifies suspicious usage of unshare to manipulate system namespaces. Unshare can be utilized to escalate privileges or escape container security boundaries. Threat actors have utilized this binary to allow themselves to escape to the host and access other resources or escalate privileges. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |9
+|<<namespace-manipulation-using-unshare, Namespace Manipulation Using Unshare>> |Identifies suspicious usage of unshare to manipulate system namespaces. Unshare can be utilized to escalate privileges or escape container security boundaries. Threat actors have utilized this binary to allow themselves to escape to the host and access other resources or escalate privileges. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |9
 
-|<<netcat-listener-established-inside-a-container, Netcat Listener Established Inside A Container>> |This rule detects an established netcat listener running inside a container. Netcat is a utility used for reading and writing data across network connections, and it can be used for malicious purposes such as establishing a backdoor for persistence or exfiltrating data. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |8.8.0 |2
+|<<netcat-listener-established-inside-a-container, Netcat Listener Established Inside A Container>> |This rule detects an established netcat listener running inside a container. Netcat is a utility used for reading and writing data across network connections, and it can be used for malicious purposes such as establishing a backdoor for persistence or exfiltrating data. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |None |2
 
-|<<netcat-listener-established-via-rlwrap, Netcat Listener Established via rlwrap>> |Monitors for the execution of a netcat listener via rlwrap. rlwrap is a 'readline wrapper', a small utility that uses the GNU Readline library to allow the editing of keyboard input for any command. This utility can be used in conjunction with netcat to gain a more stable reverse shell. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |3
+|<<netcat-listener-established-via-rlwrap, Netcat Listener Established via rlwrap>> |Monitors for the execution of a netcat listener via rlwrap. rlwrap is a 'readline wrapper', a small utility that uses the GNU Readline library to allow the editing of keyboard input for any command. This utility can be used in conjunction with netcat to gain a more stable reverse shell. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |3
 
-|<<netsh-helper-dll, Netsh Helper DLL>> |Identifies the addition of a Netsh Helper DLL, netsh.exe supports the addition of these DLLs to extend its functionality. Attackers may abuse this mechanism to execute malicious payloads every time the utility is executed, which can be done by administrators or a scheduled task. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |2
+|<<netsh-helper-dll, Netsh Helper DLL>> |Identifies the addition of a Netsh Helper DLL, netsh.exe supports the addition of these DLLs to extend its functionality. Attackers may abuse this mechanism to execute malicious payloads every time the utility is executed, which can be done by administrators or a scheduled task. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |2
 
-|<<network-activity-detected-via-kworker, Network Activity Detected via Kworker>> |This rule monitors for network connections from a kworker process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |8.6.0 |4
+|<<network-activity-detected-via-kworker, Network Activity Detected via Kworker>> |This rule monitors for network connections from a kworker process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |None |5
 
-|<<network-activity-detected-via-cat, Network Activity Detected via cat>> |This rule monitors for the execution of the cat command, followed by a connection attempt by the same process. Cat is capable of transfering data via tcp/udp channels by redirecting its read output to a /dev/tcp or /dev/udp channel. This activity is highly suspicious, and should be investigated. Attackers may leverage this capability to transfer tools or files to another host in the network or exfiltrate data while attempting to evade detection in the process. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |8.3.0 |6
+|<<network-activity-detected-via-cat, Network Activity Detected via cat>> |This rule monitors for the execution of the cat command, followed by a connection attempt by the same process. Cat is capable of transfering data via tcp/udp channels by redirecting its read output to a /dev/tcp or /dev/udp channel. This activity is highly suspicious, and should be investigated. Attackers may leverage this capability to transfer tools or files to another host in the network or exfiltrate data while attempting to evade detection in the process. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |None |6
 
-|<<network-connection-from-binary-with-rwx-memory-region, Network Connection from Binary with RWX Memory Region>> |Monitors for the execution of a unix binary with read, write and execute memory region permissions, followed by a network connection. The mprotect() system call is used to change the access protections on a region of memory that has already been allocated. This syscall allows a process to modify the permissions of pages in its virtual address space, enabling or disabling permissions such as read, write, and execute for those pages. RWX permissions on memory is in many cases overly permissive, and should (especially in conjunction with an outbound network connection) be analyzed thoroughly. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.6.0 |1
+|<<network-connection-from-binary-with-rwx-memory-region, Network Connection from Binary with RWX Memory Region>> |Monitors for the execution of a unix binary with read, write and execute memory region permissions, followed by a network connection. The mprotect() system call is used to change the access protections on a region of memory that has already been allocated. This syscall allows a process to modify the permissions of pages in its virtual address space, enabling or disabling permissions such as read, write, and execute for those pages. RWX permissions on memory is in many cases overly permissive, and should (especially in conjunction with an outbound network connection) be analyzed thoroughly. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |1
 
-|<<network-connection-via-certutil, Network Connection via Certutil>> |Identifies certutil.exe making a network connection. Adversaries could abuse certutil.exe to download a certificate, or malware, from a remote URL. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<network-connection-via-certutil, Network Connection via Certutil>> |Identifies certutil.exe making a network connection. Adversaries could abuse certutil.exe to download a certificate, or malware, from a remote URL. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<network-connection-via-compiled-html-file, Network Connection via Compiled HTML File>> |Compiled HTML files (.chm) are commonly distributed as part of the Microsoft HTML Help system. Adversaries may conceal malicious code in a CHM file and deliver it to a victim for execution. CHM content is loaded by the HTML Help executable program (hh.exe). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<network-connection-via-compiled-html-file, Network Connection via Compiled HTML File>> |Compiled HTML files (.chm) are commonly distributed as part of the Microsoft HTML Help system. Adversaries may conceal malicious code in a CHM file and deliver it to a victim for execution. CHM content is loaded by the HTML Help executable program (hh.exe). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<network-connection-via-msxsl, Network Connection via MsXsl>> |Identifies msxsl.exe making a network connection. This may indicate adversarial activity as msxsl.exe is often leveraged by adversaries to execute malicious scripts and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |106
+|<<network-connection-via-msxsl, Network Connection via MsXsl>> |Identifies msxsl.exe making a network connection. This may indicate adversarial activity as msxsl.exe is often leveraged by adversaries to execute malicious scripts and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |106
 
-|<<network-connection-via-recently-compiled-executable, Network Connection via Recently Compiled Executable>> |This rule monitors a sequence involving a program compilation event followed by its execution and a subsequent network connection event. This behavior can indicate the set up of a reverse tcp connection to a command-and-control server. Attackers may spawn reverse shells to establish persistence onto a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |5
+|<<network-connection-via-recently-compiled-executable, Network Connection via Recently Compiled Executable>> |This rule monitors a sequence involving a program compilation event followed by its execution and a subsequent network connection event. This behavior can indicate the set up of a reverse tcp connection to a command-and-control server. Attackers may spawn reverse shells to establish persistence onto a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |5
 
-|<<network-connection-via-registration-utility, Network Connection via Registration Utility>> |Identifies the native Windows tools regsvr32.exe, regsvr64.exe, RegSvcs.exe, or RegAsm.exe making a network connection. This may be indicative of an attacker bypassing allowlists or running arbitrary scripts via a signed Microsoft binary. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<network-connection-via-registration-utility, Network Connection via Registration Utility>> |Identifies the native Windows tools regsvr32.exe, regsvr64.exe, RegSvcs.exe, or RegAsm.exe making a network connection. This may be indicative of an attacker bypassing allowlists or running arbitrary scripts via a signed Microsoft binary. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<network-connection-via-signed-binary, Network Connection via Signed Binary>> |Binaries signed with trusted digital certificates can execute on Windows systems protected by digital signature validation. Adversaries may use these binaries to 'live off the land' and execute malicious files that could bypass application allowlists and signature validation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<network-connection-via-signed-binary, Network Connection via Signed Binary>> |Binaries signed with trusted digital certificates can execute on Windows systems protected by digital signature validation. Adversaries may use these binaries to 'live off the land' and execute malicious files that could bypass application allowlists and signature validation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<network-logon-provider-registry-modification, Network Logon Provider Registry Modification>> |Identifies the modification of the network logon provider registry. Adversaries may register a rogue network logon provider module for persistence and/or credential access via intercepting the authentication credentials in clear text during user logon. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<network-logon-provider-registry-modification, Network Logon Provider Registry Modification>> |Identifies the modification of the network logon provider registry. Adversaries may register a rogue network logon provider module for persistence and/or credential access via intercepting the authentication credentials in clear text during user logon. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
 |<<network-traffic-capture-via-cap-net-raw, Network Traffic Capture via CAP_NET_RAW>> |Identifies the ability of a process to be able to create RAW and PACKET socket types for the available network namespaces by a non-root user. A malicious process with this capability may exploit routing between hosts, bypass network access controls, and otherwise tamper with host networking if a firewall is not in place to limit the packet types and contents. The CAP_NET_RAW capability allows the process to bind to any address within the available namespaces, which allows network traffic sniffing by a non root user. The rule identifies previously unknown processes executing with CAP_NET_RAW capabilities through the use of the new terms rule type. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |8.11.0 |2
 
-|<<network-traffic-to-rare-destination-country, Network Traffic to Rare Destination Country>> |A machine learning job detected a rare destination country name in the network logs. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from a server in a country which does not normally appear in network traffic or business work-flows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |8.3.0 |103
+|<<network-traffic-to-rare-destination-country, Network Traffic to Rare Destination Country>> |A machine learning job detected a rare destination country name in the network logs. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from a server in a country which does not normally appear in network traffic or business work-flows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |None |103
 
-|<<network-level-authentication-nla-disabled, Network-Level Authentication (NLA) Disabled>> |Identifies the attempt to disable Network-Level Authentication (NLA) via registry modification. Network Level Authentication (NLA) is a feature on Windows that provides an extra layer of security for Remote Desktop (RDP) connections, as it requires users to authenticate before allowing a full RDP session. Attackers can disable NLA to enable persistence methods that require access to the Windows sign-in screen without authenticating, such as Accessibility Features persistence methods, like Sticky Keys. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |3
+|<<network-level-authentication-nla-disabled, Network-Level Authentication (NLA) Disabled>> |Identifies the attempt to disable Network-Level Authentication (NLA) via registry modification. Network Level Authentication (NLA) is a feature on Windows that provides an extra layer of security for Remote Desktop (RDP) connections, as it requires users to authenticate before allowing a full RDP session. Attackers can disable NLA to enable persistence methods that require access to the Windows sign-in screen without authenticating, such as Accessibility Features persistence methods, like Sticky Keys. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |3
 
-|<<new-activesyncalloweddeviceid-added-via-powershell, New ActiveSyncAllowedDeviceID Added via PowerShell>> |Identifies the use of the Exchange PowerShell cmdlet, Set-CASMailbox, to add a new ActiveSync allowed device. Adversaries may target user email to collect sensitive information. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<new-activesyncalloweddeviceid-added-via-powershell, New ActiveSyncAllowedDeviceID Added via PowerShell>> |Identifies the use of the Exchange PowerShell cmdlet, Set-CASMailbox, to add a new ActiveSync allowed device. Adversaries may target user email to collect sensitive information. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<new-github-app-installed, New GitHub App Installed>> |This rule detects when a new GitHub App has been installed in your organization account. GitHub Apps extend GitHub's functionality both within and outside of GitHub. When an app is installed it is granted permissions to read or modify your repository and organization data. Only trusted apps should be installed and any newly installed apps should be investigated to verify their legitimacy. Unauthorized app installation could lower your organization's security posture and leave you exposed for future attacks. |[Domain: Cloud], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Github] |8.3.0 |1
+|<<new-github-app-installed, New GitHub App Installed>> |This rule detects when a new GitHub App has been installed in your organization account. GitHub Apps extend GitHub's functionality both within and outside of GitHub. When an app is installed it is granted permissions to read or modify your repository and organization data. Only trusted apps should be installed and any newly installed apps should be investigated to verify their legitimacy. Unauthorized app installation could lower your organization's security posture and leave you exposed for future attacks. |[Domain: Cloud], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Github] |None |1
 
-|<<new-github-owner-added, New GitHub Owner Added>> |Detects when a new member is added to a GitHub organization as an owner. This role provides admin level privileges. Any new owner roles should be investigated to determine it's validity. Unauthorized owner roles could indicate compromise within your organization and provide unlimited access to data and settings. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Data Source: Github] |8.3.0 |3
+|<<new-github-owner-added, New GitHub Owner Added>> |Detects when a new member is added to a GitHub organization as an owner. This role provides admin level privileges. Any new owner roles should be investigated to determine it's validity. Unauthorized owner roles could indicate compromise within your organization and provide unlimited access to data and settings. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Data Source: Github] |None |3
 
 |<<new-okta-authentication-behavior-detected, New Okta Authentication Behavior Detected>> |Detects events where Okta behavior detection has identified a new authentication behavior. |[Use Case: Identity and Access Audit], [Tactic: Initial Access], [Data Source: Okta] |8.10.0 |1
 
 |<<new-okta-identity-provider-idp-added-by-admin, New Okta Identity Provider (IdP) Added by Admin>> |Detects the creation of a new Identity Provider (IdP) by a Super Administrator or Organization Administrator within Okta. |[Use Case: Identity and Access Audit], [Tactic: Persistence], [Data Source: Okta] |8.10.0 |1
 
-|<<new-systemd-service-created-by-previously-unknown-process, New Systemd Service Created by Previously Unknown Process>> |Systemd service files are configuration files in Linux systems used to define and manage system services. Malicious actors can leverage systemd service files to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |9
+|<<new-systemd-service-created-by-previously-unknown-process, New Systemd Service Created by Previously Unknown Process>> |Systemd service files are configuration files in Linux systems used to define and manage system services. Malicious actors can leverage systemd service files to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |10
 
-|<<new-systemd-timer-created, New Systemd Timer Created>> |Detects the creation of a systemd timer within any of the default systemd timer directories. Systemd timers can be used by an attacker to gain persistence, by scheduling the execution of a command or script. Similarly to cron/at, systemd timers can be set up to execute on boot time, or on a specific point in time, which allows attackers to regain access in case the connection to the infected asset was lost. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.6.0 |9
+|<<new-systemd-timer-created, New Systemd Timer Created>> |Detects the creation of a systemd timer within any of the default systemd timer directories. Systemd timers can be used by an attacker to gain persistence, by scheduling the execution of a command or script. Similarly to cron/at, systemd timers can be set up to execute on boot time, or on a specific point in time, which allows attackers to regain access in case the connection to the infected asset was lost. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |10
 
-|<<new-user-added-to-github-organization, New User Added To GitHub Organization>> |A new user was added to a GitHub organization. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Github] |8.3.0 |1
+|<<new-user-added-to-github-organization, New User Added To GitHub Organization>> |A new user was added to a GitHub organization. |[Domain: Cloud], [Use Case: Threat Detection], [Use Case: UEBA], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Github] |None |1
 
-|<<new-or-modified-federation-domain, New or Modified Federation Domain>> |Identifies a new or modified federation domain, which can be used to create a trust between O365 and an external identity provider. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |8.8.0 |206
+|<<new-or-modified-federation-domain, New or Modified Federation Domain>> |Identifies a new or modified federation domain, which can be used to create a trust between O365 and an external identity provider. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Privilege Escalation] |None |206
 
-|<<nping-process-activity, Nping Process Activity>> |Nping ran on a Linux host. Nping is part of the Nmap tool suite and has the ability to construct raw packets for a wide variety of security testing applications, including denial of service testing. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |108
+|<<nping-process-activity, Nping Process Activity>> |Nping ran on a Linux host. Nping is part of the Nmap tool suite and has the ability to construct raw packets for a wide variety of security testing applications, including denial of service testing. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |108
 
-|<<nullsessionpipe-registry-modification, NullSessionPipe Registry Modification>> |Identifies NullSessionPipe registry modifications that specify which pipes can be accessed anonymously. This could be indicative of adversary lateral movement preparation by making the added pipe available to everyone. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<nullsessionpipe-registry-modification, NullSessionPipe Registry Modification>> |Identifies NullSessionPipe registry modifications that specify which pipes can be accessed anonymously. This could be indicative of adversary lateral movement preparation by making the added pipe available to everyone. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<o365-email-reported-by-user-as-malware-or-phish, O365 Email Reported by User as Malware or Phish>> |Detects the occurrence of emails reported as Phishing or Malware by Users. Security Awareness training is essential to stay ahead of scammers and threat actors, as security products can be bypassed, and the user can still receive a malicious message. Educating users to report suspicious messages can help identify gaps in security controls and prevent malware infections and Business Email Compromise attacks. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Initial Access] |8.8.0 |206
+|<<o365-email-reported-by-user-as-malware-or-phish, O365 Email Reported by User as Malware or Phish>> |Detects the occurrence of emails reported as Phishing or Malware by Users. Security Awareness training is essential to stay ahead of scammers and threat actors, as security products can be bypassed, and the user can still receive a malicious message. Educating users to report suspicious messages can help identify gaps in security controls and prevent malware infections and Business Email Compromise attacks. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Initial Access] |None |206
 
-|<<o365-excessive-single-sign-on-logon-errors, O365 Excessive Single Sign-On Logon Errors>> |Identifies accounts with a high number of single sign-on (SSO) logon errors. Excessive logon errors may indicate an attempt to brute force a password or SSO token. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |8.8.0 |207
+|<<o365-excessive-single-sign-on-logon-errors, O365 Excessive Single Sign-On Logon Errors>> |Identifies accounts with a high number of single sign-on (SSO) logon errors. Excessive logon errors may indicate an attempt to brute force a password or SSO token. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |None |207
 
-|<<o365-exchange-suspicious-mailbox-right-delegation, O365 Exchange Suspicious Mailbox Right Delegation>> |Identifies the assignment of rights to access content from another mailbox. An adversary may use the compromised account to send messages to other accounts in the network of the target organization while creating inbox rules, so messages can evade spam/phishing detection mechanisms. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |8.8.0 |206
+|<<o365-exchange-suspicious-mailbox-right-delegation, O365 Exchange Suspicious Mailbox Right Delegation>> |Identifies the assignment of rights to access content from another mailbox. An adversary may use the compromised account to send messages to other accounts in the network of the target organization while creating inbox rules, so messages can evade spam/phishing detection mechanisms. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Persistence] |None |206
 
-|<<o365-mailbox-audit-logging-bypass, O365 Mailbox Audit Logging Bypass>> |Detects the occurrence of mailbox audit bypass associations. The mailbox audit is responsible for logging specified mailbox events (like accessing a folder or a message or permanently deleting a message). However, actions taken by some authorized accounts, such as accounts used by third-party tools or accounts used for lawful monitoring, can create a large number of mailbox audit log entries and may not be of interest to your organization. Because of this, administrators can create bypass associations, allowing certain accounts to perform their tasks without being logged. Attackers can abuse this allowlist mechanism to conceal actions taken, as the mailbox audit will log no activity done by the account. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Initial Access], [Tactic: Defense Evasion] |8.8.0 |206
+|<<o365-mailbox-audit-logging-bypass, O365 Mailbox Audit Logging Bypass>> |Detects the occurrence of mailbox audit bypass associations. The mailbox audit is responsible for logging specified mailbox events (like accessing a folder or a message or permanently deleting a message). However, actions taken by some authorized accounts, such as accounts used by third-party tools or accounts used for lawful monitoring, can create a large number of mailbox audit log entries and may not be of interest to your organization. Because of this, administrators can create bypass associations, allowing certain accounts to perform their tasks without being logged. Attackers can abuse this allowlist mechanism to conceal actions taken, as the mailbox audit will log no activity done by the account. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Initial Access], [Tactic: Defense Evasion] |None |206
 
-|<<office-test-registry-persistence, Office Test Registry Persistence>> |Identifies the modification of the Microsoft Office "Office Test" Registry key, a registry location that can be used to specify a DLL which will be executed every time an MS Office application is started. Attackers can abuse this to gain persistence on a compromised host. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |3
+|<<office-test-registry-persistence, Office Test Registry Persistence>> |Identifies the modification of the Microsoft Office "Office Test" Registry key, a registry location that can be used to specify a DLL which will be executed every time an MS Office application is started. Attackers can abuse this to gain persistence on a compromised host. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |3
 
 |<<okta-brute-force-or-password-spraying-attack, Okta Brute Force or Password Spraying Attack>> |Identifies a high number of failed Okta user authentication attempts from a single IP address, which could be indicative of a brute force or password spraying attack. An adversary may attempt a brute force or password spraying attack to obtain unauthorized access to user accounts. |[Use Case: Identity and Access Audit], [Tactic: Credential Access], [Data Source: Okta] |8.10.0 |208
 
@@ -1074,409 +1080,409 @@ and their rule type is `machine_learning`.
 
 |<<okta-user-sessions-started-from-different-geolocations, Okta User Sessions Started from Different Geolocations>> |Detects when a specific Okta actor has multiple sessions started from different geolocations. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Initial Access] |8.10.0 |1
 
-|<<onedrive-malware-file-upload, OneDrive Malware File Upload>> |Identifies the occurence of files uploaded to OneDrive being detected as Malware by the file scanning engine. Attackers can use File Sharing and Organization Repositories to spread laterally within the company and amplify their access. Users can inadvertently share these files without knowing their maliciousness, giving adversaries opportunity to gain initial access to other endpoints in the environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Lateral Movement] |8.8.0 |206
+|<<onedrive-malware-file-upload, OneDrive Malware File Upload>> |Identifies the occurence of files uploaded to OneDrive being detected as Malware by the file scanning engine. Attackers can use File Sharing and Organization Repositories to spread laterally within the company and amplify their access. Users can inadvertently share these files without knowing their maliciousness, giving adversaries opportunity to gain initial access to other endpoints in the environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Lateral Movement] |None |206
 
-|<<outbound-scheduled-task-activity-via-powershell, Outbound Scheduled Task Activity via PowerShell>> |Identifies the PowerShell process loading the Task Scheduler COM DLL followed by an outbound RPC network connection within a short time period. This may indicate lateral movement or remote discovery via scheduled tasks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<outbound-scheduled-task-activity-via-powershell, Outbound Scheduled Task Activity via PowerShell>> |Identifies the PowerShell process loading the Task Scheduler COM DLL followed by an outbound RPC network connection within a short time period. This may indicate lateral movement or remote discovery via scheduled tasks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<parent-process-pid-spoofing, Parent Process PID Spoofing>> |Identifies parent process spoofing used to thwart detection. Adversaries may spoof the parent process identifier (PPID) of a new process to evade process-monitoring defenses or to elevate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |106
+|<<parent-process-pid-spoofing, Parent Process PID Spoofing>> |Identifies parent process spoofing used to thwart detection. Adversaries may spoof the parent process identifier (PPID) of a new process to evade process-monitoring defenses or to elevate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |106
 
-|<<peripheral-device-discovery, Peripheral Device Discovery>> |Identifies use of the Windows file system utility (fsutil.exe) to gather information about attached peripheral devices and components connected to a computer system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<peripheral-device-discovery, Peripheral Device Discovery>> |Identifies use of the Windows file system utility (fsutil.exe) to gather information about attached peripheral devices and components connected to a computer system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<permission-theft-detected-elastic-endgame, Permission Theft - Detected - Elastic Endgame>> |Elastic Endgame detected Permission Theft. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<permission-theft-detected-elastic-endgame, Permission Theft - Detected - Elastic Endgame>> |Elastic Endgame detected Permission Theft. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |103
 
-|<<permission-theft-prevented-elastic-endgame, Permission Theft - Prevented - Elastic Endgame>> |Elastic Endgame prevented Permission Theft. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<permission-theft-prevented-elastic-endgame, Permission Theft - Prevented - Elastic Endgame>> |Elastic Endgame prevented Permission Theft. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |103
 
-|<<persistence-via-bits-job-notify-cmdline, Persistence via BITS Job Notify Cmdline>> |An adversary can use the Background Intelligent Transfer Service (BITS) SetNotifyCmdLine method to execute a program that runs after a job finishes transferring data or after a job enters a specified state in order to persist on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<persistence-via-bits-job-notify-cmdline, Persistence via BITS Job Notify Cmdline>> |An adversary can use the Background Intelligent Transfer Service (BITS) SetNotifyCmdLine method to execute a program that runs after a job finishes transferring data or after a job enters a specified state in order to persist on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |209
 
-|<<persistence-via-directoryservice-plugin-modification, Persistence via DirectoryService Plugin Modification>> |Identifies the creation or modification of a DirectoryService PlugIns (dsplug) file. The DirectoryService daemon launches on each system boot and automatically reloads after crash. It scans and executes bundles that are located in the DirectoryServices PlugIns folder and can be abused by adversaries to maintain persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<persistence-via-directoryservice-plugin-modification, Persistence via DirectoryService Plugin Modification>> |Identifies the creation or modification of a DirectoryService PlugIns (dsplug) file. The DirectoryService daemon launches on each system boot and automatically reloads after crash. It scans and executes bundles that are located in the DirectoryServices PlugIns folder and can be abused by adversaries to maintain persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<persistence-via-docker-shortcut-modification, Persistence via Docker Shortcut Modification>> |An adversary can establish persistence by modifying an existing macOS dock property list in order to execute a malicious application instead of the intended one when invoked. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |107
+|<<persistence-via-docker-shortcut-modification, Persistence via Docker Shortcut Modification>> |An adversary can establish persistence by modifying an existing macOS dock property list in order to execute a malicious application instead of the intended one when invoked. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |107
 
-|<<persistence-via-folder-action-script, Persistence via Folder Action Script>> |Detects modification of a Folder Action script. A Folder Action script is executed when the folder to which it is attached has items added or removed, or when its window is opened, closed, moved, or resized. Adversaries may abuse this feature to establish persistence by utilizing a malicious script. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |107
+|<<persistence-via-folder-action-script, Persistence via Folder Action Script>> |Detects modification of a Folder Action script. A Folder Action script is executed when the folder to which it is attached has items added or removed, or when its window is opened, closed, moved, or resized. Adversaries may abuse this feature to establish persistence by utilizing a malicious script. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Persistence], [Data Source: Elastic Defend] |None |107
 
-|<<persistence-via-hidden-run-key-detected, Persistence via Hidden Run Key Detected>> |Identifies a persistence mechanism that utilizes the NtSetValueKey native API to create a hidden (null terminated) registry key. An adversary may use this method to hide from system utilities such as the Registry Editor (regedit). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<persistence-via-hidden-run-key-detected, Persistence via Hidden Run Key Detected>> |Identifies a persistence mechanism that utilizes the NtSetValueKey native API to create a hidden (null terminated) registry key. An adversary may use this method to hide from system utilities such as the Registry Editor (regedit). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<persistence-via-kde-autostart-script-or-desktop-file-modification, Persistence via KDE AutoStart Script or Desktop File Modification>> |Identifies the creation or modification of a K Desktop Environment (KDE) AutoStart script or desktop file that will execute upon each user logon. Adversaries may abuse this method for persistence. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<persistence-via-kde-autostart-script-or-desktop-file-modification, Persistence via KDE AutoStart Script or Desktop File Modification>> |Identifies the creation or modification of a K Desktop Environment (KDE) AutoStart script or desktop file that will execute upon each user logon. Adversaries may abuse this method for persistence. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<persistence-via-login-or-logout-hook, Persistence via Login or Logout Hook>> |Identifies use of the Defaults command to install a login or logoff hook in MacOS. An adversary may abuse this capability to establish persistence in an environment by inserting code to be executed at login or logout. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |107
+|<<persistence-via-login-or-logout-hook, Persistence via Login or Logout Hook>> |Identifies use of the Defaults command to install a login or logoff hook in MacOS. An adversary may abuse this capability to establish persistence in an environment by inserting code to be executed at login or logout. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |107
 
-|<<persistence-via-microsoft-office-addins, Persistence via Microsoft Office AddIns>> |Detects attempts to establish persistence on an endpoint by abusing Microsoft Office add-ins. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<persistence-via-microsoft-office-addins, Persistence via Microsoft Office AddIns>> |Detects attempts to establish persistence on an endpoint by abusing Microsoft Office add-ins. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<persistence-via-microsoft-outlook-vba, Persistence via Microsoft Outlook VBA>> |Detects attempts to establish persistence on an endpoint by installing a rogue Microsoft Outlook VBA Template. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<persistence-via-microsoft-outlook-vba, Persistence via Microsoft Outlook VBA>> |Detects attempts to establish persistence on an endpoint by installing a rogue Microsoft Outlook VBA Template. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<persistence-via-powershell-profile, Persistence via PowerShell profile>> |Identifies the creation or modification of a PowerShell profile. PowerShell profile is a script that is executed when PowerShell starts to customize the user environment, which can be abused by attackers to persist in a environment where PowerShell is common. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |9
+|<<persistence-via-powershell-profile, Persistence via PowerShell profile>> |Identifies the creation or modification of a PowerShell profile. PowerShell profile is a script that is executed when PowerShell starts to customize the user environment, which can be abused by attackers to persist in a environment where PowerShell is common. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |9
 
-|<<persistence-via-scheduled-job-creation, Persistence via Scheduled Job Creation>> |A job can be used to schedule programs or scripts to be executed at a specified date and time. Adversaries may abuse task scheduling functionality to facilitate initial or recurring execution of malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<persistence-via-scheduled-job-creation, Persistence via Scheduled Job Creation>> |A job can be used to schedule programs or scripts to be executed at a specified date and time. Adversaries may abuse task scheduling functionality to facilitate initial or recurring execution of malicious code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |210
 
-|<<persistence-via-telemetrycontroller-scheduled-task-hijack, Persistence via TelemetryController Scheduled Task Hijack>> |Detects the successful hijack of Microsoft Compatibility Appraiser scheduled task to establish persistence with an integrity level of system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<persistence-via-telemetrycontroller-scheduled-task-hijack, Persistence via TelemetryController Scheduled Task Hijack>> |Detects the successful hijack of Microsoft Compatibility Appraiser scheduled task to establish persistence with an integrity level of system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<persistence-via-update-orchestrator-service-hijack, Persistence via Update Orchestrator Service Hijack>> |Identifies potential hijacking of the Microsoft Update Orchestrator Service to establish persistence with an integrity level of SYSTEM. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<persistence-via-update-orchestrator-service-hijack, Persistence via Update Orchestrator Service Hijack>> |Identifies potential hijacking of the Microsoft Update Orchestrator Service to establish persistence with an integrity level of SYSTEM. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<persistence-via-wmi-event-subscription, Persistence via WMI Event Subscription>> |An adversary can use Windows Management Instrumentation (WMI) to install event filters, providers, consumers, and bindings that execute code when a defined event occurs. Adversaries may use the capabilities of WMI to subscribe to an event and execute arbitrary code when that event occurs, providing persistence on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<persistence-via-wmi-event-subscription, Persistence via WMI Event Subscription>> |An adversary can use Windows Management Instrumentation (WMI) to install event filters, providers, consumers, and bindings that execute code when a defined event occurs. Adversaries may use the capabilities of WMI to subscribe to an event and execute arbitrary code when that event occurs, providing persistence on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<persistence-via-wmi-standard-registry-provider, Persistence via WMI Standard Registry Provider>> |Identifies use of the Windows Management Instrumentation StdRegProv (registry provider) to modify commonly abused registry locations for persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |108
+|<<persistence-via-wmi-standard-registry-provider, Persistence via WMI Standard Registry Provider>> |Identifies use of the Windows Management Instrumentation StdRegProv (registry provider) to modify commonly abused registry locations for persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |108
 
-|<<persistent-scripts-in-the-startup-directory, Persistent Scripts in the Startup Directory>> |Identifies script engines creating files in the Startup folder, or the creation of script files in the Startup folder. Adversaries may abuse this technique to maintain persistence in an environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<persistent-scripts-in-the-startup-directory, Persistent Scripts in the Startup Directory>> |Identifies script engines creating files in the Startup folder, or the creation of script files in the Startup folder. Adversaries may abuse this technique to maintain persistence in an environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<port-forwarding-rule-addition, Port Forwarding Rule Addition>> |Identifies the creation of a new port forwarding rule. An adversary may abuse this technique to bypass network segmentation restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<port-forwarding-rule-addition, Port Forwarding Rule Addition>> |Identifies the creation of a new port forwarding rule. An adversary may abuse this technique to bypass network segmentation restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |212
 
-|<<possible-consent-grant-attack-via-azure-registered-application, Possible Consent Grant Attack via Azure-Registered Application>> |Detects when a user grants permissions to an Azure-registered application or when an administrator grants tenant-wide permissions to an application. An adversary may create an Azure-registered application that requests access to data such as contact information, email, or documents. |[Domain: Cloud], [Data Source: Azure], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |8.8.0 |212
+|<<possible-consent-grant-attack-via-azure-registered-application, Possible Consent Grant Attack via Azure-Registered Application>> |Detects when a user grants permissions to an Azure-registered application or when an administrator grants tenant-wide permissions to an application. An adversary may create an Azure-registered application that requests access to data such as contact information, email, or documents. |[Domain: Cloud], [Data Source: Azure], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Resources: Investigation Guide], [Tactic: Initial Access] |None |212
 
-|<<possible-fin7-dga-command-and-control-behavior, Possible FIN7 DGA Command and Control Behavior>> |This rule detects a known command and control pattern in network events. The FIN7 threat group is known to use this command and control technique, while maintaining persistence in their target's network. |[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |8.3.0 |105
+|<<possible-fin7-dga-command-and-control-behavior, Possible FIN7 DGA Command and Control Behavior>> |This rule detects a known command and control pattern in network events. The FIN7 threat group is known to use this command and control technique, while maintaining persistence in their target's network. |[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |None |105
 
 |<<possible-okta-dos-attack, Possible Okta DoS Attack>> |Detects possible Denial of Service (DoS) attacks against an Okta organization. An adversary may attempt to disrupt an organization's business operations by performing a DoS attack against its Okta service. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Impact] |8.10.0 |205
 
-|<<potential-adidns-poisoning-via-wildcard-record-creation, Potential ADIDNS Poisoning via Wildcard Record Creation>> |Active Directory Integrated DNS (ADIDNS) is one of the core components of AD DS, leveraging AD's access control and replication to maintain domain consistency. It stores DNS zones as AD objects, a feature that, while robust, introduces some security issues, such as wildcard records, mainly because of the default permission (Any authenticated users) to create DNS-named records. Attackers can create wildcard records to redirect traffic that doesn't explicitly match records contained in the zone, becoming the Man-in-the-Middle and being able to abuse DNS similarly to LLMNR/NBNS spoofing. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Use Case: Active Directory Monitoring] |8.3.0 |1
+|<<potential-adidns-poisoning-via-wildcard-record-creation, Potential ADIDNS Poisoning via Wildcard Record Creation>> |Active Directory Integrated DNS (ADIDNS) is one of the core components of AD DS, leveraging AD's access control and replication to maintain domain consistency. It stores DNS zones as AD objects, a feature that, while robust, introduces some security issues, such as wildcard records, mainly because of the default permission (Any authenticated users) to create DNS-named records. Attackers can create wildcard records to redirect traffic that doesn't explicitly match records contained in the zone, becoming the Man-in-the-Middle and being able to abuse DNS similarly to LLMNR/NBNS spoofing. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Use Case: Active Directory Monitoring] |None |1
 
 |<<potential-admin-group-account-addition, Potential Admin Group Account Addition>> |Identifies attempts to add an account to the admin group via the command line. This could be an indication of privilege escalation activity. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.11.0 |206
 
-|<<potential-antimalware-scan-interface-bypass-via-powershell, Potential Antimalware Scan Interface Bypass via PowerShell>> |Identifies the execution of PowerShell script with keywords related to different Antimalware Scan Interface (AMSI) bypasses. An adversary may attempt first to disable AMSI before executing further malicious powershell scripts to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |8.3.0 |8
+|<<potential-antimalware-scan-interface-bypass-via-powershell, Potential Antimalware Scan Interface Bypass via PowerShell>> |Identifies the execution of PowerShell script with keywords related to different Antimalware Scan Interface (AMSI) bypasses. An adversary may attempt first to disable AMSI before executing further malicious powershell scripts to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |None |8
 
-|<<potential-application-shimming-via-sdbinst, Potential Application Shimming via Sdbinst>> |The Application Shim was created to allow for backward compatibility of software as the operating system codebase changes over time. This Windows functionality has been abused by attackers to stealthily gain persistence and arbitrary code execution in legitimate Windows processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<potential-application-shimming-via-sdbinst, Potential Application Shimming via Sdbinst>> |The Application Shim was created to allow for backward compatibility of software as the operating system codebase changes over time. This Windows functionality has been abused by attackers to stealthily gain persistence and arbitrary code execution in legitimate Windows processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<potential-buffer-overflow-attack-detected, Potential Buffer Overflow Attack Detected>> |Detects potential buffer overflow attacks by querying the "Segfault Detected" pre-built rule signal index, through a threshold rule, with a minimum number of 100 segfault alerts in a short timespan. A large amount of segfaults in a short time interval could indicate application exploitation attempts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Initial Access], [Use Case: Vulnerability], [Rule Type: Higher-Order Rule] |8.3.0 |2
+|<<potential-buffer-overflow-attack-detected, Potential Buffer Overflow Attack Detected>> |Detects potential buffer overflow attacks by querying the "Segfault Detected" pre-built rule signal index, through a threshold rule, with a minimum number of 100 segfault alerts in a short timespan. A large amount of segfaults in a short time interval could indicate application exploitation attempts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Initial Access], [Use Case: Vulnerability], [Rule Type: Higher-Order Rule] |None |3
 
-|<<potential-chroot-container-escape-via-mount, Potential Chroot Container Escape via Mount>> |Monitors for the execution of a file system mount followed by a chroot execution. Given enough permissions, a user within a container is capable of mounting the root file system of the host, and leveraging chroot to escape its containarized environment. This behavior pattern is very uncommon and should be investigated. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Domain: Container], [Data Source: Elastic Defend] |8.3.0 |2
+|<<potential-chroot-container-escape-via-mount, Potential Chroot Container Escape via Mount>> |Monitors for the execution of a file system mount followed by a chroot execution. Given enough permissions, a user within a container is capable of mounting the root file system of the host, and leveraging chroot to escape its containarized environment. This behavior pattern is very uncommon and should be investigated. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Domain: Container], [Data Source: Elastic Defend] |None |2
 
-|<<potential-code-execution-via-postgresql, Potential Code Execution via Postgresql>> |This rule monitors for suspicious activities that may indicate an attacker attempting to execute arbitrary code within a PostgreSQL environment. Attackers can execute code via PostgreSQL as a result of gaining unauthorized access to a public facing PostgreSQL database or exploiting vulnerabilities, such as remote command execution and SQL injection attacks, which can result in unauthorized access and malicious actions, and facilitate post-exploitation activities for unauthorized access and malicious actions. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |6
+|<<potential-code-execution-via-postgresql, Potential Code Execution via Postgresql>> |This rule monitors for suspicious activities that may indicate an attacker attempting to execute arbitrary code within a PostgreSQL environment. Attackers can execute code via PostgreSQL as a result of gaining unauthorized access to a public facing PostgreSQL database or exploiting vulnerabilities, such as remote command execution and SQL injection attacks, which can result in unauthorized access and malicious actions, and facilitate post-exploitation activities for unauthorized access and malicious actions. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |6
 
-|<<potential-command-and-control-via-internet-explorer, Potential Command and Control via Internet Explorer>> |Identifies instances of Internet Explorer (iexplore.exe) being started via the Component Object Model (COM) making unusual network connections. Adversaries could abuse Internet Explorer via COM to avoid suspicious processes making network connections and bypass host-based firewall restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |8.3.0 |106
+|<<potential-command-and-control-via-internet-explorer, Potential Command and Control via Internet Explorer>> |Identifies instances of Internet Explorer (iexplore.exe) being started via the Component Object Model (COM) making unusual network connections. Adversaries could abuse Internet Explorer via COM to avoid suspicious processes making network connections and bypass host-based firewall restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |None |106
 
-|<<potential-container-escape-via-modified-notify-on-release-file, Potential Container Escape via Modified notify_on_release File>> |This rule detects modification of the cgroup notify_on_release file from inside a container. When the notify_on_release flag is enabled (1) in a cgroup, then whenever the last task in the cgroup exits or attaches to another cgroup, the command specified in the release_agent file is run and invoked from the host. A privileged container with SYS_ADMIN capabilities, enables a threat actor to mount a cgroup directory and modify the notify_on_release flag in order to take advantage of this feature, which could be used for further privilege escalation and container escapes to the host machine. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.8.0 |1
+|<<potential-container-escape-via-modified-notify-on-release-file, Potential Container Escape via Modified notify_on_release File>> |This rule detects modification of the cgroup notify_on_release file from inside a container. When the notify_on_release flag is enabled (1) in a cgroup, then whenever the last task in the cgroup exits or attaches to another cgroup, the command specified in the release_agent file is run and invoked from the host. A privileged container with SYS_ADMIN capabilities, enables a threat actor to mount a cgroup directory and modify the notify_on_release flag in order to take advantage of this feature, which could be used for further privilege escalation and container escapes to the host machine. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |1
 
-|<<potential-container-escape-via-modified-release-agent-file, Potential Container Escape via Modified release_agent File>> |This rule detects modification of the CGroup release_agent file from inside a privileged container. The release_agent is a script that is executed at the termination of any process on that CGroup and is invoked from the host. A privileged container with SYS_ADMIN capabilities, enables a threat actor to mount a CGroup directory and modify the release_agent which could be used for further privilege escalation and container escapes to the host machine. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.8.0 |1
+|<<potential-container-escape-via-modified-release-agent-file, Potential Container Escape via Modified release_agent File>> |This rule detects modification of the CGroup release_agent file from inside a privileged container. The release_agent is a script that is executed at the termination of any process on that CGroup and is invoked from the host. A privileged container with SYS_ADMIN capabilities, enables a threat actor to mount a CGroup directory and modify the release_agent which could be used for further privilege escalation and container escapes to the host machine. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |1
 
-|<<potential-cookies-theft-via-browser-debugging, Potential Cookies Theft via Browser Debugging>> |Identifies the execution of a Chromium based browser with the debugging process argument, which may indicate an attempt to steal authentication cookies. An adversary may steal web application or service session cookies and use them to gain access web applications or Internet services as an authenticated user without needing credentials. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.3.0 |105
+|<<potential-cookies-theft-via-browser-debugging, Potential Cookies Theft via Browser Debugging>> |Identifies the execution of a Chromium based browser with the debugging process argument, which may indicate an attempt to steal authentication cookies. An adversary may steal web application or service session cookies and use them to gain access web applications or Internet services as an authenticated user without needing credentials. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |105
 
-|<<potential-credential-access-via-dcsync, Potential Credential Access via DCSync>> |This rule identifies when a User Account starts the Active Directory Replication Process. Attackers can use the DCSync technique to get credential information of individual accounts or the entire domain, thus compromising the entire domain. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Privilege Escalation], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |8.3.0 |113
+|<<potential-credential-access-via-dcsync, Potential Credential Access via DCSync>> |This rule identifies when a User Account starts the Active Directory Replication Process. Attackers can use the DCSync technique to get credential information of individual accounts or the entire domain, thus compromising the entire domain. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Privilege Escalation], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |None |113
 
-|<<potential-credential-access-via-duplicatehandle-in-lsass, Potential Credential Access via DuplicateHandle in LSASS>> |Identifies suspicious access to an LSASS handle via DuplicateHandle from an unknown call trace module. This may indicate an attempt to bypass the NtOpenProcess API to evade detection and dump LSASS memory for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |8.8.0 |208
+|<<potential-credential-access-via-duplicatehandle-in-lsass, Potential Credential Access via DuplicateHandle in LSASS>> |Identifies suspicious access to an LSASS handle via DuplicateHandle from an unknown call trace module. This may indicate an attempt to bypass the NtOpenProcess API to evade detection and dump LSASS memory for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |None |208
 
-|<<potential-credential-access-via-lsass-memory-dump, Potential Credential Access via LSASS Memory Dump>> |Identifies suspicious access to LSASS handle from a call trace pointing to DBGHelp.dll or DBGCore.dll, which both export the MiniDumpWriteDump method that can be used to dump LSASS memory content in preparation for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic:Execution], [Data Source: Sysmon] |8.8.0 |209
+|<<potential-credential-access-via-lsass-memory-dump, Potential Credential Access via LSASS Memory Dump>> |Identifies suspicious access to LSASS handle from a call trace pointing to DBGHelp.dll or DBGCore.dll, which both export the MiniDumpWriteDump method that can be used to dump LSASS memory content in preparation for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic:Execution], [Data Source: Sysmon] |None |209
 
-|<<potential-credential-access-via-memory-dump-file-creation, Potential Credential Access via Memory Dump File Creation>> |Identifies the creation or modification of a medium size memory dump file which can indicate an attempt to access credentials from a process memory. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |3
+|<<potential-credential-access-via-memory-dump-file-creation, Potential Credential Access via Memory Dump File Creation>> |Identifies the creation or modification of a medium size memory dump file which can indicate an attempt to access credentials from a process memory. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Rule Type: BBR] |None |3
 
-|<<potential-credential-access-via-renamed-com-services-dll, Potential Credential Access via Renamed COM+ Services DLL>> |Identifies suspicious renamed COMSVCS.DLL Image Load, which exports the MiniDump function that can be used to dump a process memory. This may indicate an attempt to dump LSASS memory while bypassing command-line based detection in preparation for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Sysmon] |8.3.0 |108
+|<<potential-credential-access-via-renamed-com-services-dll, Potential Credential Access via Renamed COM+ Services DLL>> |Identifies suspicious renamed COMSVCS.DLL Image Load, which exports the MiniDump function that can be used to dump a process memory. This may indicate an attempt to dump LSASS memory while bypassing command-line based detection in preparation for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Sysmon] |None |108
 
-|<<potential-credential-access-via-trusted-developer-utility, Potential Credential Access via Trusted Developer Utility>> |An instance of MSBuild, the Microsoft Build Engine, loaded DLLs (dynamically linked libraries) responsible for Windows credential management. This technique is sometimes used for credential dumping. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<potential-credential-access-via-trusted-developer-utility, Potential Credential Access via Trusted Developer Utility>> |An instance of MSBuild, the Microsoft Build Engine, loaded DLLs (dynamically linked libraries) responsible for Windows credential management. This technique is sometimes used for credential dumping. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<potential-credential-access-via-windows-utilities, Potential Credential Access via Windows Utilities>> |Identifies the execution of known Windows utilities often abused to dump LSASS memory or the Active Directory database (NTDS.dit) in preparation for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<potential-credential-access-via-windows-utilities, Potential Credential Access via Windows Utilities>> |Identifies the execution of known Windows utilities often abused to dump LSASS memory or the Active Directory database (NTDS.dit) in preparation for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<potential-cross-site-scripting-xss, Potential Cross Site Scripting (XSS)>> |Cross-Site Scripting (XSS) is a type of attack in which malicious scripts are injected into trusted websites. In XSS attacks, an attacker uses a benign web application to send malicious code, generally in the form of a browser-side script. This detection rule identifies the potential malicious executions of such browser-side scripts. |[Data Source: APM], [Use Case: Threat Detection], [Tactic: Initial Access] |8.3.0 |1
+|<<potential-cross-site-scripting-xss, Potential Cross Site Scripting (XSS)>> |Cross-Site Scripting (XSS) is a type of attack in which malicious scripts are injected into trusted websites. In XSS attacks, an attacker uses a benign web application to send malicious code, generally in the form of a browser-side script. This detection rule identifies the potential malicious executions of such browser-side scripts. |[Data Source: APM], [Use Case: Threat Detection], [Tactic: Initial Access] |None |1
 
-|<<potential-dga-activity, Potential DGA Activity>> |A population analysis machine learning job detected potential DGA (domain generation algorithm) activity. Such activity is often used by malware command and control (C2) channels. This machine learning job looks for a source IP address making DNS requests that have an aggregate high probability of being DGA activity. |[Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |8.9.0 |3
+|<<potential-dga-activity, Potential DGA Activity>> |A population analysis machine learning job detected potential DGA (domain generation algorithm) activity. Such activity is often used by malware command and control (C2) channels. This machine learning job looks for a source IP address making DNS requests that have an aggregate high probability of being DGA activity. |[Use Case: Domain Generation Algorithm Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |None |4
 
-|<<potential-dll-side-loading-via-microsoft-antimalware-service-executable, Potential DLL Side-Loading via Microsoft Antimalware Service Executable>> |Identifies a Windows trusted program that is known to be vulnerable to DLL Search Order Hijacking starting after being renamed or from a non-standard path. This is uncommon behavior and may indicate an attempt to evade defenses via side-loading a malicious DLL within the memory space of one of those processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<potential-dll-side-loading-via-microsoft-antimalware-service-executable, Potential DLL Side-Loading via Microsoft Antimalware Service Executable>> |Identifies a Windows trusted program that is known to be vulnerable to DLL Search Order Hijacking starting after being renamed or from a non-standard path. This is uncommon behavior and may indicate an attempt to evade defenses via side-loading a malicious DLL within the memory space of one of those processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<potential-dll-side-loading-via-trusted-microsoft-programs, Potential DLL Side-Loading via Trusted Microsoft Programs>> |Identifies an instance of a Windows trusted program that is known to be vulnerable to DLL Search Order Hijacking starting after being renamed or from a non-standard path. This is uncommon behavior and may indicate an attempt to evade defenses via side loading a malicious DLL within the memory space of one of those processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<potential-dll-side-loading-via-trusted-microsoft-programs, Potential DLL Side-Loading via Trusted Microsoft Programs>> |Identifies an instance of a Windows trusted program that is known to be vulnerable to DLL Search Order Hijacking starting after being renamed or from a non-standard path. This is uncommon behavior and may indicate an attempt to evade defenses via side loading a malicious DLL within the memory space of one of those processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<potential-dns-tunneling-via-nslookup, Potential DNS Tunneling via NsLookup>> |This rule identifies a large number (15) of nslookup.exe executions with an explicit query type from the same host. This may indicate command and control activity utilizing the DNS protocol. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<potential-dns-tunneling-via-nslookup, Potential DNS Tunneling via NsLookup>> |This rule identifies a large number (15) of nslookup.exe executions with an explicit query type from the same host. This may indicate command and control activity utilizing the DNS protocol. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<potential-data-exfiltration-activity-to-an-unusual-destination-port, Potential Data Exfiltration Activity to an Unusual Destination Port>> |A machine learning job has detected data exfiltration to a particular destination port. Data transfer patterns that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |8.9.0 |3
+|<<potential-data-exfiltration-activity-to-an-unusual-destination-port, Potential Data Exfiltration Activity to an Unusual Destination Port>> |A machine learning job has detected data exfiltration to a particular destination port. Data transfer patterns that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |None |4
 
-|<<potential-data-exfiltration-activity-to-an-unusual-ip-address, Potential Data Exfiltration Activity to an Unusual IP Address>> |A machine learning job has detected data exfiltration to a particular geo-location (by IP address). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |8.9.0 |3
+|<<potential-data-exfiltration-activity-to-an-unusual-ip-address, Potential Data Exfiltration Activity to an Unusual IP Address>> |A machine learning job has detected data exfiltration to a particular geo-location (by IP address). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |None |4
 
-|<<potential-data-exfiltration-activity-to-an-unusual-iso-code, Potential Data Exfiltration Activity to an Unusual ISO Code>> |A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |8.9.0 |3
+|<<potential-data-exfiltration-activity-to-an-unusual-iso-code, Potential Data Exfiltration Activity to an Unusual ISO Code>> |A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |None |4
 
-|<<potential-data-exfiltration-activity-to-an-unusual-region, Potential Data Exfiltration Activity to an Unusual Region>> |A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |8.9.0 |3
+|<<potential-data-exfiltration-activity-to-an-unusual-region, Potential Data Exfiltration Activity to an Unusual Region>> |A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |None |4
 
-|<<potential-defense-evasion-via-cmstp-exe, Potential Defense Evasion via CMSTP.exe>> |The Microsoft Connection Manager Profile Installer (CMSTP.exe) is a command-line program to install Connection Manager service profiles, which accept installation information file (INF) files. Adversaries may abuse CMSTP to proxy the execution of malicious code by supplying INF files that contain malicious commands. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |2
+|<<potential-defense-evasion-via-cmstp-exe, Potential Defense Evasion via CMSTP.exe>> |The Microsoft Connection Manager Profile Installer (CMSTP.exe) is a command-line program to install Connection Manager service profiles, which accept installation information file (INF) files. Adversaries may abuse CMSTP to proxy the execution of malicious code by supplying INF files that contain malicious commands. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |None |2
 
-|<<potential-defense-evasion-via-proot, Potential Defense Evasion via PRoot>> |Identifies the execution of the PRoot utility, an open-source tool for user-space implementation of chroot, mount --bind, and binfmt_misc. Adversaries can leverage an open-source tool PRoot to expand the scope of their operations to multiple Linux distributions and simplify their necessary efforts. In a normal threat scenario, the scope of an attack is limited by the varying configurations of each Linux distribution. With PRoot, it provides an attacker with a consistent operational environment across different Linux distributions, such as Ubuntu, Fedora, and Alpine. PRoot also provides emulation capabilities that allow for malware built on other architectures, such as ARM, to be run.The post-exploitation technique called bring your own filesystem (BYOF), can be used by the threat actors to execute malicious payload or elevate privileges or perform network scans or orchestrate another attack on the environment. Although PRoot was originally not developed with malicious intent it can be easily tuned to work for one. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |7
+|<<potential-defense-evasion-via-proot, Potential Defense Evasion via PRoot>> |Identifies the execution of the PRoot utility, an open-source tool for user-space implementation of chroot, mount --bind, and binfmt_misc. Adversaries can leverage an open-source tool PRoot to expand the scope of their operations to multiple Linux distributions and simplify their necessary efforts. In a normal threat scenario, the scope of an attack is limited by the varying configurations of each Linux distribution. With PRoot, it provides an attacker with a consistent operational environment across different Linux distributions, such as Ubuntu, Fedora, and Alpine. PRoot also provides emulation capabilities that allow for malware built on other architectures, such as ARM, to be run.The post-exploitation technique called bring your own filesystem (BYOF), can be used by the threat actors to execute malicious payload or elevate privileges or perform network scans or orchestrate another attack on the environment. Although PRoot was originally not developed with malicious intent it can be easily tuned to work for one. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |7
 
-|<<potential-disabling-of-apparmor, Potential Disabling of AppArmor>> |This rule monitors for potential attempts to disable AppArmor. AppArmor is a Linux security module that enforces fine-grained access control policies to restrict the actions and resources that specific applications and processes can access. Adversaries may disable security tools to avoid possible detection of their tools and activities. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |6
+|<<potential-disabling-of-apparmor, Potential Disabling of AppArmor>> |This rule monitors for potential attempts to disable AppArmor. AppArmor is a Linux security module that enforces fine-grained access control policies to restrict the actions and resources that specific applications and processes can access. Adversaries may disable security tools to avoid possible detection of their tools and activities. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |6
 
-|<<potential-disabling-of-selinux, Potential Disabling of SELinux>> |Identifies potential attempts to disable Security-Enhanced Linux (SELinux), which is a Linux kernel security feature to support access control policies. Adversaries may disable security tools to avoid possible detection of their tools and activities. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |110
+|<<potential-disabling-of-selinux, Potential Disabling of SELinux>> |Identifies potential attempts to disable Security-Enhanced Linux (SELinux), which is a Linux kernel security feature to support access control policies. Adversaries may disable security tools to avoid possible detection of their tools and activities. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |110
 
-|<<potential-enumeration-via-active-directory-web-service, Potential Enumeration via Active Directory Web Service>> |Identifies processes loading Active Directory related modules followed by a network connection to the ADWS dedicated TCP port. Adversaries may abuse the ADWS Windows service that allows Active Directory to be queried via this web service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |8.3.0 |2
+|<<potential-enumeration-via-active-directory-web-service, Potential Enumeration via Active Directory Web Service>> |Identifies processes loading Active Directory related modules followed by a network connection to the ADWS dedicated TCP port. Adversaries may abuse the ADWS Windows service that allows Active Directory to be queried via this web service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |None |2
 
-|<<potential-evasion-via-filter-manager, Potential Evasion via Filter Manager>> |The Filter Manager Control Program (fltMC.exe) binary may be abused by adversaries to unload a filter driver and evade defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |110
+|<<potential-evasion-via-filter-manager, Potential Evasion via Filter Manager>> |The Filter Manager Control Program (fltMC.exe) binary may be abused by adversaries to unload a filter driver and evade defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |110
 
-|<<potential-evasion-via-windows-filtering-platform, Potential Evasion via Windows Filtering Platform>> |Identifies multiple Windows Filtering Platform block events and where the process name is related to an endpoint security software. Adversaries may add malicious WFP rules to prevent Endpoint security from sending telemetry. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |3
+|<<potential-evasion-via-windows-filtering-platform, Potential Evasion via Windows Filtering Platform>> |Identifies multiple Windows Filtering Platform block events and where the process name is related to an endpoint security software. Adversaries may add malicious WFP rules to prevent Endpoint security from sending telemetry. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |3
 
-|<<potential-execution-via-xzbackdoor, Potential Execution via XZBackdoor>> |It identifies potential malicious shell executions through remote SSH and detects cases where the sshd service suddenly terminates soon after successful execution, suggesting suspicious behavior similar to the XZ backdoor. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |8.3.0 |1
+|<<potential-execution-via-xzbackdoor, Potential Execution via XZBackdoor>> |It identifies potential malicious shell executions through remote SSH and detects cases where the sshd service suddenly terminates soon after successful execution, suggesting suspicious behavior similar to the XZ backdoor. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |None |1
 
-|<<potential-exploitation-of-an-unquoted-service-path-vulnerability, Potential Exploitation of an Unquoted Service Path Vulnerability>> |Adversaries may leverage unquoted service path vulnerabilities to escalate privileges. By placing an executable in a higher-level directory within the path of an unquoted service executable, Windows will natively launch this executable from its defined path variable instead of the benign one in a deeper directory, thus leading to code execution. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |3
+|<<potential-exploitation-of-an-unquoted-service-path-vulnerability, Potential Exploitation of an Unquoted Service Path Vulnerability>> |Adversaries may leverage unquoted service path vulnerabilities to escalate privileges. By placing an executable in a higher-level directory within the path of an unquoted service executable, Windows will natively launch this executable from its defined path variable instead of the benign one in a deeper directory, thus leading to code execution. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |3
 
-|<<potential-external-linux-ssh-brute-force-detected, Potential External Linux SSH Brute Force Detected>> |Identifies multiple external consecutive login failures targeting a user account from the same source address within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to these accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |8.3.0 |7
+|<<potential-external-linux-ssh-brute-force-detected, Potential External Linux SSH Brute Force Detected>> |Identifies multiple external consecutive login failures targeting a user account from the same source address within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to these accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |None |7
 
-|<<potential-file-download-via-a-headless-browser, Potential File Download via a Headless Browser>> |Identifies the use of a browser to download a file from a remote URL and from a suspicious parent process. Adversaries may use browsers to avoid ingress tool transfer restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Windows], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |1
+|<<potential-file-download-via-a-headless-browser, Potential File Download via a Headless Browser>> |Identifies the use of a browser to download a file from a remote URL and from a suspicious parent process. Adversaries may use browsers to avoid ingress tool transfer restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Windows], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |1
 
-|<<potential-file-transfer-via-certreq, Potential File Transfer via Certreq>> |Identifies Certreq making an HTTP Post request. Adversaries could abuse Certreq to download files or upload data to a remote URL. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Command and Control], [Tactic: Exfiltration], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |8
+|<<potential-file-transfer-via-certreq, Potential File Transfer via Certreq>> |Identifies Certreq making an HTTP Post request. Adversaries could abuse Certreq to download files or upload data to a remote URL. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Command and Control], [Tactic: Exfiltration], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |8
 
-|<<potential-hidden-local-user-account-creation, Potential Hidden Local User Account Creation>> |Identifies attempts to create a local account that will be hidden from the macOS logon window. This may indicate an attempt to evade user attention while maintaining persistence using a separate local account. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<potential-hidden-local-user-account-creation, Potential Hidden Local User Account Creation>> |Identifies attempts to create a local account that will be hidden from the macOS logon window. This may indicate an attempt to evade user attention while maintaining persistence using a separate local account. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<potential-hidden-process-via-mount-hidepid, Potential Hidden Process via Mount Hidepid>> |Identifies the execution of mount process with hidepid parameter, which can make processes invisible to other users from the system. Adversaries using Linux kernel version 3.2+ (or RHEL/CentOS v6.5+ above) can hide the process from other users. When hidepid=2 option is executed to mount the /proc filesystem, only the root user can see all processes and the logged-in user can only see their own process. This provides a defense evasion mechanism for the adversaries to hide their process executions from all other commands such as ps, top, pgrep and more. With the Linux kernel hardening hidepid option all the user has to do is remount the /proc filesystem with the option, which can now be monitored and detected. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |8
+|<<potential-hidden-process-via-mount-hidepid, Potential Hidden Process via Mount Hidepid>> |Identifies the execution of mount process with hidepid parameter, which can make processes invisible to other users from the system. Adversaries using Linux kernel version 3.2+ (or RHEL/CentOS v6.5+ above) can hide the process from other users. When hidepid=2 option is executed to mount the /proc filesystem, only the root user can see all processes and the logged-in user can only see their own process. This provides a defense evasion mechanism for the adversaries to hide their process executions from all other commands such as ps, top, pgrep and more. With the Linux kernel hardening hidepid option all the user has to do is remount the /proc filesystem with the option, which can now be monitored and detected. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |8
 
-|<<potential-internal-linux-ssh-brute-force-detected, Potential Internal Linux SSH Brute Force Detected>> |Identifies multiple internal consecutive login failures targeting a user account from the same source address within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to these accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |8.3.0 |11
+|<<potential-internal-linux-ssh-brute-force-detected, Potential Internal Linux SSH Brute Force Detected>> |Identifies multiple internal consecutive login failures targeting a user account from the same source address within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to these accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |None |11
 
-|<<potential-invoke-mimikatz-powershell-script, Potential Invoke-Mimikatz PowerShell Script>> |Mimikatz is a credential dumper capable of obtaining plaintext Windows account logins and passwords, along with many other features that make it useful for testing the security of networks. This rule detects Invoke-Mimikatz PowerShell script and alike. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |108
+|<<potential-invoke-mimikatz-powershell-script, Potential Invoke-Mimikatz PowerShell Script>> |Mimikatz is a credential dumper capable of obtaining plaintext Windows account logins and passwords, along with many other features that make it useful for testing the security of networks. This rule detects Invoke-Mimikatz PowerShell script and alike. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |108
 
-|<<potential-java-jndi-exploitation-attempt, Potential JAVA/JNDI Exploitation Attempt>> |Identifies an outbound network connection by JAVA to LDAP, RMI or DNS standard ports followed by a suspicious JAVA child processes. This may indicate an attempt to exploit a JAVA/NDI (Java Naming and Directory Interface) injection vulnerability. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |104
+|<<potential-java-jndi-exploitation-attempt, Potential JAVA/JNDI Exploitation Attempt>> |Identifies an outbound network connection by JAVA to LDAP, RMI or DNS standard ports followed by a suspicious JAVA child processes. This may indicate an attempt to exploit a JAVA/NDI (Java Naming and Directory Interface) injection vulnerability. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |104
 
-|<<potential-kerberos-attack-via-bifrost, Potential Kerberos Attack via Bifrost>> |Identifies use of Bifrost, a known macOS Kerberos pentesting tool, which can be used to dump cached Kerberos tickets or attempt unauthorized authentication techniques such as pass-the-ticket/hash and kerberoasting. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |8.3.0 |106
+|<<potential-kerberos-attack-via-bifrost, Potential Kerberos Attack via Bifrost>> |Identifies use of Bifrost, a known macOS Kerberos pentesting tool, which can be used to dump cached Kerberos tickets or attempt unauthorized authentication techniques such as pass-the-ticket/hash and kerberoasting. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |None |106
 
-|<<potential-lsa-authentication-package-abuse, Potential LSA Authentication Package Abuse>> |Adversaries can use the autostart mechanism provided by the Local Security Authority (LSA) authentication packages for privilege escalation or persistence by placing a reference to a binary in the Windows registry. The binary will then be executed by SYSTEM when the authentication packages are loaded. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |105
+|<<potential-lsa-authentication-package-abuse, Potential LSA Authentication Package Abuse>> |Adversaries can use the autostart mechanism provided by the Local Security Authority (LSA) authentication packages for privilege escalation or persistence by placing a reference to a binary in the Windows registry. The binary will then be executed by SYSTEM when the authentication packages are loaded. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |105
 
-|<<potential-lsass-clone-creation-via-psscapturesnapshot, Potential LSASS Clone Creation via PssCaptureSnapShot>> |Identifies the creation of an LSASS process clone via PssCaptureSnapShot where the parent process is the initial LSASS process instance. This may indicate an attempt to evade detection and dump LSASS memory for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |8.3.0 |106
+|<<potential-lsass-clone-creation-via-psscapturesnapshot, Potential LSASS Clone Creation via PssCaptureSnapShot>> |Identifies the creation of an LSASS process clone via PssCaptureSnapShot where the parent process is the initial LSASS process instance. This may indicate an attempt to evade detection and dump LSASS memory for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |None |106
 
-|<<potential-lsass-memory-dump-via-psscapturesnapshot, Potential LSASS Memory Dump via PssCaptureSnapShot>> |Identifies suspicious access to an LSASS handle via PssCaptureSnapShot where two successive process accesses are performed by the same process and target two different instances of LSASS. This may indicate an attempt to evade detection and dump LSASS memory for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |8.8.0 |208
+|<<potential-lsass-memory-dump-via-psscapturesnapshot, Potential LSASS Memory Dump via PssCaptureSnapShot>> |Identifies suspicious access to an LSASS handle via PssCaptureSnapShot where two successive process accesses are performed by the same process and target two different instances of LSASS. This may indicate an attempt to evade detection and dump LSASS memory for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |None |208
 
-|<<potential-lateral-tool-transfer-via-smb-share, Potential Lateral Tool Transfer via SMB Share>> |Identifies the creation or change of a Windows executable file over network shares. Adversaries may transfer tools or other files between systems in a compromised environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |108
+|<<potential-lateral-tool-transfer-via-smb-share, Potential Lateral Tool Transfer via SMB Share>> |Identifies the creation or change of a Windows executable file over network shares. Adversaries may transfer tools or other files between systems in a compromised environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |108
 
-|<<potential-linux-backdoor-user-account-creation, Potential Linux Backdoor User Account Creation>> |Identifies the attempt to create a new backdoor user by setting the user's UID to 0. Attackers may alter a user's UID to 0 to establish persistence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |6
+|<<potential-linux-backdoor-user-account-creation, Potential Linux Backdoor User Account Creation>> |Identifies the attempt to create a new backdoor user by setting the user's UID to 0. Attackers may alter a user's UID to 0 to establish persistence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |7
 
-|<<potential-linux-credential-dumping-via-proc-filesystem, Potential Linux Credential Dumping via Proc Filesystem>> |Identifies the execution of the mimipenguin exploit script which is linux adaptation of Windows tool mimikatz. Mimipenguin exploit script is used to dump clear text passwords from a currently logged-in user. The tool exploits a known vulnerability CVE-2018-20781. Malicious actors can exploit the cleartext credentials in memory by dumping the process and extracting lines that have a high probability of containing cleartext passwords. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |7
+|<<potential-linux-credential-dumping-via-proc-filesystem, Potential Linux Credential Dumping via Proc Filesystem>> |Identifies the execution of the mimipenguin exploit script which is linux adaptation of Windows tool mimikatz. Mimipenguin exploit script is used to dump clear text passwords from a currently logged-in user. The tool exploits a known vulnerability CVE-2018-20781. Malicious actors can exploit the cleartext credentials in memory by dumping the process and extracting lines that have a high probability of containing cleartext passwords. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |7
 
-|<<potential-linux-credential-dumping-via-unshadow, Potential Linux Credential Dumping via Unshadow>> |Identifies the execution of the unshadow utility which is part of John the Ripper, a password-cracking tool on the host machine. Malicious actors can use the utility to retrieve the combined contents of the '/etc/shadow' and '/etc/password' files. Using the combined file generated from the utility, the malicious threat actors can use them as input for password-cracking utilities or prepare themselves for future operations by gathering credential information of the victim. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |8
+|<<potential-linux-credential-dumping-via-unshadow, Potential Linux Credential Dumping via Unshadow>> |Identifies the execution of the unshadow utility which is part of John the Ripper, a password-cracking tool on the host machine. Malicious actors can use the utility to retrieve the combined contents of the '/etc/shadow' and '/etc/password' files. Using the combined file generated from the utility, the malicious threat actors can use them as input for password-cracking utilities or prepare themselves for future operations by gathering credential information of the victim. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |8
 
-|<<potential-linux-hack-tool-launched, Potential Linux Hack Tool Launched>> |Monitors for the execution of different processes that might be used by attackers for malicious intent. An alert from this rule should be investigated further, as hack tools are commonly used by blue teamers and system administrators as well. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |3
+|<<potential-linux-hack-tool-launched, Potential Linux Hack Tool Launched>> |Monitors for the execution of different processes that might be used by attackers for malicious intent. An alert from this rule should be investigated further, as hack tools are commonly used by blue teamers and system administrators as well. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |3
 
-|<<potential-linux-local-account-brute-force-detected, Potential Linux Local Account Brute Force Detected>> |Identifies multiple consecutive login attempts executed by one process targeting a local linux user account within a short time interval. Adversaries might brute force login attempts across different users with a default wordlist or a set of customly crafted passwords in an attempt to gain access to these accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.3.0 |6
+|<<potential-linux-local-account-brute-force-detected, Potential Linux Local Account Brute Force Detected>> |Identifies multiple consecutive login attempts executed by one process targeting a local linux user account within a short time interval. Adversaries might brute force login attempts across different users with a default wordlist or a set of customly crafted passwords in an attempt to gain access to these accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |6
 
-|<<potential-linux-ransomware-note-creation-detected, Potential Linux Ransomware Note Creation Detected>> |This rule identifies a sequence of a mass file encryption event in conjunction with the creation of a .txt file with a file name containing ransomware keywords executed by the same process in a 1 second timespan. Ransomware is a type of malware that encrypts a victim's files or systems and demands payment (usually in cryptocurrency) in exchange for the decryption key. One important indicator of a ransomware attack is the mass encryption of the file system, after which a new file extension is added to the file. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend] |8.3.0 |8
+|<<potential-linux-ransomware-note-creation-detected, Potential Linux Ransomware Note Creation Detected>> |This rule identifies a sequence of a mass file encryption event in conjunction with the creation of a .txt file with a file name containing ransomware keywords executed by the same process in a 1 second timespan. Ransomware is a type of malware that encrypts a victim's files or systems and demands payment (usually in cryptocurrency) in exchange for the decryption key. One important indicator of a ransomware attack is the mass encryption of the file system, after which a new file extension is added to the file. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend] |None |8
 
-|<<potential-linux-ssh-x11-forwarding, Potential Linux SSH X11 Forwarding>> |This rule monitors for X11 forwarding via SSH. X11 forwarding is a feature that allows users to run graphical applications on a remote server and display the application's graphical user interface on their local machine. Attackers can abuse X11 forwarding for tunneling their GUI-based tools, pivot through compromised systems, and create covert communication channels, enabling lateral movement and facilitating remote control of systems within a network. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR] |8.3.0 |3
+|<<potential-linux-ssh-x11-forwarding, Potential Linux SSH X11 Forwarding>> |This rule monitors for X11 forwarding via SSH. X11 forwarding is a feature that allows users to run graphical applications on a remote server and display the application's graphical user interface on their local machine. Attackers can abuse X11 forwarding for tunneling their GUI-based tools, pivot through compromised systems, and create covert communication channels, enabling lateral movement and facilitating remote control of systems within a network. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR] |None |3
 
-|<<potential-linux-tunneling-and-or-port-forwarding, Potential Linux Tunneling and/or Port Forwarding>> |This rule monitors for a set of Linux utilities that can be used for tunneling and port forwarding. Attackers can leverage tunneling and port forwarding techniques to bypass network defenses, establish hidden communication channels, and gain unauthorized access to internal resources, facilitating data exfiltration, lateral movement, and remote control. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |7
+|<<potential-linux-tunneling-and-or-port-forwarding, Potential Linux Tunneling and/or Port Forwarding>> |This rule monitors for a set of Linux utilities that can be used for tunneling and port forwarding. Attackers can leverage tunneling and port forwarding techniques to bypass network defenses, establish hidden communication channels, and gain unauthorized access to internal resources, facilitating data exfiltration, lateral movement, and remote control. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |7
 
-|<<potential-local-ntlm-relay-via-http, Potential Local NTLM Relay via HTTP>> |Identifies attempt to coerce a local NTLM authentication via HTTP using the Windows Printer Spooler service as a target. An adversary may use this primitive in combination with other techniques to elevate privileges on a compromised system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<potential-local-ntlm-relay-via-http, Potential Local NTLM Relay via HTTP>> |Identifies attempt to coerce a local NTLM authentication via HTTP using the Windows Printer Spooler service as a target. An adversary may use this primitive in combination with other techniques to elevate privileges on a compromised system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<potential-masquerading-as-browser-process, Potential Masquerading as Browser Process>> |Identifies suspicious instances of browser processes, such as unsigned or signed with unusual certificates, that can indicate an attempt to conceal malicious activity, bypass security features such as allowlists, or trick users into executing malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |4
+|<<potential-masquerading-as-browser-process, Potential Masquerading as Browser Process>> |Identifies suspicious instances of browser processes, such as unsigned or signed with unusual certificates, that can indicate an attempt to conceal malicious activity, bypass security features such as allowlists, or trick users into executing malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Elastic Defend] |None |4
 
-|<<potential-masquerading-as-business-app-installer, Potential Masquerading as Business App Installer>> |Identifies executables with names resembling legitimate business applications but lacking signatures from the original developer. Attackers may trick users into downloading malicious executables that masquerade as legitimate applications via malicious ads, forum posts, and tutorials, effectively gaining initial access. |[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Initial Access], [Tactic: Execution] |8.3.0 |4
+|<<potential-masquerading-as-business-app-installer, Potential Masquerading as Business App Installer>> |Identifies executables with names resembling legitimate business applications but lacking signatures from the original developer. Attackers may trick users into downloading malicious executables that masquerade as legitimate applications via malicious ads, forum posts, and tutorials, effectively gaining initial access. |[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Initial Access], [Tactic: Execution] |None |4
 
-|<<potential-masquerading-as-communication-apps, Potential Masquerading as Communication Apps>> |Identifies suspicious instances of communications apps, both unsigned and renamed ones, that can indicate an attempt to conceal malicious activity, bypass security features such as allowlists, or trick users into executing malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |5
+|<<potential-masquerading-as-communication-apps, Potential Masquerading as Communication Apps>> |Identifies suspicious instances of communications apps, both unsigned and renamed ones, that can indicate an attempt to conceal malicious activity, bypass security features such as allowlists, or trick users into executing malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |5
 
-|<<potential-masquerading-as-system32-dll, Potential Masquerading as System32 DLL>> |Identifies suspicious instances of default system32 DLLs either unsigned or signed with non-MS certificates. This can potentially indicate the attempt to masquerade as system DLLs, perform DLL Search Order Hijacking or backdoor and resign legitimate DLLs. |[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR] |8.4.0 |104
+|<<potential-masquerading-as-system32-dll, Potential Masquerading as System32 DLL>> |Identifies suspicious instances of default system32 DLLs either unsigned or signed with non-MS certificates. This can potentially indicate the attempt to masquerade as system DLLs, perform DLL Search Order Hijacking or backdoor and resign legitimate DLLs. |[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR] |None |104
 
-|<<potential-masquerading-as-system32-executable, Potential Masquerading as System32 Executable>> |Identifies suspicious instances of default system32 executables, either unsigned or signed with non-MS certificates. This could indicate the attempt to masquerade as system executables or backdoored and resigned legitimate executables. |[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR] |8.3.0 |4
+|<<potential-masquerading-as-system32-executable, Potential Masquerading as System32 Executable>> |Identifies suspicious instances of default system32 executables, either unsigned or signed with non-MS certificates. This could indicate the attempt to masquerade as system executables or backdoored and resigned legitimate executables. |[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR] |None |4
 
-|<<potential-masquerading-as-vlc-dll, Potential Masquerading as VLC DLL>> |Identifies instances of VLC-related DLLs which are not signed by the original developer. Attackers may name their payload as legitimate applications to blend into the environment, or embedding its malicious code within legitimate applications to deceive machine learning algorithms by incorporating authentic and benign code. |[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR] |8.3.0 |3
+|<<potential-masquerading-as-vlc-dll, Potential Masquerading as VLC DLL>> |Identifies instances of VLC-related DLLs which are not signed by the original developer. Attackers may name their payload as legitimate applications to blend into the environment, or embedding its malicious code within legitimate applications to deceive machine learning algorithms by incorporating authentic and benign code. |[Domain: Endpoint], [Data Source: Elastic Defend], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR] |None |3
 
-|<<potential-memory-seeking-activity, Potential Memory Seeking Activity>> |Monitors for the execution of Unix utilities that may be leveraged as memory address seekers. Attackers may leverage built-in utilities to seek specific memory addresses, allowing for potential future manipulation/exploitation. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<potential-memory-seeking-activity, Potential Memory Seeking Activity>> |Monitors for the execution of Unix utilities that may be leveraged as memory address seekers. Attackers may leverage built-in utilities to seek specific memory addresses, allowing for potential future manipulation/exploitation. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |2
 
-|<<potential-meterpreter-reverse-shell, Potential Meterpreter Reverse Shell>> |This detection rule identifies a sample of suspicious Linux system file reads used for system fingerprinting, leveraged by the Metasploit Meterpreter shell to gather information about the target that it is executing its shell on. Detecting this pattern is indicative of a successful meterpreter shell connection. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |8.6.0 |6
+|<<potential-meterpreter-reverse-shell, Potential Meterpreter Reverse Shell>> |This detection rule identifies a sample of suspicious Linux system file reads used for system fingerprinting, leveraged by the Metasploit Meterpreter shell to gather information about the target that it is executing its shell on. Detecting this pattern is indicative of a successful meterpreter shell connection. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |None |6
 
-|<<potential-microsoft-office-sandbox-evasion, Potential Microsoft Office Sandbox Evasion>> |Identifies the creation of a suspicious zip file prepended with special characters. Sandboxed Microsoft Office applications on macOS are allowed to write files that start with special characters, which can be combined with an AutoStart location to achieve sandbox evasion. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |106
+|<<potential-microsoft-office-sandbox-evasion, Potential Microsoft Office Sandbox Evasion>> |Identifies the creation of a suspicious zip file prepended with special characters. Sandboxed Microsoft Office applications on macOS are allowed to write files that start with special characters, which can be combined with an AutoStart location to achieve sandbox evasion. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |106
 
-|<<potential-modification-of-accessibility-binaries, Potential Modification of Accessibility Binaries>> |Windows contains accessibility features that may be launched with a key combination before a user has logged in. An adversary can modify the way these programs are launched to get a command prompt or backdoor without logging in to the system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<potential-modification-of-accessibility-binaries, Potential Modification of Accessibility Binaries>> |Windows contains accessibility features that may be launched with a key combination before a user has logged in. An adversary can modify the way these programs are launched to get a command prompt or backdoor without logging in to the system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<potential-network-scan-detected, Potential Network Scan Detected>> |This rule identifies a potential port scan. A port scan is a method utilized by attackers to systematically scan a target system or network for open ports, allowing them to identify available services and potential vulnerabilities. By mapping out the open ports, attackers can gather critical information to plan and execute targeted attacks, gaining unauthorized access, compromising security, and potentially leading to data breaches, unauthorized control, or further exploitation of the targeted system or network. This rule proposes threshold logic to check for connection attempts from one source host to 20 or more destination ports. |[Domain: Network], [Tactic: Discovery], [Tactic: Reconnaissance], [Use Case: Network Security Monitoring] |8.3.0 |5
+|<<potential-network-scan-detected, Potential Network Scan Detected>> |This rule identifies a potential port scan. A port scan is a method utilized by attackers to systematically scan a target system or network for open ports, allowing them to identify available services and potential vulnerabilities. By mapping out the open ports, attackers can gather critical information to plan and execute targeted attacks, gaining unauthorized access, compromising security, and potentially leading to data breaches, unauthorized control, or further exploitation of the targeted system or network. This rule proposes threshold logic to check for connection attempts from one source host to 20 or more destination ports. |[Domain: Network], [Tactic: Discovery], [Tactic: Reconnaissance], [Use Case: Network Security Monitoring] |None |5
 
-|<<potential-network-scan-executed-from-host, Potential Network Scan Executed From Host>> |This threshold rule monitors for the rapid execution of unix utilities that are capable of conducting network scans. Adversaries may leverage built-in tools such as ping, netcat or socat to execute ping sweeps across the network while attempting to evade detection or due to the lack of network mapping tools available on the compromised host. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |3
+|<<potential-network-scan-executed-from-host, Potential Network Scan Executed From Host>> |This threshold rule monitors for the rapid execution of unix utilities that are capable of conducting network scans. Adversaries may leverage built-in tools such as ping, netcat or socat to execute ping sweeps across the network while attempting to evade detection or due to the lack of network mapping tools available on the compromised host. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |3
 
-|<<potential-network-share-discovery, Potential Network Share Discovery>> |Adversaries may look for folders and drives shared on remote systems to identify sources of information to gather as a precursor for collection and identify potential systems of interest for Lateral Movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Rule Type: BBR] |8.3.0 |3
+|<<potential-network-share-discovery, Potential Network Share Discovery>> |Adversaries may look for folders and drives shared on remote systems to identify sources of information to gather as a precursor for collection and identify potential systems of interest for Lateral Movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Rule Type: BBR] |None |3
 
-|<<potential-network-sweep-detected, Potential Network Sweep Detected>> |This rule identifies a potential network sweep.  A network sweep is a method used by attackers to scan a target network, identifying active hosts, open ports, and available services to gather information on vulnerabilities and weaknesses. This reconnaissance helps them plan subsequent attacks and exploit potential entry points for unauthorized access, data theft, or other malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination hosts on commonly used network services. |[Domain: Network], [Tactic: Discovery], [Tactic: Reconnaissance], [Use Case: Network Security Monitoring] |8.3.0 |5
+|<<potential-network-sweep-detected, Potential Network Sweep Detected>> |This rule identifies a potential network sweep. A network sweep is a method used by attackers to scan a target network, identifying active hosts, open ports, and available services to gather information on vulnerabilities and weaknesses. This reconnaissance helps them plan subsequent attacks and exploit potential entry points for unauthorized access, data theft, or other malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination hosts on commonly used network services. |[Domain: Network], [Tactic: Discovery], [Tactic: Reconnaissance], [Use Case: Network Security Monitoring] |None |6
 
-|<<potential-non-standard-port-http-https-connection, Potential Non-Standard Port HTTP/HTTPS connection>> |Identifies potentially malicious processes communicating via a port paring typically not associated with HTTP/HTTPS. For example, HTTP over port 8443 or port 440 as opposed to the traditional port 80 , 443. Adversaries may make changes to the standard port a protocol uses to bypass filtering or muddle analysis/parsing of network data. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Command and Control], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |4
+|<<potential-non-standard-port-http-https-connection, Potential Non-Standard Port HTTP/HTTPS connection>> |Identifies potentially malicious processes communicating via a port paring typically not associated with HTTP/HTTPS. For example, HTTP over port 8443 or port 440 as opposed to the traditional port 80 , 443. Adversaries may make changes to the standard port a protocol uses to bypass filtering or muddle analysis/parsing of network data. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Command and Control], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |5
 
-|<<potential-non-standard-port-ssh-connection, Potential Non-Standard Port SSH connection>> |Identifies potentially malicious processes communicating via a port paring typically not associated with SSH. For example, SSH over port 2200 or port 2222 as opposed to the traditional port 22. Adversaries may make changes to the standard port a protocol uses to bypass filtering or muddle analysis/parsing of network data. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [OS: macOS], [Data Source: Elastic Defend] |8.3.0 |5
+|<<potential-non-standard-port-ssh-connection, Potential Non-Standard Port SSH connection>> |Identifies potentially malicious processes communicating via a port paring typically not associated with SSH. For example, SSH over port 2200 or port 2222 as opposed to the traditional port 22. Adversaries may make changes to the standard port a protocol uses to bypass filtering or muddle analysis/parsing of network data. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [OS: macOS], [Data Source: Elastic Defend] |None |5
 
 |<<potential-okta-mfa-bombing-via-push-notifications, Potential Okta MFA Bombing via Push Notifications>> |Detects when an attacker abuses the Multi-Factor authentication mechanism by repeatedly issuing login requests until the user eventually accepts the Okta push notification. An adversary may attempt to bypass the Okta MFA policies configured for an organization to obtain unauthorized access. |[Use Case: Identity and Access Audit], [Tactic: Credential Access], [Data Source: Okta] |8.10.0 |3
 
-|<<potential-openssh-backdoor-logging-activity, Potential OpenSSH Backdoor Logging Activity>> |Identifies a Secure Shell (SSH) client or server process creating or writing to a known SSH backdoor log file. Adversaries may modify SSH related binaries for persistence or credential access via patching sensitive functions to enable unauthorized access or to log SSH credentials for exfiltration. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<potential-openssh-backdoor-logging-activity, Potential OpenSSH Backdoor Logging Activity>> |Identifies a Secure Shell (SSH) client or server process creating or writing to a known SSH backdoor log file. Adversaries may modify SSH related binaries for persistence or credential access via patching sensitive functions to enable unauthorized access or to log SSH credentials for exfiltration. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<potential-outgoing-rdp-connection-by-unusual-process, Potential Outgoing RDP Connection by Unusual Process>> |Adversaries may attempt to connect to a remote system over Windows Remote Desktop Protocol (RDP) to achieve lateral movement. Adversaries may avoid using the Microsoft Terminal Services Client (mstsc.exe) binary to establish an RDP connection to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |8.3.0 |3
+|<<potential-outgoing-rdp-connection-by-unusual-process, Potential Outgoing RDP Connection by Unusual Process>> |Adversaries may attempt to connect to a remote system over Windows Remote Desktop Protocol (RDP) to achieve lateral movement. Adversaries may avoid using the Microsoft Terminal Services Client (mstsc.exe) binary to establish an RDP connection to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |None |3
 
-|<<potential-pass-the-hash-pth-attempt, Potential Pass-the-Hash (PtH) Attempt>> |Adversaries may pass the hash using stolen password hashes to move laterally within an environment, bypassing normal system access controls. Pass the hash (PtH) is a method of authenticating as a user without having access to the user's cleartext password. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement] |8.4.0 |3
+|<<potential-pass-the-hash-pth-attempt, Potential Pass-the-Hash (PtH) Attempt>> |Adversaries may pass the hash using stolen password hashes to move laterally within an environment, bypassing normal system access controls. Pass the hash (PtH) is a method of authenticating as a user without having access to the user's cleartext password. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement] |None |3
 
-|<<potential-password-spraying-of-microsoft-365-user-accounts, Potential Password Spraying of Microsoft 365 User Accounts>> |Identifies a high number (25) of failed Microsoft 365 user authentication attempts from a single IP address within 30 minutes, which could be indicative of a password spraying attack. An adversary may attempt a password spraying attack to obtain unauthorized access to user accounts. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |8.8.0 |207
+|<<potential-password-spraying-of-microsoft-365-user-accounts, Potential Password Spraying of Microsoft 365 User Accounts>> |Identifies a high number (25) of failed Microsoft 365 user authentication attempts from a single IP address within 30 minutes, which could be indicative of a password spraying attack. An adversary may attempt a password spraying attack to obtain unauthorized access to user accounts. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Identity and Access Audit], [Tactic: Credential Access] |None |207
 
-|<<potential-persistence-through-motd-file-creation-detected, Potential Persistence Through MOTD File Creation Detected>> |Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" and "/usr/lib/update-notifier/" directories. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. This rule detects the creation of potentially malicious files within the default MOTD file directories. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.6.0 |9
+|<<potential-persistence-through-motd-file-creation-detected, Potential Persistence Through MOTD File Creation Detected>> |Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" and "/usr/lib/update-notifier/" directories. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. This rule detects the creation of potentially malicious files within the default MOTD file directories. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |10
 
-|<<potential-persistence-through-run-control-detected, Potential Persistence Through Run Control Detected>> |This rule monitors the creation/alteration of the rc.local file by a previously unknown process executable through the use of the new terms rule type. The /etc/rc.local file is used to start custom applications, services, scripts or commands during start-up. The rc.local file has mostly been replaced by Systemd. However, through the "systemd-rc-local-generator", rc.local files can be converted to services that run at boot. Adversaries may alter rc.local to execute malicious code at start-up, and gain persistence onto the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.6.0 |110
+|<<potential-persistence-through-run-control-detected, Potential Persistence Through Run Control Detected>> |This rule monitors the creation/alteration of the rc.local file by a previously unknown process executable through the use of the new terms rule type. The /etc/rc.local file is used to start custom applications, services, scripts or commands during start-up. The rc.local file has mostly been replaced by Systemd. However, through the "systemd-rc-local-generator", rc.local files can be converted to services that run at boot. Adversaries may alter rc.local to execute malicious code at start-up, and gain persistence onto the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |111
 
-|<<potential-persistence-through-systemd-udevd, Potential Persistence Through Systemd-udevd>> |Monitors for the creation of rule files that are used by systemd-udevd to manage device nodes and handle kernel device events in the Linux operating system. Systemd-udevd can be exploited for persistence by adversaries by creating malicious udev rules that trigger on specific events, executing arbitrary commands or payloads whenever a certain device is plugged in or recognized by the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |3
+|<<potential-persistence-through-systemd-udevd, Potential Persistence Through Systemd-udevd>> |Monitors for the creation of rule files that are used by systemd-udevd to manage device nodes and handle kernel device events in the Linux operating system. Systemd-udevd can be exploited for persistence by adversaries by creating malicious udev rules that trigger on specific events, executing arbitrary commands or payloads whenever a certain device is plugged in or recognized by the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |3
 
-|<<potential-persistence-through-init-d-detected, Potential Persistence Through init.d Detected>> |Files that are placed in the /etc/init.d/ directory in Unix can be used to start custom applications, services, scripts or commands during start-up. Init.d has been mostly replaced in favor of Systemd. However, the "systemd-sysv-generator" can convert init.d files to service unit files that run at boot. Adversaries may add or alter files located in the /etc/init.d/ directory to execute malicious code upon boot in order to gain persistence on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.6.0 |9
+|<<potential-persistence-through-init-d-detected, Potential Persistence Through init.d Detected>> |Files that are placed in the /etc/init.d/ directory in Unix can be used to start custom applications, services, scripts or commands during start-up. Init.d has been mostly replaced in favor of Systemd. However, the "systemd-sysv-generator" can convert init.d files to service unit files that run at boot. Adversaries may add or alter files located in the /etc/init.d/ directory to execute malicious code upon boot in order to gain persistence on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |10
 
-|<<potential-persistence-via-atom-init-script-modification, Potential Persistence via Atom Init Script Modification>> |Identifies modifications to the Atom desktop text editor Init File. Adversaries may add malicious JavaScript code to the init.coffee file that will be executed upon the Atom application opening. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<potential-persistence-via-atom-init-script-modification, Potential Persistence via Atom Init Script Modification>> |Identifies modifications to the Atom desktop text editor Init File. Adversaries may add malicious JavaScript code to the init.coffee file that will be executed upon the Atom application opening. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<potential-persistence-via-login-hook, Potential Persistence via Login Hook>> |Identifies the creation or modification of the login window property list (plist). Adversaries may modify plist files to run a program during system boot or user login for persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |108
+|<<potential-persistence-via-login-hook, Potential Persistence via Login Hook>> |Identifies the creation or modification of the login window property list (plist). Adversaries may modify plist files to run a program during system boot or user login for persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |108
 
-|<<potential-persistence-via-periodic-tasks, Potential Persistence via Periodic Tasks>> |Identifies the creation or modification of the default configuration for periodic tasks. Adversaries may abuse periodic tasks to execute malicious code or maintain persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<potential-persistence-via-periodic-tasks, Potential Persistence via Periodic Tasks>> |Identifies the creation or modification of the default configuration for periodic tasks. Adversaries may abuse periodic tasks to execute malicious code or maintain persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<potential-persistence-via-time-provider-modification, Potential Persistence via Time Provider Modification>> |Identifies modification of the Time Provider. Adversaries may establish persistence by registering and enabling a malicious DLL as a time provider. Windows uses the time provider architecture to obtain accurate time stamps from other network devices or clients in the network. Time providers are implemented in the form of a DLL file which resides in the System32 folder. The service W32Time initiates during the startup of Windows and loads w32time.dll. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<potential-persistence-via-time-provider-modification, Potential Persistence via Time Provider Modification>> |Identifies modification of the Time Provider. Adversaries may establish persistence by registering and enabling a malicious DLL as a time provider. Windows uses the time provider architecture to obtain accurate time stamps from other network devices or clients in the network. Time providers are implemented in the form of a DLL file which resides in the System32 folder. The service W32Time initiates during the startup of Windows and loads w32time.dll. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<potential-port-monitor-or-print-processor-registration-abuse, Potential Port Monitor or Print Processor Registration Abuse>> |Identifies port monitor and print processor registry modifications. Adversaries may abuse port monitor and print processors to run malicious DLLs during system boot that will be executed as SYSTEM for privilege escalation and/or persistence, if permissions allow writing a fully-qualified pathname for that DLL. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |106
+|<<potential-port-monitor-or-print-processor-registration-abuse, Potential Port Monitor or Print Processor Registration Abuse>> |Identifies port monitor and print processor registry modifications. Adversaries may abuse port monitor and print processors to run malicious DLLs during system boot that will be executed as SYSTEM for privilege escalation and/or persistence, if permissions allow writing a fully-qualified pathname for that DLL. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |106
 
-|<<potential-powershell-hacktool-script-by-author, Potential PowerShell HackTool Script by Author>> |Detects known PowerShell offensive tooling author's name in PowerShell scripts. Attackers commonly use out-of-the-box offensive tools without modifying the code, which may still contain the author artifacts. This rule identifies common author handles found in popular PowerShell scripts used for red team exercises. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: PowerShell Logs] |8.3.0 |1
+|<<potential-powershell-hacktool-script-by-author, Potential PowerShell HackTool Script by Author>> |Detects known PowerShell offensive tooling author's name in PowerShell scripts. Attackers commonly use out-of-the-box offensive tools without modifying the code, which may still contain the author artifacts. This rule identifies common author handles found in popular PowerShell scripts used for red team exercises. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: PowerShell Logs] |None |1
 
 |<<potential-powershell-hacktool-script-by-function-names, Potential PowerShell HackTool Script by Function Names>> |Detects known PowerShell offensive tooling functions names in PowerShell scripts. Attackers commonly use out-of-the-box offensive tools without modifying the code. This rule aim is to take advantage of that. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: PowerShell Logs] |8.3.0 |11
 
-|<<potential-powershell-pass-the-hash-relay-script, Potential PowerShell Pass-the-Hash/Relay Script>> |Detects PowerShell scripts that can execute pass-the-hash (PtH) attacks, intercept and relay NTLM challenges, and carry out other man-in-the-middle (MitM) attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |1
+|<<potential-powershell-pass-the-hash-relay-script, Potential PowerShell Pass-the-Hash/Relay Script>> |Detects PowerShell scripts that can execute pass-the-hash (PtH) attacks, intercept and relay NTLM challenges, and carry out other man-in-the-middle (MitM) attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |1
 
-|<<potential-privacy-control-bypass-via-localhost-secure-copy, Potential Privacy Control Bypass via Localhost Secure Copy>> |Identifies use of the Secure Copy Protocol (SCP) to copy files locally by abusing the auto addition of the Secure Shell Daemon (sshd) to the authorized application list for Full Disk Access. This may indicate attempts to bypass macOS privacy controls to access sensitive files. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |107
+|<<potential-privacy-control-bypass-via-localhost-secure-copy, Potential Privacy Control Bypass via Localhost Secure Copy>> |Identifies use of the Secure Copy Protocol (SCP) to copy files locally by abusing the auto addition of the Secure Shell Daemon (sshd) to the authorized application list for Full Disk Access. This may indicate attempts to bypass macOS privacy controls to access sensitive files. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |107
 
-|<<potential-privacy-control-bypass-via-tccdb-modification, Potential Privacy Control Bypass via TCCDB Modification>> |Identifies the use of sqlite3 to directly modify the Transparency, Consent, and Control (TCC) SQLite database. This may indicate an attempt to bypass macOS privacy controls, including access to sensitive resources like the system camera, microphone, address book, and calendar. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |107
+|<<potential-privacy-control-bypass-via-tccdb-modification, Potential Privacy Control Bypass via TCCDB Modification>> |Identifies the use of sqlite3 to directly modify the Transparency, Consent, and Control (TCC) SQLite database. This may indicate an attempt to bypass macOS privacy controls, including access to sensitive resources like the system camera, microphone, address book, and calendar. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |107
 
-|<<potential-privilege-escalation-through-writable-docker-socket, Potential Privilege Escalation through Writable Docker Socket>> |This rule monitors for the usage of Docker runtime sockets to escalate privileges on Linux systems. Docker sockets by default are only be writable by the root user and docker group. Attackers that have permissions to write to these sockets may be able to create and run a container that allows them to escalate privileges and gain further access onto the host file system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Domain: Container], [Data Source: Elastic Defend] |8.3.0 |5
+|<<potential-privilege-escalation-through-writable-docker-socket, Potential Privilege Escalation through Writable Docker Socket>> |This rule monitors for the usage of Docker runtime sockets to escalate privileges on Linux systems. Docker sockets by default are only be writable by the root user and docker group. Attackers that have permissions to write to these sockets may be able to create and run a container that allows them to escalate privileges and gain further access onto the host file system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Domain: Container], [Data Source: Elastic Defend] |None |5
 
-|<<potential-privilege-escalation-via-cve-2023-4911, Potential Privilege Escalation via CVE-2023-4911>> |This rule detects potential privilege escalation attempts through Looney Tunables (CVE-2023-4911). Looney Tunables is a buffer overflow vulnerability in GNU C Library's dynamic loader's processing of the GLIBC_TUNABLES environment variable. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.6.0 |4
+|<<potential-privilege-escalation-via-cve-2023-4911, Potential Privilege Escalation via CVE-2023-4911>> |This rule detects potential privilege escalation attempts through Looney Tunables (CVE-2023-4911). Looney Tunables is a buffer overflow vulnerability in GNU C Library's dynamic loader's processing of the GLIBC_TUNABLES environment variable. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |4
 
-|<<potential-privilege-escalation-via-container-misconfiguration, Potential Privilege Escalation via Container Misconfiguration>> |This rule monitors for the execution of processes that interact with Linux containers through an interactive shell without root permissions. Utilities such as runc and ctr are universal command-line utilities leveraged to interact with containers via root permissions. On systems where the access to these utilities are misconfigured, attackers might be able to create and run a container that mounts the root folder or spawn a privileged container vulnerable to a container escape attack, which might allow them to escalate privileges and gain further access onto the host file system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Domain: Container], [Data Source: Elastic Defend] |8.3.0 |5
+|<<potential-privilege-escalation-via-container-misconfiguration, Potential Privilege Escalation via Container Misconfiguration>> |This rule monitors for the execution of processes that interact with Linux containers through an interactive shell without root permissions. Utilities such as runc and ctr are universal command-line utilities leveraged to interact with containers via root permissions. On systems where the access to these utilities are misconfigured, attackers might be able to create and run a container that mounts the root folder or spawn a privileged container vulnerable to a container escape attack, which might allow them to escalate privileges and gain further access onto the host file system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Domain: Container], [Data Source: Elastic Defend] |None |5
 
 |<<potential-privilege-escalation-via-enlightenment, Potential Privilege Escalation via Enlightenment>> |Identifies an attempt to exploit a local privilege escalation CVE-2022-37706 via a flaw in Linux window manager package Enlightenment. enlightenment_sys in Enlightenment before 0.25.4 allows local users to gain privileges because it is setuid root, and the system library function mishandles pathnames that begin with a /dev/.. substring. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.11.0 |2
 
-|<<potential-privilege-escalation-via-installerfiletakeover, Potential Privilege Escalation via InstallerFileTakeOver>> |Identifies a potential exploitation of InstallerTakeOver (CVE-2021-41379) default PoC execution. Successful exploitation allows an unprivileged user to escalate privileges to SYSTEM. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |111
+|<<potential-privilege-escalation-via-installerfiletakeover, Potential Privilege Escalation via InstallerFileTakeOver>> |Identifies a potential exploitation of InstallerTakeOver (CVE-2021-41379) default PoC execution. Successful exploitation allows an unprivileged user to escalate privileges to SYSTEM. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |111
 
 |<<potential-privilege-escalation-via-linux-dac-permissions, Potential Privilege Escalation via Linux DAC permissions>> |Identifies potential privilege escalation exploitation of DAC (Discretionary access control) file permissions. The rule identifies exploitation of DAC checks on sensitive file paths via suspicious processes whose capabilities include CAP_DAC_OVERRIDE (where a process can bypass all read write and execution checks) or CAP_DAC_READ_SEARCH (where a process can read any file or perform any executable permission on the directories). |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.11.0 |2
 
-|<<potential-privilege-escalation-via-overlayfs, Potential Privilege Escalation via OverlayFS>> |Identifies an attempt to exploit a local privilege escalation (CVE-2023-2640 and CVE-2023-32629) via a flaw in Ubuntu's modifications to OverlayFS. These flaws allow the creation of specialized executables, which, upon execution, grant the ability to escalate privileges to root on the affected machine. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |5
+|<<potential-privilege-escalation-via-overlayfs, Potential Privilege Escalation via OverlayFS>> |Identifies an attempt to exploit a local privilege escalation (CVE-2023-2640 and CVE-2023-32629) via a flaw in Ubuntu's modifications to OverlayFS. These flaws allow the creation of specialized executables, which, upon execution, grant the ability to escalate privileges to root on the affected machine. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |5
 
-|<<potential-privilege-escalation-via-pkexec, Potential Privilege Escalation via PKEXEC>> |Identifies an attempt to exploit a local privilege escalation in polkit pkexec (CVE-2021-4034) via unsecure environment variable injection. Successful exploitation allows an unprivileged user to escalate to the root user. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |108
+|<<potential-privilege-escalation-via-pkexec, Potential Privilege Escalation via PKEXEC>> |Identifies an attempt to exploit a local privilege escalation in polkit pkexec (CVE-2021-4034) via unsecure environment variable injection. Successful exploitation allows an unprivileged user to escalate to the root user. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |108
 
-|<<potential-privilege-escalation-via-python-cap-setuid, Potential Privilege Escalation via Python cap_setuid>> |This detection rule monitors for the execution of a system command with setuid or setgid capabilities via Python, followed by a uid or gid change to the root user. This sequence of events may indicate successful privilege escalation. Setuid (Set User ID) and setgid (Set Group ID) are Unix-like OS features that enable processes to run with elevated privileges, based on the file owner or group. Threat actors can exploit these attributes to escalate privileges to the privileges that are set on the binary that is being executed. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |3
+|<<potential-privilege-escalation-via-python-cap-setuid, Potential Privilege Escalation via Python cap_setuid>> |This detection rule monitors for the execution of a system command with setuid or setgid capabilities via Python, followed by a uid or gid change to the root user. This sequence of events may indicate successful privilege escalation. Setuid (Set User ID) and setgid (Set Group ID) are Unix-like OS features that enable processes to run with elevated privileges, based on the file owner or group. Threat actors can exploit these attributes to escalate privileges to the privileges that are set on the binary that is being executed. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |3
 
-|<<potential-privilege-escalation-via-recently-compiled-executable, Potential Privilege Escalation via Recently Compiled Executable>> |This rule monitors a sequence involving a program compilation event followed by its execution and a subsequent alteration of UID permissions to root privileges. This behavior can potentially indicate the execution of a kernel or software privilege escalation exploit. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |4
+|<<potential-privilege-escalation-via-recently-compiled-executable, Potential Privilege Escalation via Recently Compiled Executable>> |This rule monitors a sequence involving a program compilation event followed by its execution and a subsequent alteration of UID permissions to root privileges. This behavior can potentially indicate the execution of a kernel or software privilege escalation exploit. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |4
 
-|<<potential-privilege-escalation-via-sudoers-file-modification, Potential Privilege Escalation via Sudoers File Modification>> |A sudoers file specifies the commands users or groups can run and from which terminals. Adversaries can take advantage of these configurations to execute commands as other users or spawn processes with higher privileges. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |103
+|<<potential-privilege-escalation-via-sudoers-file-modification, Potential Privilege Escalation via Sudoers File Modification>> |A sudoers file specifies the commands users or groups can run and from which terminals. Adversaries can take advantage of these configurations to execute commands as other users or spawn processes with higher privileges. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |103
 
-|<<potential-privilege-escalation-via-uid-int-max-bug-detected, Potential Privilege Escalation via UID INT_MAX Bug Detected>> |This rule monitors for the execution of the systemd-run command by a user with a UID that is larger than the maximum allowed UID size (INT_MAX). Some older Linux versions were affected by a bug which allows user accounts with a UID greater than INT_MAX to escalate privileges by spawning a shell through systemd-run. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |5
+|<<potential-privilege-escalation-via-uid-int-max-bug-detected, Potential Privilege Escalation via UID INT_MAX Bug Detected>> |This rule monitors for the execution of the systemd-run command by a user with a UID that is larger than the maximum allowed UID size (INT_MAX). Some older Linux versions were affected by a bug which allows user accounts with a UID greater than INT_MAX to escalate privileges by spawning a shell through systemd-run. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |5
 
-|<<potential-privileged-escalation-via-samaccountname-spoofing, Potential Privileged Escalation via SamAccountName Spoofing>> |Identifies a suspicious computer account name rename event, which may indicate an attempt to exploit CVE-2021-42278 to elevate privileges from a standard domain user to a user with domain admin privileges. CVE-2021-42278 is a security vulnerability that allows potential attackers to impersonate a domain controller via samAccountName attribute spoofing. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Use Case: Vulnerability] |8.3.0 |108
+|<<potential-privileged-escalation-via-samaccountname-spoofing, Potential Privileged Escalation via SamAccountName Spoofing>> |Identifies a suspicious computer account name rename event, which may indicate an attempt to exploit CVE-2021-42278 to elevate privileges from a standard domain user to a user with domain admin privileges. CVE-2021-42278 is a security vulnerability that allows potential attackers to impersonate a domain controller via samAccountName attribute spoofing. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Use Case: Vulnerability] |None |108
 
-|<<potential-process-injection-from-malicious-document, Potential Process Injection from Malicious Document>> |Identifies child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, Excel) with unusual process arguments and path. This behavior is often observed during exploitation of Office applications or from documents with malicious macros. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |2
+|<<potential-process-injection-from-malicious-document, Potential Process Injection from Malicious Document>> |Identifies child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, Excel) with unusual process arguments and path. This behavior is often observed during exploitation of Office applications or from documents with malicious macros. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Tactic: Initial Access], [Rule Type: BBR], [Data Source: Elastic Defend] |None |2
 
-|<<potential-process-injection-via-powershell, Potential Process Injection via PowerShell>> |Detects the use of Windows API functions that are commonly abused by malware and security tools to load malicious code or inject it into remote processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |110
+|<<potential-process-injection-via-powershell, Potential Process Injection via PowerShell>> |Detects the use of Windows API functions that are commonly abused by malware and security tools to load malicious code or inject it into remote processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |110
 
-|<<potential-protocol-tunneling-via-chisel-client, Potential Protocol Tunneling via Chisel Client>> |This rule monitors for common command line flags leveraged by the Chisel client utility followed by a connection attempt. Chisel is a command-line utility used for creating and managing TCP and UDP tunnels, enabling port forwarding and secure communication between machines. Attackers can abuse the Chisel utility to establish covert communication channels, bypass network restrictions, and carry out malicious activities by creating tunnels that allow unauthorized access to internal systems. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |8.3.0 |5
+|<<potential-protocol-tunneling-via-chisel-client, Potential Protocol Tunneling via Chisel Client>> |This rule monitors for common command line flags leveraged by the Chisel client utility followed by a connection attempt. Chisel is a command-line utility used for creating and managing TCP and UDP tunnels, enabling port forwarding and secure communication between machines. Attackers can abuse the Chisel utility to establish covert communication channels, bypass network restrictions, and carry out malicious activities by creating tunnels that allow unauthorized access to internal systems. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |None |5
 
-|<<potential-protocol-tunneling-via-chisel-server, Potential Protocol Tunneling via Chisel Server>> |This rule monitors for common command line flags leveraged by the Chisel server utility followed by a received connection within a timespan of 1 minute. Chisel is a command-line utility used for creating and managing TCP and UDP tunnels, enabling port forwarding and secure communication between machines. Attackers can abuse the Chisel utility to establish covert communication channels, bypass network restrictions, and carry out malicious activities by creating tunnels that allow unauthorized access to internal systems. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |8.3.0 |6
+|<<potential-protocol-tunneling-via-chisel-server, Potential Protocol Tunneling via Chisel Server>> |This rule monitors for common command line flags leveraged by the Chisel server utility followed by a received connection within a timespan of 1 minute. Chisel is a command-line utility used for creating and managing TCP and UDP tunnels, enabling port forwarding and secure communication between machines. Attackers can abuse the Chisel utility to establish covert communication channels, bypass network restrictions, and carry out malicious activities by creating tunnels that allow unauthorized access to internal systems. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend] |None |6
 
-|<<potential-protocol-tunneling-via-earthworm, Potential Protocol Tunneling via EarthWorm>> |Identifies the execution of the EarthWorm tunneler. Adversaries may tunnel network communications to and from a victim system within a separate protocol to avoid detection and network filtering, or to enable access to otherwise unreachable systems. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<potential-protocol-tunneling-via-earthworm, Potential Protocol Tunneling via EarthWorm>> |Identifies the execution of the EarthWorm tunneler. Adversaries may tunnel network communications to and from a victim system within a separate protocol to avoid detection and network filtering, or to enable access to otherwise unreachable systems. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<potential-pspy-process-monitoring-detected, Potential Pspy Process Monitoring Detected>> |This rule leverages auditd to monitor for processes scanning different processes within the /proc directory using the openat syscall. This is a strong indication for the usage of the pspy utility. Attackers may leverage the pspy process monitoring utility to monitor system processes without requiring root permissions, in order to find potential privilege escalation vectors. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery] |8.3.0 |7
+|<<potential-pspy-process-monitoring-detected, Potential Pspy Process Monitoring Detected>> |This rule leverages auditd to monitor for processes scanning different processes within the /proc directory using the openat syscall. This is a strong indication for the usage of the pspy utility. Attackers may leverage the pspy process monitoring utility to monitor system processes without requiring root permissions, in order to find potential privilege escalation vectors. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery] |None |7
 
-|<<potential-ransomware-behavior-high-count-of-readme-files-by-system, Potential Ransomware Behavior - High count of Readme files by System>> |This rule identifies a high number (20) of file creation event by the System virtual process from the same host and with same file name containing keywords similar to ransomware note files and all within a short time period. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |1
+|<<potential-ransomware-behavior-high-count-of-readme-files-by-system, Potential Ransomware Behavior - High count of Readme files by System>> |This rule identifies a high number (20) of file creation event by the System virtual process from the same host and with same file name containing keywords similar to ransomware note files and all within a short time period. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |2
 
-|<<potential-ransomware-note-file-dropped-via-smb, Potential Ransomware Note File Dropped via SMB>> |Identifies an incoming SMB connection followed by the creation of a file with a name similar to ransomware note files. This may indicate a remote ransomware attack via the SMB protocol. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |1
+|<<potential-ransomware-note-file-dropped-via-smb, Potential Ransomware Note File Dropped via SMB>> |Identifies an incoming SMB connection followed by the creation of a file with a name similar to ransomware note files. This may indicate a remote ransomware attack via the SMB protocol. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |2
 
-|<<potential-remote-code-execution-via-web-server, Potential Remote Code Execution via Web Server>> |Identifies suspicious commands executed via a web server, which may suggest a vulnerability and remote shell access. Attackers may exploit a vulnerability in a web application to execute commands via a web server, or place a backdoor file that can be abused to gain code execution as a mechanism for persistence. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |7
+|<<potential-remote-code-execution-via-web-server, Potential Remote Code Execution via Web Server>> |Identifies suspicious commands executed via a web server, which may suggest a vulnerability and remote shell access. Attackers may exploit a vulnerability in a web application to execute commands via a web server, or place a backdoor file that can be abused to gain code execution as a mechanism for persistence. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |7
 
-|<<potential-remote-credential-access-via-registry, Potential Remote Credential Access via Registry>> |Identifies remote access to the registry to potentially dump credential data from the Security Account Manager (SAM) registry hive in preparation for credential access and privileges elevation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |111
+|<<potential-remote-credential-access-via-registry, Potential Remote Credential Access via Registry>> |Identifies remote access to the registry to potentially dump credential data from the Security Account Manager (SAM) registry hive in preparation for credential access and privileges elevation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |111
 
-|<<potential-remote-desktop-shadowing-activity, Potential Remote Desktop Shadowing Activity>> |Identifies the modification of the Remote Desktop Protocol (RDP) Shadow registry or the execution of processes indicative of an active RDP shadowing session. An adversary may abuse the RDP Shadowing feature to spy on or control other users active RDP sessions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<potential-remote-desktop-shadowing-activity, Potential Remote Desktop Shadowing Activity>> |Identifies the modification of the Remote Desktop Protocol (RDP) Shadow registry or the execution of processes indicative of an active RDP shadowing session. An adversary may abuse the RDP Shadowing feature to spy on or control other users active RDP sessions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<potential-remote-desktop-tunneling-detected, Potential Remote Desktop Tunneling Detected>> |Identifies potential use of an SSH utility to establish RDP over a reverse SSH Tunnel. This can be used by attackers to enable routing of network packets that would otherwise not reach their intended destination. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<potential-remote-desktop-tunneling-detected, Potential Remote Desktop Tunneling Detected>> |Identifies potential use of an SSH utility to establish RDP over a reverse SSH Tunnel. This can be used by attackers to enable routing of network packets that would otherwise not reach their intended destination. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne] |8.11.0 |212
 
-|<<potential-remote-file-execution-via-msiexec, Potential Remote File Execution via MSIEXEC>> |Identifies the execution of the built-in Windows Installer, msiexec.exe, to install a remote package. Adversaries may abuse msiexec.exe to launch local or network accessible MSI files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |3
+|<<potential-remote-file-execution-via-msiexec, Potential Remote File Execution via MSIEXEC>> |Identifies the execution of the built-in Windows Installer, msiexec.exe, to install a remote package. Adversaries may abuse msiexec.exe to launch local or network accessible MSI files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |3
 
-|<<potential-reverse-shell, Potential Reverse Shell>> |This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a parent-child relationship where a network event is followed by the creation of a shell process. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |8
+|<<potential-reverse-shell, Potential Reverse Shell>> |This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a parent-child relationship where a network event is followed by the creation of a shell process. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |9
 
-|<<potential-reverse-shell-activity-via-terminal, Potential Reverse Shell Activity via Terminal>> |Identifies the execution of a shell process with suspicious arguments which may be indicative of reverse shell activity. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |108
+|<<potential-reverse-shell-activity-via-terminal, Potential Reverse Shell Activity via Terminal>> |Identifies the execution of a shell process with suspicious arguments which may be indicative of reverse shell activity. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |108
 
-|<<potential-reverse-shell-via-background-process, Potential Reverse Shell via Background Process>> |Monitors for the execution of background processes with process arguments capable of opening a socket in the /dev/tcp channel. This may indicate the creation of a backdoor reverse connection, and should be investigated further. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |4
+|<<potential-reverse-shell-via-background-process, Potential Reverse Shell via Background Process>> |Monitors for the execution of background processes with process arguments capable of opening a socket in the /dev/tcp channel. This may indicate the creation of a backdoor reverse connection, and should be investigated further. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |4
 
-|<<potential-reverse-shell-via-child, Potential Reverse Shell via Child>> |This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a network event that is followed by the creation of a shell process with suspicious command line arguments. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |2
+|<<potential-reverse-shell-via-child, Potential Reverse Shell via Child>> |This detection rule identifies suspicious network traffic patterns associated with TCP reverse shell activity. This activity consists of a network event that is followed by the creation of a shell process with suspicious command line arguments. An attacker may establish a Linux TCP reverse shell to gain remote access to a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |3
 
-|<<potential-reverse-shell-via-java, Potential Reverse Shell via Java>> |This detection rule identifies the execution of a Linux shell process from a Java JAR application post an incoming network connection. This behavior may indicate reverse shell activity via a Java application. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |8
+|<<potential-reverse-shell-via-java, Potential Reverse Shell via Java>> |This detection rule identifies the execution of a Linux shell process from a Java JAR application post an incoming network connection. This behavior may indicate reverse shell activity via a Java application. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |8
 
-|<<potential-reverse-shell-via-suspicious-binary, Potential Reverse Shell via Suspicious Binary>> |This detection rule detects the creation of a shell through a chain consisting of the execution of a suspicious binary (located in a commonly abused location or executed manually) followed by a network event and ending with a shell being spawned. Stageless reverse tcp shells display this behaviour. Attackers may spawn reverse shells to establish persistence onto a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |7
+|<<potential-reverse-shell-via-suspicious-binary, Potential Reverse Shell via Suspicious Binary>> |This detection rule detects the creation of a shell through a chain consisting of the execution of a suspicious binary (located in a commonly abused location or executed manually) followed by a network event and ending with a shell being spawned. Stageless reverse tcp shells display this behaviour. Attackers may spawn reverse shells to establish persistence onto a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |7
 
-|<<potential-reverse-shell-via-suspicious-child-process, Potential Reverse Shell via Suspicious Child Process>> |This detection rule detects the creation of a shell through a suspicious process chain. Any reverse shells spawned by the specified utilities that are initialized from a single process followed by a network connection attempt will be captured through this rule. Attackers may spawn reverse shells to establish persistence onto a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |9
+|<<potential-reverse-shell-via-suspicious-child-process, Potential Reverse Shell via Suspicious Child Process>> |This detection rule detects the creation of a shell through a suspicious process chain. Any reverse shells spawned by the specified utilities that are initialized from a single process followed by a network connection attempt will be captured through this rule. Attackers may spawn reverse shells to establish persistence onto a target system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |9
 
-|<<potential-reverse-shell-via-udp, Potential Reverse Shell via UDP>> |This detection rule identifies suspicious network traffic patterns associated with UDP reverse shell activity. This activity consists of a sample of an execve, socket and connect syscall executed by the same process, where the auditd.data.a0-1 indicate a UDP connection, ending with an egress connection event. An attacker may establish a Linux UDP reverse shell to bypass traditional firewall restrictions and gain remote access to a target system covertly. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |8.6.0 |6
+|<<potential-reverse-shell-via-udp, Potential Reverse Shell via UDP>> |This detection rule identifies suspicious network traffic patterns associated with UDP reverse shell activity. This activity consists of a sample of an execve, socket and connect syscall executed by the same process, where the auditd.data.a0-1 indicate a UDP connection, ending with an egress connection event. An attacker may establish a Linux UDP reverse shell to bypass traditional firewall restrictions and gain remote access to a target system covertly. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |None |6
 
-|<<potential-ssh-it-ssh-worm-downloaded, Potential SSH-IT SSH Worm Downloaded>> |Identifies processes that are capable of downloading files with command line arguments containing URLs to SSH-IT's autonomous SSH worm. This worm intercepts outgoing SSH connections every time a user uses ssh. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |3
+|<<potential-ssh-it-ssh-worm-downloaded, Potential SSH-IT SSH Worm Downloaded>> |Identifies processes that are capable of downloading files with command line arguments containing URLs to SSH-IT's autonomous SSH worm. This worm intercepts outgoing SSH connections every time a user uses ssh. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |3
 
-|<<potential-syn-based-network-scan-detected, Potential SYN-Based Network Scan Detected>> |This rule identifies a potential SYN-Based port scan. A SYN port scan is a technique employed by attackers to scan a target network for open ports by sending SYN packets to multiple ports and observing the response. Attackers use this method to identify potential entry points or services that may be vulnerable to exploitation, allowing them to launch targeted attacks or gain unauthorized access to the system or network, compromising its security and potentially leading to data breaches or further malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination ports using 2 or less packets per port. |[Domain: Network], [Tactic: Discovery], [Tactic: Reconnaissance], [Use Case: Network Security Monitoring] |8.3.0 |5
+|<<potential-syn-based-network-scan-detected, Potential SYN-Based Network Scan Detected>> |This rule identifies a potential SYN-Based port scan. A SYN port scan is a technique employed by attackers to scan a target network for open ports by sending SYN packets to multiple ports and observing the response. Attackers use this method to identify potential entry points or services that may be vulnerable to exploitation, allowing them to launch targeted attacks or gain unauthorized access to the system or network, compromising its security and potentially leading to data breaches or further malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination ports using 2 or less packets per port. |[Domain: Network], [Tactic: Discovery], [Tactic: Reconnaissance], [Use Case: Network Security Monitoring] |None |5
 
-|<<potential-secure-file-deletion-via-sdelete-utility, Potential Secure File Deletion via SDelete Utility>> |Detects file name patterns generated by the use of Sysinternals SDelete utility to securely delete a file via multiple file overwrite and rename operations. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Impact], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<potential-secure-file-deletion-via-sdelete-utility, Potential Secure File Deletion via SDelete Utility>> |Detects file name patterns generated by the use of Sysinternals SDelete utility to securely delete a file via multiple file overwrite and rename operations. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Impact], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<potential-shadow-credentials-added-to-ad-object, Potential Shadow Credentials added to AD Object>> |Identify the modification of the msDS-KeyCredentialLink attribute in an Active Directory Computer or User Object. Attackers can abuse control over the object and create a key pair, append to raw public key in the attribute, and obtain persistent and stealthy access to the target user or computer object. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |8.3.0 |108
+|<<potential-shadow-credentials-added-to-ad-object, Potential Shadow Credentials added to AD Object>> |Identify the modification of the msDS-KeyCredentialLink attribute in an Active Directory Computer or User Object. Attackers can abuse control over the object and create a key pair, append to raw public key in the attribute, and obtain persistent and stealthy access to the target user or computer object. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |None |108
 
-|<<potential-shadow-file-read-via-command-line-utilities, Potential Shadow File Read via Command Line Utilities>> |Identifies access to the /etc/shadow file via the commandline using standard system utilities. After elevating privileges to root, threat actors may attempt to read or dump this file in order to gain valid credentials. They may utilize these to move laterally undetected and access additional resources. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |208
+|<<potential-shadow-file-read-via-command-line-utilities, Potential Shadow File Read via Command Line Utilities>> |Identifies access to the /etc/shadow file via the commandline using standard system utilities. After elevating privileges to root, threat actors may attempt to read or dump this file in order to gain valid credentials. They may utilize these to move laterally undetected and access additional resources. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |208
 
-|<<potential-sharprdp-behavior, Potential SharpRDP Behavior>> |Identifies potential behavior of SharpRDP, which is a tool that can be used to perform authenticated command execution against a remote target via Remote Desktop Protocol (RDP) for the purposes of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |8.3.0 |106
+|<<potential-sharprdp-behavior, Potential SharpRDP Behavior>> |Identifies potential behavior of SharpRDP, which is a tool that can be used to perform authenticated command execution against a remote target via Remote Desktop Protocol (RDP) for the purposes of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |None |106
 
-|<<potential-shell-via-wildcard-injection-detected, Potential Shell via Wildcard Injection Detected>> |This rule monitors for the execution of a set of linux binaries, that are potentially vulnerable to wildcard injection, with suspicious command line flags followed by a shell spawn event. Linux wildcard injection is a type of security vulnerability where attackers manipulate commands or input containing wildcards (e.g., *, ?, []) to execute unintended operations or access sensitive data by tricking the system into interpreting the wildcard characters in unexpected ways. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |5
+|<<potential-shell-via-wildcard-injection-detected, Potential Shell via Wildcard Injection Detected>> |This rule monitors for the execution of a set of linux binaries, that are potentially vulnerable to wildcard injection, with suspicious command line flags followed by a shell spawn event. Linux wildcard injection is a type of security vulnerability where attackers manipulate commands or input containing wildcards (e.g., *, ?, []) to execute unintended operations or access sensitive data by tricking the system into interpreting the wildcard characters in unexpected ways. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Execution], [Data Source: Elastic Defend] |None |5
 
-|<<potential-successful-linux-ftp-brute-force-attack-detected, Potential Successful Linux FTP Brute Force Attack Detected>> |An FTP (file transfer protocol) brute force attack is a method where an attacker systematically tries different combinations of usernames and passwords to gain unauthorized access to an FTP server, and if successful, the impact can include unauthorized data access, manipulation, or theft, compromising the security and integrity of the server and potentially exposing sensitive information. This rule identifies multiple consecutive authentication failures targeting a specific user account from the same source address and within a short time interval, followed by a successful authentication. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |8.3.0 |7
+|<<potential-successful-linux-ftp-brute-force-attack-detected, Potential Successful Linux FTP Brute Force Attack Detected>> |An FTP (file transfer protocol) brute force attack is a method where an attacker systematically tries different combinations of usernames and passwords to gain unauthorized access to an FTP server, and if successful, the impact can include unauthorized data access, manipulation, or theft, compromising the security and integrity of the server and potentially exposing sensitive information. This rule identifies multiple consecutive authentication failures targeting a specific user account from the same source address and within a short time interval, followed by a successful authentication. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |None |7
 
-|<<potential-successful-linux-rdp-brute-force-attack-detected, Potential Successful Linux RDP Brute Force Attack Detected>> |An RDP (Remote Desktop Protocol) brute force attack involves an attacker repeatedly attempting various username and password combinations to gain unauthorized access to a remote computer via RDP, and if successful, the potential impact can include unauthorized control over the compromised system, data theft, or the ability to launch further attacks within the network, jeopardizing the security and confidentiality of the targeted system and potentially compromising the entire network infrastructure. This rule identifies multiple consecutive authentication failures targeting a specific user account within a short time interval, followed by a successful authentication. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |8.3.0 |7
+|<<potential-successful-linux-rdp-brute-force-attack-detected, Potential Successful Linux RDP Brute Force Attack Detected>> |An RDP (Remote Desktop Protocol) brute force attack involves an attacker repeatedly attempting various username and password combinations to gain unauthorized access to a remote computer via RDP, and if successful, the potential impact can include unauthorized control over the compromised system, data theft, or the ability to launch further attacks within the network, jeopardizing the security and confidentiality of the targeted system and potentially compromising the entire network infrastructure. This rule identifies multiple consecutive authentication failures targeting a specific user account within a short time interval, followed by a successful authentication. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |None |7
 
-|<<potential-successful-ssh-brute-force-attack, Potential Successful SSH Brute Force Attack>> |Identifies multiple SSH login failures followed by a successful one from the same source address. Adversaries can attempt to login into multiple users with a common or known password to gain access to accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |8.3.0 |11
+|<<potential-successful-ssh-brute-force-attack, Potential Successful SSH Brute Force Attack>> |Identifies multiple SSH login failures followed by a successful one from the same source address. Adversaries can attempt to login into multiple users with a common or known password to gain access to accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |None |11
 
-|<<potential-sudo-hijacking-detected, Potential Sudo Hijacking Detected>> |Identifies the creation of a sudo binary located at /usr/bin/sudo. Attackers may hijack the default sudo binary and replace it with a custom binary or script that can read the user's password in clear text to escalate privileges or enable persistence onto the system every time the sudo binary is executed. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |105
+|<<potential-sudo-hijacking-detected, Potential Sudo Hijacking Detected>> |Identifies the creation of a sudo binary located at /usr/bin/sudo. Attackers may hijack the default sudo binary and replace it with a custom binary or script that can read the user's password in clear text to escalate privileges or enable persistence onto the system every time the sudo binary is executed. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |105
 
-|<<potential-sudo-privilege-escalation-via-cve-2019-14287, Potential Sudo Privilege Escalation via CVE-2019-14287>> |This rule monitors for the execution of a suspicious sudo command that is leveraged in CVE-2019-14287 to escalate privileges to root. Sudo does not verify the presence of the designated user ID and proceeds to execute using a user ID that can be chosen arbitrarily. By using the sudo privileges, the command "sudo -u#-1" translates to an ID of 0, representing the root user. This exploit may work for sudo versions prior to v1.28. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Use Case: Vulnerability], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |4
+|<<potential-sudo-privilege-escalation-via-cve-2019-14287, Potential Sudo Privilege Escalation via CVE-2019-14287>> |This rule monitors for the execution of a suspicious sudo command that is leveraged in CVE-2019-14287 to escalate privileges to root. Sudo does not verify the presence of the designated user ID and proceeds to execute using a user ID that can be chosen arbitrarily. By using the sudo privileges, the command "sudo -u#-1" translates to an ID of 0, representing the root user. This exploit may work for sudo versions prior to v1.28. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Use Case: Vulnerability], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |4
 
-|<<potential-sudo-token-manipulation-via-process-injection, Potential Sudo Token Manipulation via Process Injection>> |This rule detects potential sudo token manipulation attacks through process injection by monitoring the use of a debugger (gdb) process followed by a successful uid change event during the execution of the sudo process. A sudo token manipulation attack is performed by injecting into a process that has a valid sudo token, which can then be used by attackers to activate their own sudo token. This attack requires ptrace to be enabled in conjunction with the existence of a living process that has a valid sudo token with the same uid as the current user. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |5
+|<<potential-sudo-token-manipulation-via-process-injection, Potential Sudo Token Manipulation via Process Injection>> |This rule detects potential sudo token manipulation attacks through process injection by monitoring the use of a debugger (gdb) process followed by a successful uid change event during the execution of the sudo process. A sudo token manipulation attack is performed by injecting into a process that has a valid sudo token, which can then be used by attackers to activate their own sudo token. This attack requires ptrace to be enabled in conjunction with the existence of a living process that has a valid sudo token with the same uid as the current user. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |5
 
-|<<potential-suspicious-clipboard-activity-detected, Potential Suspicious Clipboard Activity Detected>> |This rule monitors for the usage of the most common clipboard utilities on unix systems by an uncommon process group leader. Adversaries may collect data stored in the clipboard from users copying information within or between applications. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Collection], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.6.0 |4
+|<<potential-suspicious-clipboard-activity-detected, Potential Suspicious Clipboard Activity Detected>> |This rule monitors for the usage of the most common clipboard utilities on unix systems by an uncommon process group leader. Adversaries may collect data stored in the clipboard from users copying information within or between applications. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Collection], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |4
 
-|<<potential-suspicious-debugfs-root-device-access, Potential Suspicious DebugFS Root Device Access>> |This rule monitors for the usage of the built-in Linux DebugFS utility to access a disk device without root permissions. Linux users that are part of the "disk" group have sufficient privileges to access all data inside of the machine through DebugFS. Attackers may leverage DebugFS in conjunction with "disk" permissions to read sensitive files owned by root, such as the shadow file, root ssh private keys or other sensitive files that may allow them to further escalate privileges. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |5
+|<<potential-suspicious-debugfs-root-device-access, Potential Suspicious DebugFS Root Device Access>> |This rule monitors for the usage of the built-in Linux DebugFS utility to access a disk device without root permissions. Linux users that are part of the "disk" group have sufficient privileges to access all data inside of the machine through DebugFS. Attackers may leverage DebugFS in conjunction with "disk" permissions to read sensitive files owned by root, such as the shadow file, root ssh private keys or other sensitive files that may allow them to further escalate privileges. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |5
 
-|<<potential-suspicious-file-edit, Potential Suspicious File Edit>> |This rule monitors for the potential edit of a suspicious file. In Linux, when editing a file through an editor, a temporary .swp file is created. By monitoring for the creation of this .swp file, we can detect potential file edits of suspicious files. The execution of this rule is not a clear sign of the file being edited, as just opening the file through an editor will trigger this event. Attackers may alter any of the files added in this rule to establish persistence, escalate privileges or perform reconnaisance on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |4
+|<<potential-suspicious-file-edit, Potential Suspicious File Edit>> |This rule monitors for the potential edit of a suspicious file. In Linux, when editing a file through an editor, a temporary .swp file is created. By monitoring for the creation of this .swp file, we can detect potential file edits of suspicious files. The execution of this rule is not a clear sign of the file being edited, as just opening the file through an editor will trigger this event. Attackers may alter any of the files added in this rule to establish persistence, escalate privileges or perform reconnaisance on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |5
 
-|<<potential-unauthorized-access-via-wildcard-injection-detected, Potential Unauthorized Access via Wildcard Injection Detected>> |This rule monitors for the execution of the "chown" and "chmod" commands with command line flags that could indicate a wildcard injection attack. Linux wildcard injection is a type of security vulnerability where attackers manipulate commands or input containing wildcards (e.g., *, ?, []) to execute unintended operations or access sensitive data by tricking the system into interpreting the wildcard characters in unexpected ways. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |5
+|<<potential-unauthorized-access-via-wildcard-injection-detected, Potential Unauthorized Access via Wildcard Injection Detected>> |This rule monitors for the execution of the "chown" and "chmod" commands with command line flags that could indicate a wildcard injection attack. Linux wildcard injection is a type of security vulnerability where attackers manipulate commands or input containing wildcards (e.g., *, ?, []) to execute unintended operations or access sensitive data by tricking the system into interpreting the wildcard characters in unexpected ways. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |5
 
-|<<potential-upgrade-of-non-interactive-shell, Potential Upgrade of Non-interactive Shell>> |Identifies when a non-interactive terminal (tty) is being upgraded to a fully interactive shell. Attackers may upgrade a simple reverse shell to a fully interactive tty after obtaining initial access to a host, in order to obtain a more stable connection. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |3
+|<<potential-upgrade-of-non-interactive-shell, Potential Upgrade of Non-interactive Shell>> |Identifies when a non-interactive terminal (tty) is being upgraded to a fully interactive shell. Attackers may upgrade a simple reverse shell to a fully interactive tty after obtaining initial access to a host, in order to obtain a more stable connection. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |3
 
-|<<potential-veeam-credential-access-command, Potential Veeam Credential Access Command>> |Identifies commands that can access and decrypt Veeam credentials stored in MSSQL databases. Attackers can use Veeam Credentials to target backups as part of destructive operations such as Ransomware attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |1
+|<<potential-veeam-credential-access-command, Potential Veeam Credential Access Command>> |Identifies commands that can access and decrypt Veeam credentials stored in MSSQL databases. Attackers can use Veeam Credentials to target backups as part of destructive operations such as Ransomware attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |1
 
-|<<potential-windows-error-manager-masquerading, Potential Windows Error Manager Masquerading>> |Identifies suspicious instances of the Windows Error Reporting process (WerFault.exe or Wermgr.exe) with matching command-line and process executable values performing outgoing network connections. This may be indicative of a masquerading attempt to evade suspicious child process behavior detections. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<potential-windows-error-manager-masquerading, Potential Windows Error Manager Masquerading>> |Identifies suspicious instances of the Windows Error Reporting process (WerFault.exe or Wermgr.exe) with matching command-line and process executable values performing outgoing network connections. This may be indicative of a masquerading attempt to evade suspicious child process behavior detections. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<potential-windows-session-hijacking-via-ccmexec, Potential Windows Session Hijacking via CcmExec>> |This detection rule identifies when 'SCNotification.exe' loads an untrusted DLL, which is a potential indicator of an attacker attempt to hijack/impersonate a Windows user session. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |1
+|<<potential-windows-session-hijacking-via-ccmexec, Potential Windows Session Hijacking via CcmExec>> |This detection rule identifies when 'SCNotification.exe' loads an untrusted DLL, which is a potential indicator of an attacker attempt to hijack/impersonate a Windows user session. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |1
 
-|<<potential-curl-cve-2023-38545-exploitation, Potential curl CVE-2023-38545 Exploitation>> |Detects potential exploitation of curl CVE-2023-38545 by monitoring for vulnerable command line arguments in conjunction with an unusual command line length. A flaw in curl version <= 8.3 makes curl vulnerable to a heap based buffer overflow during the SOCKS5 proxy handshake. Upgrade to curl version >= 8.4 to patch this vulnerability. This exploit can be executed with and without the use of environment variables. For increased visibility, enable the collection of http_proxy, HTTPS_PROXY and ALL_PROXY environment variables based on the instructions provided in the setup guide of this rule. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Use Case: Vulnerability], [Tactic: Execution], [Data Source: Elastic Defend] |8.6.0 |5
+|<<potential-curl-cve-2023-38545-exploitation, Potential curl CVE-2023-38545 Exploitation>> |Detects potential exploitation of curl CVE-2023-38545 by monitoring for vulnerable command line arguments in conjunction with an unusual command line length. A flaw in curl version <= 8.3 makes curl vulnerable to a heap based buffer overflow during the SOCKS5 proxy handshake. Upgrade to curl version >= 8.4 to patch this vulnerability. This exploit can be executed with and without the use of environment variables. For increased visibility, enable the collection of http_proxy, HTTPS_PROXY and ALL_PROXY environment variables based on the instructions provided in the setup guide of this rule. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Use Case: Vulnerability], [Tactic: Execution], [Data Source: Elastic Defend] |None |5
 
-|<<potential-macos-ssh-brute-force-detected, Potential macOS SSH Brute Force Detected>> |Identifies a high number (20) of macOS SSH KeyGen process executions from the same host. An adversary may attempt a brute force attack to obtain unauthorized access to user accounts. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.3.0 |108
+|<<potential-macos-ssh-brute-force-detected, Potential macOS SSH Brute Force Detected>> |Identifies a high number (20) of macOS SSH KeyGen process executions from the same host. An adversary may attempt a brute force attack to obtain unauthorized access to user accounts. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |108
 
-|<<potential-privilege-escalation-via-cve-2022-38028, Potential privilege escalation via CVE-2022-38028>> |Identifies a privilege escalation attempt via exploiting CVE-2022-38028 to hijack the print spooler service execution. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |1
+|<<potential-privilege-escalation-via-cve-2022-38028, Potential privilege escalation via CVE-2022-38028>> |Identifies a privilege escalation attempt via exploiting CVE-2022-38028 to hijack the print spooler service execution. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |1
 
 |<<potentially-successful-mfa-bombing-via-push-notifications, Potentially Successful MFA Bombing via Push Notifications>> |Detects when an attacker abuses the Multi-Factor authentication mechanism by repeatedly issuing login requests until the user eventually accepts the Okta push notification. An adversary may attempt to bypass the Okta MFA policies configured for an organization to obtain unauthorized access. |[Use Case: Identity and Access Audit], [Tactic: Credential Access], [Data Source: Okta] |8.10.0 |209
 
-|<<potentially-suspicious-process-started-via-tmux-or-screen, Potentially Suspicious Process Started via tmux or screen>> |This rule monitors for the execution of suspicious commands via screen and tmux. When launching a command and detaching directly, the commands will be executed in the background via its parent process. Attackers may leverage screen or tmux to execute commands while attempting to evade detection. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |4
+|<<potentially-suspicious-process-started-via-tmux-or-screen, Potentially Suspicious Process Started via tmux or screen>> |This rule monitors for the execution of suspicious commands via screen and tmux. When launching a command and detaching directly, the commands will be executed in the background via its parent process. Attackers may leverage screen or tmux to execute commands while attempting to evade detection. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |4
 
-|<<powershell-invoke-ninjacopy-script, PowerShell Invoke-NinjaCopy script>> |Detects PowerShell scripts that contain the default exported functions used on Invoke-NinjaCopy. Attackers can use Invoke-NinjaCopy to read SYSTEM files that are normally locked, such as the NTDS.dit file or registry hives. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |8.3.0 |5
+|<<powershell-invoke-ninjacopy-script, PowerShell Invoke-NinjaCopy script>> |Detects PowerShell scripts that contain the default exported functions used on Invoke-NinjaCopy. Attackers can use Invoke-NinjaCopy to read SYSTEM files that are normally locked, such as the NTDS.dit file or registry hives. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |None |5
 
-|<<powershell-kerberos-ticket-dump, PowerShell Kerberos Ticket Dump>> |Detects PowerShell scripts that have the capability of dumping Kerberos tickets from LSA, which potentially indicates an attacker's attempt to acquire credentials for lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: PowerShell Logs] |8.3.0 |4
+|<<powershell-kerberos-ticket-dump, PowerShell Kerberos Ticket Dump>> |Detects PowerShell scripts that have the capability of dumping Kerberos tickets from LSA, which potentially indicates an attacker's attempt to acquire credentials for lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: PowerShell Logs] |None |4
 
-|<<powershell-kerberos-ticket-request, PowerShell Kerberos Ticket Request>> |Detects PowerShell scripts that have the capability of requesting kerberos tickets, which is a common step in Kerberoasting toolkits to crack service accounts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |111
+|<<powershell-kerberos-ticket-request, PowerShell Kerberos Ticket Request>> |Detects PowerShell scripts that have the capability of requesting kerberos tickets, which is a common step in Kerberoasting toolkits to crack service accounts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |111
 
-|<<powershell-keylogging-script, PowerShell Keylogging Script>> |Detects the use of Win32 API Functions that can be used to capture user keystrokes in PowerShell scripts. Attackers use this technique to capture user input, looking for credentials and/or other valuable data. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |112
+|<<powershell-keylogging-script, PowerShell Keylogging Script>> |Detects the use of Win32 API Functions that can be used to capture user keystrokes in PowerShell scripts. Attackers use this technique to capture user input, looking for credentials and/or other valuable data. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |112
 
-|<<powershell-mailbox-collection-script, PowerShell Mailbox Collection Script>> |Detects PowerShell scripts that can be used to collect data from mailboxes. Adversaries may target user email to collect sensitive information. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |8.3.0 |7
+|<<powershell-mailbox-collection-script, PowerShell Mailbox Collection Script>> |Detects PowerShell scripts that can be used to collect data from mailboxes. Adversaries may target user email to collect sensitive information. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |None |7
 
-|<<powershell-minidump-script, PowerShell MiniDump Script>> |This rule detects PowerShell scripts capable of dumping process memory using WindowsErrorReporting or Dbghelp.dll MiniDumpWriteDump. Attackers can use this tooling to dump LSASS and get access to credentials. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |108
+|<<powershell-minidump-script, PowerShell MiniDump Script>> |This rule detects PowerShell scripts capable of dumping process memory using WindowsErrorReporting or Dbghelp.dll MiniDumpWriteDump. Attackers can use this tooling to dump LSASS and get access to credentials. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |108
 
 |<<powershell-psreflect-script, PowerShell PSReflect Script>> |Detects the use of PSReflect in PowerShell scripts. Attackers leverage PSReflect as a library that enables PowerShell to access win32 API functions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |110
 
-|<<powershell-script-block-logging-disabled, PowerShell Script Block Logging Disabled>> |Identifies attempts to disable PowerShell Script Block Logging via registry modification. Attackers may disable this logging to conceal their activities in the host and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<powershell-script-block-logging-disabled, PowerShell Script Block Logging Disabled>> |Identifies attempts to disable PowerShell Script Block Logging via registry modification. Attackers may disable this logging to conceal their activities in the host and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
 |<<powershell-script-with-archive-compression-capabilities, PowerShell Script with Archive Compression Capabilities>> |Identifies the use of Cmdlets and methods related to archive compression activities. Adversaries will often compress and encrypt data in preparation for exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs], [Rule Type: BBR] |8.3.0 |5
 
 |<<powershell-script-with-discovery-capabilities, PowerShell Script with Discovery Capabilities>> |Identifies the use of Cmdlets and methods related to discovery activities. Attackers can use these to perform various situational awareness related activities, like enumerating users, shares, sessions, domain trusts, groups, etc. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Discovery], [Data Source: PowerShell Logs], [Rule Type: BBR] |8.3.0 |6
 
-|<<powershell-script-with-encryption-decryption-capabilities, PowerShell Script with Encryption/Decryption Capabilities>> |Identifies the use of Cmdlets and methods related to encryption/decryption of files in PowerShell scripts, which malware and offensive security tools can abuse to encrypt data or decrypt payloads to bypass security solutions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |8.3.0 |6
+|<<powershell-script-with-encryption-decryption-capabilities, PowerShell Script with Encryption/Decryption Capabilities>> |Identifies the use of Cmdlets and methods related to encryption/decryption of files in PowerShell scripts, which malware and offensive security tools can abuse to encrypt data or decrypt payloads to bypass security solutions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |None |6
 
 |<<powershell-script-with-log-clear-capabilities, PowerShell Script with Log Clear Capabilities>> |Identifies the use of Cmdlets and methods related to Windows event log deletion activities. This is often done by attackers in an attempt to evade detection or destroy forensic evidence on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: PowerShell Logs], [Rule Type: BBR] |8.3.0 |5
 
-|<<powershell-script-with-password-policy-discovery-capabilities, PowerShell Script with Password Policy Discovery Capabilities>> |Identifies the use of Cmdlets and methods related to remote execution activities using WinRM. Attackers can abuse WinRM to perform lateral movement using built-in tools. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Execution], [Data Source: PowerShell Logs], [Rule Type: BBR] |8.3.0 |5
+|<<powershell-script-with-password-policy-discovery-capabilities, PowerShell Script with Password Policy Discovery Capabilities>> |Identifies the use of Cmdlets and methods related to remote execution activities using WinRM. Attackers can abuse WinRM to perform lateral movement using built-in tools. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Execution], [Data Source: PowerShell Logs], [Rule Type: BBR] |None |5
 
 |<<powershell-script-with-remote-execution-capabilities-via-winrm, PowerShell Script with Remote Execution Capabilities via WinRM>> |Identifies the use of Cmdlets and methods related to remote execution activities using WinRM. Attackers can abuse WinRM to perform lateral movement using built-in tools. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Execution], [Data Source: PowerShell Logs], [Rule Type: BBR] |8.3.0 |6
 
-|<<powershell-script-with-token-impersonation-capabilities, PowerShell Script with Token Impersonation Capabilities>> |Detects scripts that contain PowerShell functions, structures, or Windows API functions related to token impersonation/theft. Attackers may duplicate then impersonate another user's token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: PowerShell Logs] |8.3.0 |11
+|<<powershell-script-with-token-impersonation-capabilities, PowerShell Script with Token Impersonation Capabilities>> |Detects scripts that contain PowerShell functions, structures, or Windows API functions related to token impersonation/theft. Attackers may duplicate then impersonate another user's token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: PowerShell Logs] |None |11
 
-|<<powershell-script-with-veeam-credential-access-capabilities, PowerShell Script with Veeam Credential Access Capabilities>> |Identifies PowerShell scripts that can access and decrypt Veeam credentials stored in MSSQL databases. Attackers can use Veeam Credentials to target backups as part of destructive operations such as Ransomware attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: PowerShell Logs] |8.3.0 |1
+|<<powershell-script-with-veeam-credential-access-capabilities, PowerShell Script with Veeam Credential Access Capabilities>> |Identifies PowerShell scripts that can access and decrypt Veeam credentials stored in MSSQL databases. Attackers can use Veeam Credentials to target backups as part of destructive operations such as Ransomware attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: PowerShell Logs] |None |1
 
-|<<powershell-script-with-webcam-video-capture-capabilities, PowerShell Script with Webcam Video Capture Capabilities>> |Detects PowerShell scripts that can be used to record webcam video. Attackers can capture this information to extort or spy on victims. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs] |8.3.0 |4
+|<<powershell-script-with-webcam-video-capture-capabilities, PowerShell Script with Webcam Video Capture Capabilities>> |Detects PowerShell scripts that can be used to record webcam video. Attackers can capture this information to extort or spy on victims. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs] |None |4
 
-|<<powershell-share-enumeration-script, PowerShell Share Enumeration Script>> |Detects scripts that contain PowerShell functions, structures, or Windows API functions related to windows share enumeration activities. Attackers, mainly ransomware groups, commonly identify and inspect network shares, looking for critical information for encryption and/or exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |9
+|<<powershell-share-enumeration-script, PowerShell Share Enumeration Script>> |Detects scripts that contain PowerShell functions, structures, or Windows API functions related to windows share enumeration activities. Attackers, mainly ransomware groups, commonly identify and inspect network shares, looking for critical information for encryption and/or exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |9
 
 |<<powershell-suspicious-discovery-related-windows-api-functions, PowerShell Suspicious Discovery Related Windows API Functions>> |This rule detects the use of discovery-related Windows API functions in PowerShell Scripts. Attackers can use these functions to perform various situational awareness related activities, like enumerating users, shares, sessions, domain trusts, groups, etc. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |113
 
 |<<powershell-suspicious-payload-encoded-and-compressed, PowerShell Suspicious Payload Encoded and Compressed>> |Identifies the use of .NET functionality for decompression and base64 decoding combined in PowerShell scripts, which malware and security tools heavily use to deobfuscate payloads and load them directly in memory to bypass defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |111
 
-|<<powershell-suspicious-script-with-audio-capture-capabilities, PowerShell Suspicious Script with Audio Capture Capabilities>> |Detects PowerShell scripts that can record audio, a common feature in popular post-exploitation tooling. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |110
+|<<powershell-suspicious-script-with-audio-capture-capabilities, PowerShell Suspicious Script with Audio Capture Capabilities>> |Detects PowerShell scripts that can record audio, a common feature in popular post-exploitation tooling. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |110
 
 |<<powershell-suspicious-script-with-clipboard-retrieval-capabilities, PowerShell Suspicious Script with Clipboard Retrieval Capabilities>> |Detects PowerShell scripts that can get the contents of the clipboard, which attackers can abuse to retrieve sensitive information like credentials, messages, etc. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: PowerShell Logs], [Resources: Investigation Guide] |8.3.0 |8
 
-|<<powershell-suspicious-script-with-screenshot-capabilities, PowerShell Suspicious Script with Screenshot Capabilities>> |Detects PowerShell scripts that can take screenshots, which is a common feature in post-exploitation kits and remote access tools (RATs). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |108
+|<<powershell-suspicious-script-with-screenshot-capabilities, PowerShell Suspicious Script with Screenshot Capabilities>> |Detects PowerShell scripts that can take screenshots, which is a common feature in post-exploitation kits and remote access tools (RATs). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |108
 
 |<<privilege-escalation-via-cap-chown-cap-fowner-capabilities, Privilege Escalation via CAP_CHOWN/CAP_FOWNER Capabilities>> |Identifies instances where a processes (granted CAP_CHOWN and/or CAP_FOWNER capabilities) is executed, after which the ownership of a suspicious file or binary is changed. In Linux, the CAP_CHOWN capability allows a process to change the owner of a file, while CAP_FOWNER permits it to bypass permission checks on operations that require file ownership (like reading, writing, and executing). Attackers may abuse these capabilities to obtain unauthorized access to files. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.11.0 |3
 
@@ -1484,746 +1490,750 @@ and their rule type is `machine_learning`.
 
 |<<privilege-escalation-via-gdb-cap-sys-ptrace, Privilege Escalation via GDB CAP_SYS_PTRACE>> |Identifies instances where GDB (granted the CAP_SYS_PTRACE capability) is executed, after which the user's access is elevated to UID/GID 0 (root). In Linux, the CAP_SYS_PTRACE capability grants a process the ability to use the ptrace system call, which is typically used for debugging and allows the process to trace and control other processes. Attackers may leverage this capability to hook and inject into a process that is running with root permissions in order to escalate their privileges to root. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.11.0 |2
 
-|<<privilege-escalation-via-named-pipe-impersonation, Privilege Escalation via Named Pipe Impersonation>> |Identifies a privilege escalation attempt via named pipe impersonation. An adversary may abuse this technique by utilizing a framework such Metasploit's meterpreter getsystem command. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<privilege-escalation-via-named-pipe-impersonation, Privilege Escalation via Named Pipe Impersonation>> |Identifies a privilege escalation attempt via named pipe impersonation. An adversary may abuse this technique by utilizing a framework such Metasploit's meterpreter getsystem command. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<privilege-escalation-via-rogue-named-pipe-impersonation, Privilege Escalation via Rogue Named Pipe Impersonation>> |Identifies a privilege escalation attempt via rogue named pipe impersonation. An adversary may abuse this technique by masquerading as a known named pipe and manipulating a privileged process to connect to it. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Sysmon] |8.3.0 |106
+|<<privilege-escalation-via-rogue-named-pipe-impersonation, Privilege Escalation via Rogue Named Pipe Impersonation>> |Identifies a privilege escalation attempt via rogue named pipe impersonation. An adversary may abuse this technique by masquerading as a known named pipe and manipulating a privileged process to connect to it. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Sysmon] |None |106
 
-|<<privilege-escalation-via-root-crontab-file-modification, Privilege Escalation via Root Crontab File Modification>> |Identifies modifications to the root crontab file. Adversaries may overwrite this file to gain code execution with root privileges by exploiting privileged file write or move related vulnerabilities. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |106
+|<<privilege-escalation-via-root-crontab-file-modification, Privilege Escalation via Root Crontab File Modification>> |Identifies modifications to the root crontab file. Adversaries may overwrite this file to gain code execution with root privileges by exploiting privileged file write or move related vulnerabilities. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |106
 
-|<<privilege-escalation-via-windir-environment-variable, Privilege Escalation via Windir Environment Variable>> |Identifies a privilege escalation attempt via a rogue Windows directory (Windir) environment variable. This is a known primitive that is often combined with other vulnerabilities to elevate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |106
+|<<privilege-escalation-via-windir-environment-variable, Privilege Escalation via Windir Environment Variable>> |Identifies a privilege escalation attempt via a rogue Windows directory (Windir) environment variable. This is a known primitive that is often combined with other vulnerabilities to elevate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |106
 
-|<<privileged-account-brute-force, Privileged Account Brute Force>> |Identifies multiple consecutive logon failures targeting an Admin account from the same source address and within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide] |8.3.0 |9
+|<<privileged-account-brute-force, Privileged Account Brute Force>> |Identifies multiple consecutive logon failures targeting an Admin account from the same source address and within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide] |None |9
 
-|<<privileges-elevation-via-parent-process-pid-spoofing, Privileges Elevation via Parent Process PID Spoofing>> |Identifies parent process spoofing used to create an elevated child process. Adversaries may spoof the parent process identifier (PPID) of a new process to evade process-monitoring defenses or to elevate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |7
+|<<privileges-elevation-via-parent-process-pid-spoofing, Privileges Elevation via Parent Process PID Spoofing>> |Identifies parent process spoofing used to create an elevated child process. Adversaries may spoof the parent process identifier (PPID) of a new process to evade process-monitoring defenses or to elevate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |7
 
-|<<process-activity-via-compiled-html-file, Process Activity via Compiled HTML File>> |Compiled HTML files (.chm) are commonly distributed as part of the Microsoft HTML Help system. Adversaries may conceal malicious code in a CHM file and deliver it to a victim for execution. CHM content is loaded by the HTML Help executable program (hh.exe). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |110
+|<<process-activity-via-compiled-html-file, Process Activity via Compiled HTML File>> |Compiled HTML files (.chm) are commonly distributed as part of the Microsoft HTML Help system. Adversaries may conceal malicious code in a CHM file and deliver it to a victim for execution. CHM content is loaded by the HTML Help executable program (hh.exe). |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |110
 
 |<<process-capability-enumeration, Process Capability Enumeration>> |Identifies recursive process capability enumeration of the entire filesystem through the getcap command. Malicious users may manipulate identified capabilities to gain root privileges. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.11.0 |2
 
-|<<process-created-with-a-duplicated-token, Process Created with a Duplicated Token>> |Identifies the creation of a process impersonating the token of another user logon session. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.4.0 |3
+|<<process-created-with-a-duplicated-token, Process Created with a Duplicated Token>> |Identifies the creation of a process impersonating the token of another user logon session. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |3
 
-|<<process-created-with-an-elevated-token, Process Created with an Elevated Token>> |Identifies the creation of a process running as SYSTEM and impersonating a Windows core binary privileges. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.4.0 |6
+|<<process-created-with-an-elevated-token, Process Created with an Elevated Token>> |Identifies the creation of a process running as SYSTEM and impersonating a Windows core binary privileges. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |6
 
-|<<process-creation-via-secondary-logon, Process Creation via Secondary Logon>> |Identifies process creation with alternate credentials. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |9
+|<<process-creation-via-secondary-logon, Process Creation via Secondary Logon>> |Identifies process creation with alternate credentials. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |9
 
-|<<process-discovery-using-built-in-tools, Process Discovery Using Built-in Tools>> |This rule identifies the execution of commands that can be used to enumerate running processes. Adversaries may enumerate processes to identify installed applications and security solutions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |4
+|<<process-discovery-using-built-in-tools, Process Discovery Using Built-in Tools>> |This rule identifies the execution of commands that can be used to enumerate running processes. Adversaries may enumerate processes to identify installed applications and security solutions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |4
 
-|<<process-discovery-via-built-in-applications, Process Discovery via Built-In Applications>> |Identifies the use of built-in tools attackers can use to discover running processes on an endpoint. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |3
+|<<process-discovery-via-built-in-applications, Process Discovery via Built-In Applications>> |Identifies the use of built-in tools attackers can use to discover running processes on an endpoint. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |3
 
-|<<process-execution-from-an-unusual-directory, Process Execution from an Unusual Directory>> |Identifies process execution from suspicious default Windows directories. This is sometimes done by adversaries to hide malware in trusted paths. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<process-execution-from-an-unusual-directory, Process Execution from an Unusual Directory>> |Identifies process execution from suspicious default Windows directories. This is sometimes done by adversaries to hide malware in trusted paths. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<process-injection-detected-elastic-endgame, Process Injection - Detected - Elastic Endgame>> |Elastic Endgame detected Process Injection. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<process-injection-detected-elastic-endgame, Process Injection - Detected - Elastic Endgame>> |Elastic Endgame detected Process Injection. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |103
 
-|<<process-injection-prevented-elastic-endgame, Process Injection - Prevented - Elastic Endgame>> |Elastic Endgame prevented Process Injection. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<process-injection-prevented-elastic-endgame, Process Injection - Prevented - Elastic Endgame>> |Elastic Endgame prevented Process Injection. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |103
 
-|<<process-injection-by-the-microsoft-build-engine, Process Injection by the Microsoft Build Engine>> |An instance of MSBuild, the Microsoft Build Engine, created a thread in another process. This technique is sometimes used to evade detection or elevate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Data Source: Sysmon] |8.3.0 |106
+|<<process-injection-by-the-microsoft-build-engine, Process Injection by the Microsoft Build Engine>> |An instance of MSBuild, the Microsoft Build Engine, created a thread in another process. This technique is sometimes used to evade detection or elevate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Data Source: Sysmon] |None |106
 
-|<<process-started-from-process-id-pid-file, Process Started from Process ID (PID) File>> |Identifies a new process starting from a process ID (PID), lock or reboot file within the temporary file storage paradigm (tmpfs) directory /var/run directory. On Linux, the PID files typically hold the process ID to track previous copies running and manage other tasks. Certain Linux malware use the /var/run directory for holding data, executables and other tasks, disguising itself or these files as legitimate PID files. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: BPFDoor], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |8.3.0 |109
+|<<process-started-from-process-id-pid-file, Process Started from Process ID (PID) File>> |Identifies a new process starting from a process ID (PID), lock or reboot file within the temporary file storage paradigm (tmpfs) directory /var/run directory. On Linux, the PID files typically hold the process ID to track previous copies running and manage other tasks. Certain Linux malware use the /var/run directory for holding data, executables and other tasks, disguising itself or these files as legitimate PID files. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Threat: BPFDoor], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Auditd Manager] |None |109
 
-|<<process-termination-followed-by-deletion, Process Termination followed by Deletion>> |Identifies a process termination event quickly followed by the deletion of its executable file. Malware tools and other non-native files dropped or created on a system by an adversary may leave traces to indicate to what occurred. Removal of these files can occur during an intrusion, or as part of a post-intrusion process to minimize the adversary's footprint. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |109
+|<<process-termination-followed-by-deletion, Process Termination followed by Deletion>> |Identifies a process termination event quickly followed by the deletion of its executable file. Malware tools and other non-native files dropped or created on a system by an adversary may leave traces to indicate to what occurred. Removal of these files can occur during an intrusion, or as part of a post-intrusion process to minimize the adversary's footprint. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |109
 
-|<<processes-with-trailing-spaces, Processes with Trailing Spaces>> |Identify instances where adversaries include trailing space characters to mimic regular files, disguising their activity to evade default file handling mechanisms. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |2
+|<<processes-with-trailing-spaces, Processes with Trailing Spaces>> |Identify instances where adversaries include trailing space characters to mimic regular files, disguising their activity to evade default file handling mechanisms. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |2
 
-|<<program-files-directory-masquerading, Program Files Directory Masquerading>> |Identifies execution from a directory masquerading as the Windows Program Files directories. These paths are trusted and usually host trusted third party programs. An adversary may leverage masquerading, along with low privileges to bypass detections allowlisting those folders. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<program-files-directory-masquerading, Program Files Directory Masquerading>> |Identifies execution from a directory masquerading as the Windows Program Files directories. These paths are trusted and usually host trusted third party programs. An adversary may leverage masquerading, along with low privileges to bypass detections allowlisting those folders. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<prompt-for-credentials-with-osascript, Prompt for Credentials with OSASCRIPT>> |Identifies the use of osascript to execute scripts via standard input that may prompt a user with a rogue dialog for credentials. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.7.0 |207
+|<<prompt-for-credentials-with-osascript, Prompt for Credentials with OSASCRIPT>> |Identifies the use of osascript to execute scripts via standard input that may prompt a user with a rogue dialog for credentials. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |208
 
-|<<proxychains-activity, ProxyChains Activity>> |This rule monitors for the execution of the ProxyChains utility. ProxyChains is a command-line tool that enables the routing of network connections through intermediary proxies, enhancing anonymity and enabling access to restricted resources. Attackers can exploit the ProxyChains utility to hide their true source IP address, evade detection, and perform malicious activities through a chain of proxy servers, potentially masking their identity and intentions. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |4
+|<<proxychains-activity, ProxyChains Activity>> |This rule monitors for the execution of the ProxyChains utility. ProxyChains is a command-line tool that enables the routing of network connections through intermediary proxies, enhancing anonymity and enabling access to restricted resources. Attackers can exploit the ProxyChains utility to hide their true source IP address, evade detection, and perform malicious activities through a chain of proxy servers, potentially masking their identity and intentions. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |4
 
-|<<psexec-network-connection, PsExec Network Connection>> |Identifies use of the SysInternals tool PsExec.exe making a network connection. This could be an indication of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<psexec-network-connection, PsExec Network Connection>> |Identifies use of the SysInternals tool PsExec.exe making a network connection. This could be an indication of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
 |<<python-script-execution-via-command-line, Python Script Execution via Command Line>> |Identifies when a Python script is executed using command line input and imports the sys module. Attackers often use this method to execute malicious scripts and avoiding writing it to disk. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |1
 
-|<<quarantine-attrib-removed-by-unsigned-or-untrusted-process, Quarantine Attrib Removed by Unsigned or Untrusted Process>> |Detects deletion of the quarantine attribute by an unusual process (xattr). In macOS, when applications or programs are downloaded from the internet, there is a quarantine flag set on the file. This attribute is read by Apple's Gatekeeper defense program at execution time. An adversary may disable this attribute to evade defenses. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |108
+|<<quarantine-attrib-removed-by-unsigned-or-untrusted-process, Quarantine Attrib Removed by Unsigned or Untrusted Process>> |Detects deletion of the quarantine attribute by an unusual process (xattr). In macOS, when applications or programs are downloaded from the internet, there is a quarantine flag set on the file. This attribute is read by Apple's Gatekeeper defense program at execution time. An adversary may disable this attribute to evade defenses. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |109
 
-|<<query-registry-using-built-in-tools, Query Registry using Built-in Tools>> |This rule identifies the execution of commands that can be used to query the Windows Registry. Adversaries may query the registry to gain situational awareness about the host, like installed security software, programs and settings. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |8.6.0 |105
+|<<query-registry-using-built-in-tools, Query Registry using Built-in Tools>> |This rule identifies the execution of commands that can be used to query the Windows Registry. Adversaries may query the registry to gain situational awareness about the host, like installed security software, programs and settings. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |None |105
 
-|<<rdp-remote-desktop-protocol-from-the-internet, RDP (Remote Desktop Protocol) from the Internet>> |This rule detects network events that may indicate the use of RDP traffic from the Internet. RDP is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |8.3.0 |103
+|<<rdp-remote-desktop-protocol-from-the-internet, RDP (Remote Desktop Protocol) from the Internet>> |This rule detects network events that may indicate the use of RDP traffic from the Internet. RDP is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |None |103
 
-|<<rdp-enabled-via-registry, RDP Enabled via Registry>> |Identifies registry write modifications to enable Remote Desktop Protocol (RDP) access. This could be indicative of adversary lateral movement preparation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<rdp-enabled-via-registry, RDP Enabled via Registry>> |Identifies registry write modifications to enable Remote Desktop Protocol (RDP) access. This could be indicative of adversary lateral movement preparation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<rpc-remote-procedure-call-from-the-internet, RPC (Remote Procedure Call) from the Internet>> |This rule detects network events that may indicate the use of RPC traffic from the Internet. RPC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Initial Access], [Domain: Endpoint], [Use Case: Threat Detection] |8.3.0 |103
+|<<rpc-remote-procedure-call-from-the-internet, RPC (Remote Procedure Call) from the Internet>> |This rule detects network events that may indicate the use of RPC traffic from the Internet. RPC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Initial Access], [Domain: Endpoint], [Use Case: Threat Detection] |None |103
 
-|<<rpc-remote-procedure-call-to-the-internet, RPC (Remote Procedure Call) to the Internet>> |This rule detects network events that may indicate the use of RPC traffic to the Internet. RPC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Initial Access], [Domain: Endpoint], [Use Case: Threat Detection] |8.3.0 |103
+|<<rpc-remote-procedure-call-to-the-internet, RPC (Remote Procedure Call) to the Internet>> |This rule detects network events that may indicate the use of RPC traffic to the Internet. RPC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Initial Access], [Domain: Endpoint], [Use Case: Threat Detection] |None |103
 
-|<<ransomware-detected-elastic-endgame, Ransomware - Detected - Elastic Endgame>> |Elastic Endgame detected ransomware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |8.3.0 |103
+|<<ransomware-detected-elastic-endgame, Ransomware - Detected - Elastic Endgame>> |Elastic Endgame detected ransomware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |None |103
 
-|<<ransomware-prevented-elastic-endgame, Ransomware - Prevented - Elastic Endgame>> |Elastic Endgame prevented ransomware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |8.3.0 |103
+|<<ransomware-prevented-elastic-endgame, Ransomware - Prevented - Elastic Endgame>> |Elastic Endgame prevented ransomware. Click the Elastic Endgame icon in the event.module column or the link in the rule.reference column for additional information. |[Data Source: Elastic Endgame] |None |103
 
-|<<rare-aws-error-code, Rare AWS Error Code>> |A machine learning job detected an unusual error in a CloudTrail message. These can be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |8.9.0 |208
+|<<rare-aws-error-code, Rare AWS Error Code>> |A machine learning job detected an unusual error in a CloudTrail message. These can be byproducts of attempted or successful persistence, privilege escalation, defense evasion, discovery, lateral movement, or collection. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |None |208
 
-|<<rare-smb-connection-to-the-internet, Rare SMB Connection to the Internet>> |This rule detects rare internet network connections via the SMB protocol. SMB is commonly used to leak NTLM credentials via rogue UNC path injection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Exfiltration], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |3
+|<<rare-smb-connection-to-the-internet, Rare SMB Connection to the Internet>> |This rule detects rare internet network connections via the SMB protocol. SMB is commonly used to leak NTLM credentials via rogue UNC path injection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Exfiltration], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |3
 
-|<<rare-user-logon, Rare User Logon>> |A machine learning job found an unusual user name in the authentication logs. An unusual user name is one way of detecting credentialed access by means of a new or dormant user account. An inactive user account (because the user has left the organization) that becomes active may be due to credentialed access using a compromised account password. Threat actors will sometimes also create new users as a means of persisting in a compromised web application. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access], [Resources: Investigation Guide] |8.3.0 |104
+|<<rare-user-logon, Rare User Logon>> |A machine learning job found an unusual user name in the authentication logs. An unusual user name is one way of detecting credentialed access by means of a new or dormant user account. An inactive user account (because the user has left the organization) that becomes active may be due to credentialed access using a compromised account password. Threat actors will sometimes also create new users as a means of persisting in a compromised web application. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access], [Resources: Investigation Guide] |None |104
 
-|<<registry-persistence-via-appcert-dll, Registry Persistence via AppCert DLL>> |Detects attempts to maintain persistence by creating registry keys using AppCert DLLs. AppCert DLLs are loaded by every process using the common API functions to create processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<registry-persistence-via-appcert-dll, Registry Persistence via AppCert DLL>> |Detects attempts to maintain persistence by creating registry keys using AppCert DLLs. AppCert DLLs are loaded by every process using the common API functions to create processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |210
 
-|<<registry-persistence-via-appinit-dll, Registry Persistence via AppInit DLL>> |AppInit DLLs are dynamic-link libraries (DLLs) that are loaded into every process that creates a user interface (loads user32.dll) on Microsoft Windows operating systems. The AppInit DLL mechanism is used to load custom code into user-mode processes, allowing for the customization of the user interface and the behavior of Windows-based applications. Attackers who add those DLLs to the registry locations can execute code with elevated privileges, similar to process injection, and provide a solid and constant persistence on the machine. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<registry-persistence-via-appinit-dll, Registry Persistence via AppInit DLL>> |AppInit DLLs are dynamic-link libraries (DLLs) that are loaded into every process that creates a user interface (loads user32.dll) on Microsoft Windows operating systems. The AppInit DLL mechanism is used to load custom code into user-mode processes, allowing for the customization of the user interface and the behavior of Windows-based applications. Attackers who add those DLLs to the registry locations can execute code with elevated privileges, similar to process injection, and provide a solid and constant persistence on the machine. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<remote-computer-account-dnshostname-update, Remote Computer Account DnsHostName Update>> |Identifies the remote update to a computer account's DnsHostName attribute. If the new value set is a valid domain controller DNS hostname and the subject computer name is not a domain controller, then it's highly likely a preparation step to exploit CVE-2022-26923 in an attempt to elevate privileges from a standard domain user to domain admin privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Use Case: Vulnerability] |8.3.0 |107
+|<<remote-computer-account-dnshostname-update, Remote Computer Account DnsHostName Update>> |Identifies the remote update to a computer account's DnsHostName attribute. If the new value set is a valid domain controller DNS hostname and the subject computer name is not a domain controller, then it's highly likely a preparation step to exploit CVE-2022-26923 in an attempt to elevate privileges from a standard domain user to domain admin privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Active Directory Monitoring], [Data Source: Active Directory], [Use Case: Vulnerability] |None |107
 
-|<<remote-desktop-enabled-in-windows-firewall-by-netsh, Remote Desktop Enabled in Windows Firewall by Netsh>> |Identifies use of the network shell utility (netsh.exe) to enable inbound Remote Desktop Protocol (RDP) connections in the Windows Firewall. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<remote-desktop-enabled-in-windows-firewall-by-netsh, Remote Desktop Enabled in Windows Firewall by Netsh>> |Identifies use of the network shell utility (netsh.exe) to enable inbound Remote Desktop Protocol (RDP) connections in the Windows Firewall. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<remote-execution-via-file-shares, Remote Execution via File Shares>> |Identifies the execution of a file that was created by the virtual system process. This may indicate lateral movement via network file shares. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<remote-execution-via-file-shares, Remote Execution via File Shares>> |Identifies the execution of a file that was created by the virtual system process. This may indicate lateral movement via network file shares. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<remote-file-copy-to-a-hidden-share, Remote File Copy to a Hidden Share>> |Identifies a remote file copy attempt to a hidden network share. This may indicate lateral movement or data staging activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<remote-file-copy-to-a-hidden-share, Remote File Copy to a Hidden Share>> |Identifies a remote file copy attempt to a hidden network share. This may indicate lateral movement or data staging activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<remote-file-copy-via-teamviewer, Remote File Copy via TeamViewer>> |Identifies an executable or script file remotely downloaded via a TeamViewer transfer session. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<remote-file-copy-via-teamviewer, Remote File Copy via TeamViewer>> |Identifies an executable or script file remotely downloaded via a TeamViewer transfer session. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<remote-file-download-via-desktopimgdownldr-utility, Remote File Download via Desktopimgdownldr Utility>> |Identifies the desktopimgdownldr utility being used to download a remote file. An adversary may use desktopimgdownldr to download arbitrary files as an alternative to certutil. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<remote-file-download-via-desktopimgdownldr-utility, Remote File Download via Desktopimgdownldr Utility>> |Identifies the desktopimgdownldr utility being used to download a remote file. An adversary may use desktopimgdownldr to download arbitrary files as an alternative to certutil. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<remote-file-download-via-mpcmdrun, Remote File Download via MpCmdRun>> |Identifies the Windows Defender configuration utility (MpCmdRun.exe) being used to download a remote file. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<remote-file-download-via-mpcmdrun, Remote File Download via MpCmdRun>> |Identifies the Windows Defender configuration utility (MpCmdRun.exe) being used to download a remote file. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<remote-file-download-via-powershell, Remote File Download via PowerShell>> |Identifies powershell.exe being used to download an executable file from an untrusted remote destination. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |110
+|<<remote-file-download-via-powershell, Remote File Download via PowerShell>> |Identifies powershell.exe being used to download an executable file from an untrusted remote destination. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |110
 
-|<<remote-file-download-via-script-interpreter, Remote File Download via Script Interpreter>> |Identifies built-in Windows script interpreters (cscript.exe or wscript.exe) being used to download an executable file from a remote destination. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<remote-file-download-via-script-interpreter, Remote File Download via Script Interpreter>> |Identifies built-in Windows script interpreters (cscript.exe or wscript.exe) being used to download an executable file from a remote destination. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<remote-ssh-login-enabled-via-systemsetup-command, Remote SSH Login Enabled via systemsetup Command>> |Detects use of the systemsetup command to enable remote SSH Login. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |8.3.0 |106
+|<<remote-ssh-login-enabled-via-systemsetup-command, Remote SSH Login Enabled via systemsetup Command>> |Detects use of the systemsetup command to enable remote SSH Login. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |None |106
 
-|<<remote-scheduled-task-creation, Remote Scheduled Task Creation>> |Identifies remote scheduled task creations on a target host. This could be indicative of adversary lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<remote-scheduled-task-creation, Remote Scheduled Task Creation>> |Identifies remote scheduled task creations on a target host. This could be indicative of adversary lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<remote-scheduled-task-creation-via-rpc, Remote Scheduled Task Creation via RPC>> |Identifies scheduled task creation from a remote source. This could be indicative of adversary lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement] |8.3.0 |8
+|<<remote-scheduled-task-creation-via-rpc, Remote Scheduled Task Creation via RPC>> |Identifies scheduled task creation from a remote source. This could be indicative of adversary lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement] |None |8
 
-|<<remote-system-discovery-commands, Remote System Discovery Commands>> |Discovery of remote system information using built-in commands, which may be used to move laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR] |8.3.0 |112
+|<<remote-system-discovery-commands, Remote System Discovery Commands>> |Discovery of remote system information using built-in commands, which may be used to move laterally. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR] |None |112
 
-|<<remote-windows-service-installed, Remote Windows Service Installed>> |Identifies a network logon followed by Windows service creation with same LogonId. This could be indicative of lateral movement, but will be noisy if commonly done by administrators." |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence] |8.3.0 |6
+|<<remote-windows-service-installed, Remote Windows Service Installed>> |Identifies a network logon followed by Windows service creation with same LogonId. This could be indicative of lateral movement, but will be noisy if commonly done by administrators." |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence] |None |6
 
-|<<remote-xsl-script-execution-via-com, Remote XSL Script Execution via COM>> |Identifies the execution of a hosted XSL script using the Microsoft.XMLDOM COM interface via Microsoft Office processes. This behavior may indicate adversarial activity to execute malicious JScript or VBScript on the system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |3
+|<<remote-xsl-script-execution-via-com, Remote XSL Script Execution via COM>> |Identifies the execution of a hosted XSL script using the Microsoft.XMLDOM COM interface via Microsoft Office processes. This behavior may indicate adversarial activity to execute malicious JScript or VBScript on the system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |3
 
-|<<remotely-started-services-via-rpc, Remotely Started Services via RPC>> |Identifies remote execution of Windows services over remote procedure call (RPC). This could be indicative of lateral movement, but will be noisy if commonly done by administrators. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |112
+|<<remotely-started-services-via-rpc, Remotely Started Services via RPC>> |Identifies remote execution of Windows services over remote procedure call (RPC). This could be indicative of lateral movement, but will be noisy if commonly done by administrators. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |112
 
-|<<renamed-autoit-scripts-interpreter, Renamed AutoIt Scripts Interpreter>> |Identifies a suspicious AutoIt process execution. Malware written as an AutoIt script tends to rename the AutoIt executable to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<renamed-autoit-scripts-interpreter, Renamed AutoIt Scripts Interpreter>> |Identifies a suspicious AutoIt process execution. Malware written as an AutoIt script tends to rename the AutoIt executable to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<renamed-utility-executed-with-short-program-name, Renamed Utility Executed with Short Program Name>> |Identifies the execution of a process with a single character process name, differing from the original file name. This is often done by adversaries while staging, executing temporary utilities, or trying to bypass security detections based on the process name. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<renamed-utility-executed-with-short-program-name, Renamed Utility Executed with Short Program Name>> |Identifies the execution of a process with a single character process name, differing from the original file name. This is often done by adversaries while staging, executing temporary utilities, or trying to bypass security detections based on the process name. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
 |<<root-network-connection-via-gdb-cap-sys-ptrace, Root Network Connection via GDB CAP_SYS_PTRACE>> |Identifies instances where GDB (granted the CAP_SYS_PTRACE capability) is executed, after which an outbound network connection is initiated by UID/GID 0 (root). In Linux, the CAP_SYS_PTRACE capability grants a process the ability to use the ptrace system call, which is typically used for debugging and allows the process to trace and control other processes. Attackers may leverage this capability to hook and inject into a process that is running with root permissions in order to execute shell code and gain a reverse shell with root privileges. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Execution], [Tactic: Command and Control], [Data Source: Elastic Defend] |8.11.0 |2
 
-|<<roshal-archive-rar-or-powershell-file-downloaded-from-the-internet, Roshal Archive (RAR) or PowerShell File Downloaded from the Internet>> |Detects a Roshal Archive (RAR) file or PowerShell script downloaded from the internet by an internal host. Gaining initial access to a system and then downloading encoded or encrypted tools to move laterally is a common practice for adversaries as a way to protect their more valuable tools and tactics, techniques, and procedures (TTPs). This may be atypical behavior for a managed network and can be indicative of malware, exfiltration, or command and control. |[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |8.3.0 |103
+|<<roshal-archive-rar-or-powershell-file-downloaded-from-the-internet, Roshal Archive (RAR) or PowerShell File Downloaded from the Internet>> |Detects a Roshal Archive (RAR) file or PowerShell script downloaded from the internet by an internal host. Gaining initial access to a system and then downloading encoded or encrypted tools to move laterally is a common practice for adversaries as a way to protect their more valuable tools and tactics, techniques, and procedures (TTPs). This may be atypical behavior for a managed network and can be indicative of malware, exfiltration, or command and control. |[Use Case: Threat Detection], [Tactic: Command and Control], [Domain: Endpoint] |None |103
 
-|<<route53-resolver-query-log-configuration-deleted, Route53 Resolver Query Log Configuration Deleted>> |Identifies when a Route53 Resolver Query Log Configuration is deleted. When a Route53 Resolver query log configuration is deleted, Resolver stops logging DNS queries and responses for the specified configuration. Adversaries may delete query log configurations to evade detection or cover their tracks. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon Route53], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |8.9.0 |1
+|<<route53-resolver-query-log-configuration-deleted, Route53 Resolver Query Log Configuration Deleted>> |Identifies when a Route53 Resolver Query Log Configuration is deleted. When a Route53 Resolver query log configuration is deleted, Resolver stops logging DNS queries and responses for the specified configuration. Adversaries may delete query log configurations to evade detection or cover their tracks. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: Amazon Route53], [Use Case: Log Auditing], [Resources: Investigation Guide], [Tactic: Defense Evasion] |None |2
 
-|<<sip-provider-modification, SIP Provider Modification>> |Identifies modifications to the registered Subject Interface Package (SIP) providers. SIP providers are used by the Windows cryptographic system to validate file signatures on the system. This may be an attempt to bypass signature validation checks or inject code into critical processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<sip-provider-modification, SIP Provider Modification>> |Identifies modifications to the registered Subject Interface Package (SIP) providers. SIP providers are used by the Windows cryptographic system to validate file signatures on the system. This may be an attempt to bypass signature validation checks or inject code into critical processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<smb-windows-file-sharing-activity-to-the-internet, SMB (Windows File Sharing) Activity to the Internet>> |This rule detects network events that may indicate the use of Windows file sharing (also called SMB or CIFS) traffic to the Internet. SMB is commonly used within networks to share files, printers, and other system resources amongst trusted systems. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector or for data exfiltration. |[Tactic: Initial Access], [Domain: Endpoint], [Use Case: Threat Detection] |8.3.0 |103
+|<<smb-windows-file-sharing-activity-to-the-internet, SMB (Windows File Sharing) Activity to the Internet>> |This rule detects network events that may indicate the use of Windows file sharing (also called SMB or CIFS) traffic to the Internet. SMB is commonly used within networks to share files, printers, and other system resources amongst trusted systems. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector or for data exfiltration. |[Tactic: Initial Access], [Domain: Endpoint], [Use Case: Threat Detection] |None |103
 
-|<<smtp-on-port-26-tcp, SMTP on Port 26/TCP>> |This rule detects events that may indicate use of SMTP on TCP port 26. This port is commonly used by several popular mail transfer agents to deconflict with the default SMTP port 25. This port has also been used by a malware family called BadPatch for command and control of Windows systems. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |8.3.0 |104
+|<<smtp-on-port-26-tcp, SMTP on Port 26/TCP>> |This rule detects events that may indicate use of SMTP on TCP port 26. This port is commonly used by several popular mail transfer agents to deconflict with the default SMTP port 25. This port has also been used by a malware family called BadPatch for command and control of Windows systems. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |None |104
 
-|<<ssh-authorized-keys-file-modification, SSH Authorized Keys File Modification>> |The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s). |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence], [Data Source: Elastic Defend] |8.6.0 |205
+|<<ssh-authorized-keys-file-modification, SSH Authorized Keys File Modification>> |The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s). |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence], [Data Source: Elastic Defend] |None |206
 
-|<<ssh-authorized-keys-file-modified-inside-a-container, SSH Authorized Keys File Modified Inside a Container>> |This rule detects the creation or modification of an authorized_keys or sshd_config file inside a container. The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s). Unexpected and unauthorized SSH usage inside a container can be an indicator of compromise and should be investigated. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Lateral Movement] |8.8.0 |2
+|<<ssh-authorized-keys-file-modified-inside-a-container, SSH Authorized Keys File Modified Inside a Container>> |This rule detects the creation or modification of an authorized_keys or sshd_config file inside a container. The Secure Shell (SSH) authorized_keys file specifies which users are allowed to log into a server using public key authentication. Adversaries may modify it to maintain persistence on a victim host by adding their own public key(s). Unexpected and unauthorized SSH usage inside a container can be an indicator of compromise and should be investigated. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Lateral Movement] |None |3
 
-|<<ssh-connection-established-inside-a-running-container, SSH Connection Established Inside A Running Container>> |This rule detects an incoming SSH connection established inside a running container. Running an ssh daemon inside a container should be avoided and monitored closely if necessary. If an attacker gains valid credentials they can use it to gain initial access or establish persistence within a compromised environment. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement] |8.8.0 |2
+|<<ssh-connection-established-inside-a-running-container, SSH Connection Established Inside A Running Container>> |This rule detects an incoming SSH connection established inside a running container. Running an ssh daemon inside a container should be avoided and monitored closely if necessary. If an attacker gains valid credentials they can use it to gain initial access or establish persistence within a compromised environment. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Lateral Movement] |None |2
 
-|<<ssh-process-launched-from-inside-a-container, SSH Process Launched From Inside A Container>> |This rule detects an SSH or SSHD process executed from inside a container. This includes both the client ssh binary and server ssh daemon process. SSH usage inside a container should be avoided and monitored closely when necessary. With valid credentials an attacker may move laterally to other containers or to the underlying host through container breakout. They may also use valid SSH credentials as a persistence mechanism. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence] |8.8.0 |2
+|<<ssh-process-launched-from-inside-a-container, SSH Process Launched From Inside A Container>> |This rule detects an SSH or SSHD process executed from inside a container. This includes both the client ssh binary and server ssh daemon process. SSH usage inside a container should be avoided and monitored closely when necessary. With valid credentials an attacker may move laterally to other containers or to the underlying host through container breakout. They may also use valid SSH credentials as a persistence mechanism. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence] |None |2
 
-|<<suid-sguid-enumeration-detected, SUID/SGUID Enumeration Detected>> |This rule monitors for the usage of the "find" command in conjunction with SUID and SGUID permission arguments. SUID (Set User ID) and SGID (Set Group ID) are special permissions in Linux that allow a program to execute with the privileges of the file owner or group, respectively, rather than the privileges of the user running the program. In case an attacker is able to enumerate and find a binary that is misconfigured, they might be able to leverage this misconfiguration to escalate privileges by exploiting vulnerabilities or built-in features in the privileged program. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |5
+|<<ssm-session-started-to-ec2-instance, SSM Session Started to EC2 Instance>> |Identifies the first occurrence of an AWS resource establishing a session via SSM to an EC2 instance. Adversaries may use AWS Systems Manager to establish a session to an EC2 instance to execute commands on the instance. This can be used to gain access to the instance and perform actions such as privilege escalation. This rule helps detect the first occurrence of this activity for a given AWS resource. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Data Source: AWS SSM], [Use Case: Threat Detection], [Tactic: Lateral Movement] |8.9.0 |1
 
-|<<sunburst-command-and-control-activity, SUNBURST Command and Control Activity>> |The malware known as SUNBURST targets the SolarWind's Orion business software for command and control. This rule detects post-exploitation command and control activity of the SUNBURST backdoor. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |108
+|<<suid-sguid-enumeration-detected, SUID/SGUID Enumeration Detected>> |This rule monitors for the usage of the "find" command in conjunction with SUID and SGUID permission arguments. SUID (Set User ID) and SGID (Set Group ID) are special permissions in Linux that allow a program to execute with the privileges of the file owner or group, respectively, rather than the privileges of the user running the program. In case an attacker is able to enumerate and find a binary that is misconfigured, they might be able to leverage this misconfiguration to escalate privileges by exploiting vulnerabilities or built-in features in the privileged program. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |5
 
-|<<scheduled-task-created-by-a-windows-script, Scheduled Task Created by a Windows Script>> |A scheduled task was created by a Windows script via cscript.exe, wscript.exe or powershell.exe. This can be abused by an adversary to establish persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<sunburst-command-and-control-activity, SUNBURST Command and Control Activity>> |The malware known as SUNBURST targets the SolarWind's Orion business software for command and control. This rule detects post-exploitation command and control activity of the SUNBURST backdoor. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |108
 
-|<<scheduled-task-execution-at-scale-via-gpo, Scheduled Task Execution at Scale via GPO>> |Detects the modification of Group Policy Object attributes to execute a scheduled task in the objects controlled by the GPO. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Lateral Movement], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |8.3.0 |110
+|<<scheduled-task-created-by-a-windows-script, Scheduled Task Created by a Windows Script>> |A scheduled task was created by a Windows script via cscript.exe, wscript.exe or powershell.exe. This can be abused by an adversary to establish persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<scheduled-tasks-at-command-enabled, Scheduled Tasks AT Command Enabled>> |Identifies attempts to enable the Windows scheduled tasks AT command via the registry. Attackers may use this method to move laterally or persist locally. The AT command has been deprecated since Windows 8 and Windows Server 2012, but still exists for backwards compatibility. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<scheduled-task-execution-at-scale-via-gpo, Scheduled Task Execution at Scale via GPO>> |Detects the modification of Group Policy Object attributes to execute a scheduled task in the objects controlled by the GPO. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Lateral Movement], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |None |110
 
-|<<screenconnect-server-spawning-suspicious-processes, ScreenConnect Server Spawning Suspicious Processes>> |Identifies suspicious processes being spawned by the ScreenConnect server process (ScreenConnect.Service.exe). This activity may indicate exploitation activity or access to an existing web shell backdoor. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |1
+|<<scheduled-tasks-at-command-enabled, Scheduled Tasks AT Command Enabled>> |Identifies attempts to enable the Windows scheduled tasks AT command via the registry. Attackers may use this method to move laterally or persist locally. The AT command has been deprecated since Windows 8 and Windows Server 2012, but still exists for backwards compatibility. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<screensaver-plist-file-modified-by-unexpected-process, Screensaver Plist File Modified by Unexpected Process>> |Identifies when a screensaver plist file is modified by an unexpected process. An adversary can maintain persistence on a macOS endpoint by creating a malicious screensaver (.saver) file and configuring the screensaver plist file to execute code each time the screensaver is activated. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |107
+|<<screenconnect-server-spawning-suspicious-processes, ScreenConnect Server Spawning Suspicious Processes>> |Identifies suspicious processes being spawned by the ScreenConnect server process (ScreenConnect.Service.exe). This activity may indicate exploitation activity or access to an existing web shell backdoor. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |1
 
-|<<sedebugprivilege-enabled-by-a-suspicious-process, SeDebugPrivilege Enabled by a Suspicious Process>> |Identifies the creation of a process running as SYSTEM and impersonating a Windows core binary privileges. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |7
+|<<screensaver-plist-file-modified-by-unexpected-process, Screensaver Plist File Modified by Unexpected Process>> |Identifies when a screensaver plist file is modified by an unexpected process. An adversary can maintain persistence on a macOS endpoint by creating a malicious screensaver (.saver) file and configuring the screensaver plist file to execute code each time the screensaver is activated. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |107
 
-|<<searching-for-saved-credentials-via-vaultcmd, Searching for Saved Credentials via VaultCmd>> |Windows Credential Manager allows you to create, view, or delete saved credentials for signing into websites, connected applications, and networks. An adversary may abuse this to list or dump credentials stored in the Credential Manager for saved usernames and passwords. This may also be performed in preparation of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<sedebugprivilege-enabled-by-a-suspicious-process, SeDebugPrivilege Enabled by a Suspicious Process>> |Identifies the creation of a process running as SYSTEM and impersonating a Windows core binary privileges. Adversaries may create a new process with a different token to escalate privileges and bypass access controls. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |7
 
-|<<security-software-discovery-using-wmic, Security Software Discovery using WMIC>> |Identifies the use of Windows Management Instrumentation Command (WMIC) to discover certain System Security Settings such as AntiVirus or Host Firewall details. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |111
+|<<searching-for-saved-credentials-via-vaultcmd, Searching for Saved Credentials via VaultCmd>> |Windows Credential Manager allows you to create, view, or delete saved credentials for signing into websites, connected applications, and networks. An adversary may abuse this to list or dump credentials stored in the Credential Manager for saved usernames and passwords. This may also be performed in preparation of lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<security-software-discovery-via-grep, Security Software Discovery via Grep>> |Identifies the use of the grep command to discover known third-party macOS and Linux security tools, such as Antivirus or Host Firewall details. |[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |109
+|<<security-software-discovery-using-wmic, Security Software Discovery using WMIC>> |Identifies the use of Windows Management Instrumentation Command (WMIC) to discover certain System Security Settings such as AntiVirus or Host Firewall details. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |None |111
 
-|<<segfault-detected, Segfault Detected>> |Monitors kernel logs for segfault messages. A segfault, or segmentation fault, is an error that occurs when a program tries to access a memory location that it's not allowed to access, typically leading to program termination. A segfault can be an indication of malicious behavior if it results from attempts to exploit buffer overflows or other vulnerabilities in software to execute arbitrary code or disrupt its normal operation. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Rule Type: BBR] |8.3.0 |1
+|<<security-software-discovery-via-grep, Security Software Discovery via Grep>> |Identifies the use of the grep command to discover known third-party macOS and Linux security tools, such as Antivirus or Host Firewall details. |[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |109
 
-|<<sensitive-files-compression, Sensitive Files Compression>> |Identifies the use of a compression utility to collect known files containing sensitive information, such as credentials and system configurations. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |208
+|<<segfault-detected, Segfault Detected>> |Monitors kernel logs for segfault messages. A segfault, or segmentation fault, is an error that occurs when a program tries to access a memory location that it's not allowed to access, typically leading to program termination. A segfault can be an indication of malicious behavior if it results from attempts to exploit buffer overflows or other vulnerabilities in software to execute arbitrary code or disrupt its normal operation. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Rule Type: BBR] |None |1
 
-|<<sensitive-files-compression-inside-a-container, Sensitive Files Compression Inside A Container>> |Identifies the use of a compression utility to collect known files containing sensitive information, such as credentials and system configurations inside a container. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Credential Access] |8.8.0 |2
+|<<sensitive-files-compression, Sensitive Files Compression>> |Identifies the use of a compression utility to collect known files containing sensitive information, such as credentials and system configurations. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |208
 
-|<<sensitive-keys-or-passwords-searched-for-inside-a-container, Sensitive Keys Or Passwords Searched For Inside A Container>> |This rule detects the use of system search utilities like grep and find to search for private SSH keys or passwords inside a container. Unauthorized access to these sensitive files could lead to further compromise of the container environment or facilitate a container breakout to the underlying host machine. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |8.8.0 |2
+|<<sensitive-files-compression-inside-a-container, Sensitive Files Compression Inside A Container>> |Identifies the use of a compression utility to collect known files containing sensitive information, such as credentials and system configurations inside a container. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Collection], [Tactic: Credential Access] |None |2
 
-|<<sensitive-privilege-seenabledelegationprivilege-assigned-to-a-user, Sensitive Privilege SeEnableDelegationPrivilege assigned to a User>> |Identifies the assignment of the SeEnableDelegationPrivilege sensitive "user right" to a user. The SeEnableDelegationPrivilege "user right" enables computer and user accounts to be trusted for delegation. Attackers can abuse this right to compromise Active Directory accounts and elevate their privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |8.3.0 |110
+|<<sensitive-keys-or-passwords-searched-for-inside-a-container, Sensitive Keys Or Passwords Searched For Inside A Container>> |This rule detects the use of system search utilities like grep and find to search for private SSH keys or passwords inside a container. Unauthorized access to these sensitive files could lead to further compromise of the container environment or facilitate a container breakout to the underlying host machine. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Credential Access] |None |2
 
-|<<service-command-lateral-movement, Service Command Lateral Movement>> |Identifies use of sc.exe to create, modify, or start services on remote hosts. This could be indicative of adversary lateral movement but will be noisy if commonly done by admins. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<sensitive-privilege-seenabledelegationprivilege-assigned-to-a-user, Sensitive Privilege SeEnableDelegationPrivilege assigned to a User>> |Identifies the assignment of the SeEnableDelegationPrivilege sensitive "user right" to a user. The SeEnableDelegationPrivilege "user right" enables computer and user accounts to be trusted for delegation. Attackers can abuse this right to compromise Active Directory accounts and elevate their privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Persistence], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |None |110
 
-|<<service-control-spawned-via-script-interpreter, Service Control Spawned via Script Interpreter>> |Identifies Service Control (sc.exe) spawning from script interpreter processes to create, modify, or start services. This can potentially indicate an attempt to elevate privileges or maintain persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |108
+|<<service-command-lateral-movement, Service Command Lateral Movement>> |Identifies use of sc.exe to create, modify, or start services on remote hosts. This could be indicative of adversary lateral movement but will be noisy if commonly done by admins. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<service-creation-via-local-kerberos-authentication, Service Creation via Local Kerberos Authentication>> |Identifies a suspicious local successful logon event where the Logon Package is Kerberos, the remote address is set to localhost, followed by a sevice creation from the same LogonId. This may indicate an attempt to leverage a Kerberos relay attack variant that can be used to elevate privilege locally from a domain joined user to local System privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |8.3.0 |105
+|<<service-control-spawned-via-script-interpreter, Service Control Spawned via Script Interpreter>> |Identifies Service Control (sc.exe) spawning from script interpreter processes to create, modify, or start services. This can potentially indicate an attempt to elevate privileges or maintain persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |109
 
-|<<service-disabled-via-registry-modification, Service Disabled via Registry Modification>> |Identifies attempts to modify services start settings using processes other than services.exe. Attackers may attempt to modify security and monitoring services to avoid detection or delay response. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |3
+|<<service-creation-via-local-kerberos-authentication, Service Creation via Local Kerberos Authentication>> |Identifies a suspicious local successful logon event where the Logon Package is Kerberos, the remote address is set to localhost, followed by a sevice creation from the same LogonId. This may indicate an attempt to leverage a Kerberos relay attack variant that can be used to elevate privilege locally from a domain joined user to local System privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |None |105
 
-|<<service-path-modification, Service Path Modification>> |Identifies attempts to modify a service path by an unusual process. Attackers may attempt to modify existing services for persistence or privilege escalation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |2
+|<<service-disabled-via-registry-modification, Service Disabled via Registry Modification>> |Identifies attempts to modify services start settings using processes other than services.exe. Attackers may attempt to modify security and monitoring services to avoid detection or delay response. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |None |3
 
-|<<service-path-modification-via-sc-exe, Service Path Modification via sc.exe>> |Identifies attempts to modify a service path setting using sc.exe. Attackers may attempt to modify existing services for persistence or privilege escalation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |3
+|<<service-path-modification, Service Path Modification>> |Identifies attempts to modify a service path by an unusual process. Attackers may attempt to modify existing services for persistence or privilege escalation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |None |2
 
-|<<setcap-setuid-setgid-capability-set, Setcap setuid/setgid Capability Set>> |This rule monitors for the addition of the cap_setuid+ep or cap_setgid+ep capabilities via setcap. Setuid (Set User ID) and setgid (Set Group ID) are Unix-like OS features that enable processes to run with elevated privileges, based on the file owner or group. Threat actors can exploit these attributes to achieve persistence by creating malicious binaries, allowing them to maintain control over a compromised system with elevated permissions. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |5
+|<<service-path-modification-via-sc-exe, Service Path Modification via sc.exe>> |Identifies attempts to modify a service path setting using sc.exe. Attackers may attempt to modify existing services for persistence or privilege escalation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |None |3
 
-|<<setuid-setgid-bit-set-via-chmod, Setuid / Setgid Bit Set via chmod>> |An adversary may add the setuid or setgid bit to a file or directory in order to run a file with the privileges of the owning user or group. An adversary can take advantage of this to either do a shell escape or exploit a vulnerability in an application with the setuid or setgid bit to get code running in a different user’s context. Additionally, adversaries can use this mechanism on their own malware to make sure they're able to execute in elevated contexts in the future. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |103
+|<<setcap-setuid-setgid-capability-set, Setcap setuid/setgid Capability Set>> |This rule monitors for the addition of the cap_setuid+ep or cap_setgid+ep capabilities via setcap. Setuid (Set User ID) and setgid (Set Group ID) are Unix-like OS features that enable processes to run with elevated privileges, based on the file owner or group. Threat actors can exploit these attributes to achieve persistence by creating malicious binaries, allowing them to maintain control over a compromised system with elevated permissions. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |5
 
-|<<sharepoint-malware-file-upload, SharePoint Malware File Upload>> |Identifies the occurence of files uploaded to SharePoint being detected as Malware by the file scanning engine. Attackers can use File Sharing and Organization Repositories to spread laterally within the company and amplify their access. Users can inadvertently share these files without knowing their maliciousness, giving adversaries opportunities to gain initial access to other endpoints in the environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Lateral Movement] |8.8.0 |206
+|<<setuid-setgid-bit-set-via-chmod, Setuid / Setgid Bit Set via chmod>> |An adversary may add the setuid or setgid bit to a file or directory in order to run a file with the privileges of the owning user or group. An adversary can take advantage of this to either do a shell escape or exploit a vulnerability in an application with the setuid or setgid bit to get code running in a different user’s context. Additionally, adversaries can use this mechanism on their own malware to make sure they're able to execute in elevated contexts in the future. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |103
 
-|<<shared-object-created-or-changed-by-previously-unknown-process, Shared Object Created or Changed by Previously Unknown Process>> |This rule monitors the creation of shared object files by previously unknown processes. The creation of a shared object file involves compiling code into a dynamically linked library that can be loaded by other programs at runtime. While this process is typically used for legitimate purposes, malicious actors can leverage shared object files to execute unauthorized code, inject malicious functionality into legitimate processes, or bypass security controls. This allows malware to persist on the system, evade detection, and potentially compromise the integrity and confidentiality of the affected system and its data. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |7
+|<<sharepoint-malware-file-upload, SharePoint Malware File Upload>> |Identifies the occurence of files uploaded to SharePoint being detected as Malware by the file scanning engine. Attackers can use File Sharing and Organization Repositories to spread laterally within the company and amplify their access. Users can inadvertently share these files without knowing their maliciousness, giving adversaries opportunities to gain initial access to other endpoints in the environment. |[Domain: Cloud], [Data Source: Microsoft 365], [Tactic: Lateral Movement] |None |206
 
-|<<shell-configuration-modification, Shell Configuration Modification>> |This rule monitors the creation/alteration of a shell configuration by a previously unknown process executable using the new terms rule type. Unix systems use shell configuration files to set environment variables, create aliases, and customize the user's environment. Adversaries may modify or add a shell configuration file to execute malicious code and gain persistence in the system. This behavior is consistent with the Kaiji malware family. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |1
+|<<shared-object-created-or-changed-by-previously-unknown-process, Shared Object Created or Changed by Previously Unknown Process>> |This rule monitors the creation of shared object files by previously unknown processes. The creation of a shared object file involves compiling code into a dynamically linked library that can be loaded by other programs at runtime. While this process is typically used for legitimate purposes, malicious actors can leverage shared object files to execute unauthorized code, inject malicious functionality into legitimate processes, or bypass security controls. This allows malware to persist on the system, evade detection, and potentially compromise the integrity and confidentiality of the affected system and its data. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |8
 
-|<<shell-execution-via-apple-scripting, Shell Execution via Apple Scripting>> |Identifies the execution of the shell process (sh) via scripting (JXA or AppleScript). Adversaries may use the doShellScript functionality in JXA or do shell script in AppleScript to execute system commands. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |107
+|<<shell-configuration-modification, Shell Configuration Modification>> |This rule monitors the creation/alteration of a shell configuration by a previously unknown process executable using the new terms rule type. Unix systems use shell configuration files to set environment variables, create aliases, and customize the user's environment. Adversaries may modify or add a shell configuration file to execute malicious code and gain persistence in the system. This behavior is consistent with the Kaiji malware family. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |1
 
-|<<shortcut-file-written-or-modified-on-startup-folder, Shortcut File Written or Modified on Startup Folder>> |Identifies shortcut files written to or modified in the startup folder. Adversaries may use this technique to maintain persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |2
+|<<shell-execution-via-apple-scripting, Shell Execution via Apple Scripting>> |Identifies the execution of the shell process (sh) via scripting (JXA or AppleScript). Adversaries may use the doShellScript functionality in JXA or do shell script in AppleScript to execute system commands. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |107
 
-|<<signed-proxy-execution-via-ms-work-folders, Signed Proxy Execution via MS Work Folders>> |Identifies the use of Windows Work Folders to execute a potentially masqueraded control.exe file in the current working directory. Misuse of Windows Work Folders could indicate malicious activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame] |8.3.0 |108
+|<<shortcut-file-written-or-modified-on-startup-folder, Shortcut File Written or Modified on Startup Folder>> |Identifies shortcut files written to or modified in the startup folder. Adversaries may use this technique to maintain persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Rule Type: BBR] |None |2
 
-|<<softwareupdate-preferences-modification, SoftwareUpdate Preferences Modification>> |Identifies changes to the SoftwareUpdate preferences using the built-in defaults command. Adversaries may abuse this in an attempt to disable security updates. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |106
+|<<signed-proxy-execution-via-ms-work-folders, Signed Proxy Execution via MS Work Folders>> |Identifies the use of Windows Work Folders to execute a potentially masqueraded control.exe file in the current working directory. Misuse of Windows Work Folders could indicate malicious activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame] |None |108
 
-|<<solarwinds-process-disabling-services-via-registry, SolarWinds Process Disabling Services via Registry>> |Identifies a SolarWinds binary modifying the start type of a service to be disabled. An adversary may abuse this technique to manipulate relevant security services. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<softwareupdate-preferences-modification, SoftwareUpdate Preferences Modification>> |Identifies changes to the SoftwareUpdate preferences using the built-in defaults command. Adversaries may abuse this in an attempt to disable security updates. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |106
 
-|<<spike-in-aws-error-messages, Spike in AWS Error Messages>> |A machine learning job detected a significant spike in the rate of a particular error in the CloudTrail messages. Spikes in error messages may accompany attempts at privilege escalation, lateral movement, or discovery. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |8.9.0 |208
+|<<solarwinds-process-disabling-services-via-registry, SolarWinds Process Disabling Services via Registry>> |Identifies a SolarWinds binary modifying the start type of a service to be disabled. An adversary may abuse this technique to manipulate relevant security services. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<spike-in-bytes-sent-to-an-external-device, Spike in Bytes Sent to an External Device>> |A machine learning job has detected high bytes of data written to an external device. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |8.9.0 |3
+|<<spike-in-aws-error-messages, Spike in AWS Error Messages>> |A machine learning job detected a significant spike in the rate of a particular error in the CloudTrail messages. Spikes in error messages may accompany attempts at privilege escalation, lateral movement, or discovery. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |None |208
 
-|<<spike-in-bytes-sent-to-an-external-device-via-airdrop, Spike in Bytes Sent to an External Device via Airdrop>> |A machine learning job has detected high bytes of data written to an external device via Airdrop. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |8.9.0 |3
+|<<spike-in-bytes-sent-to-an-external-device, Spike in Bytes Sent to an External Device>> |A machine learning job has detected high bytes of data written to an external device. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |None |4
 
-|<<spike-in-failed-logon-events, Spike in Failed Logon Events>> |A machine learning job found an unusually large spike in authentication failure events. This can be due to password spraying, user enumeration or brute force activity and may be a precursor to account takeover or credentialed access. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access], [Resources: Investigation Guide] |8.3.0 |104
+|<<spike-in-bytes-sent-to-an-external-device-via-airdrop, Spike in Bytes Sent to an External Device via Airdrop>> |A machine learning job has detected high bytes of data written to an external device via Airdrop. In a typical operational setting, there is usually a predictable pattern or a certain range of data that is written to external devices. An unusually large amount of data being written is anomalous and can signal illicit data copying or transfer activities. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |None |4
 
-|<<spike-in-firewall-denies, Spike in Firewall Denies>> |A machine learning job detected an unusually large spike in network traffic that was denied by network access control lists (ACLs) or firewall rules. Such a burst of denied traffic is usually caused by either 1) a mis-configured application or firewall or 2) suspicious or malicious activity. Unsuccessful attempts at network transit, in order to connect to command-and-control (C2), or engage in data exfiltration, may produce a burst of failed connections. This could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |8.3.0 |103
+|<<spike-in-failed-logon-events, Spike in Failed Logon Events>> |A machine learning job found an unusually large spike in authentication failure events. This can be due to password spraying, user enumeration or brute force activity and may be a precursor to account takeover or credentialed access. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access], [Resources: Investigation Guide] |None |104
 
-|<<spike-in-logon-events, Spike in Logon Events>> |A machine learning job found an unusually large spike in successful authentication events. This can be due to password spraying, user enumeration or brute force activity. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |8.3.0 |103
+|<<spike-in-firewall-denies, Spike in Firewall Denies>> |A machine learning job detected an unusually large spike in network traffic that was denied by network access control lists (ACLs) or firewall rules. Such a burst of denied traffic is usually caused by either 1) a mis-configured application or firewall or 2) suspicious or malicious activity. Unsuccessful attempts at network transit, in order to connect to command-and-control (C2), or engage in data exfiltration, may produce a burst of failed connections. This could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |None |103
 
-|<<spike-in-network-traffic, Spike in Network Traffic>> |A machine learning job detected an unusually large spike in network traffic. Such a burst of traffic, if not caused by a surge in business activity, can be due to suspicious or malicious activity. Large-scale data exfiltration may produce a burst of network traffic; this could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |8.3.0 |103
+|<<spike-in-logon-events, Spike in Logon Events>> |A machine learning job found an unusually large spike in successful authentication events. This can be due to password spraying, user enumeration or brute force activity. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |None |103
 
-|<<spike-in-network-traffic-to-a-country, Spike in Network Traffic To a Country>> |A machine learning job detected an unusually large spike in network activity to one destination country in the network logs. This could be due to unusually large amounts of reconnaissance or enumeration traffic. Data exfiltration activity may also produce such a surge in traffic to a destination country that does not normally appear in network traffic or business workflows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |8.3.0 |104
+|<<spike-in-network-traffic, Spike in Network Traffic>> |A machine learning job detected an unusually large spike in network traffic. Such a burst of traffic, if not caused by a surge in business activity, can be due to suspicious or malicious activity. Large-scale data exfiltration may produce a burst of network traffic; this could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |None |103
 
-|<<spike-in-number-of-connections-made-from-a-source-ip, Spike in Number of Connections Made from a Source IP>> |A machine learning job has detected a high count of destination IPs establishing an RDP connection with a single source IP. Once an attacker has gained access to one system, they might attempt to access more in the network in search of valuable assets, data, or further access points. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<spike-in-network-traffic-to-a-country, Spike in Network Traffic To a Country>> |A machine learning job detected an unusually large spike in network activity to one destination country in the network logs. This could be due to unusually large amounts of reconnaissance or enumeration traffic. Data exfiltration activity may also produce such a surge in traffic to a destination country that does not normally appear in network traffic or business workflows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |None |104
 
-|<<spike-in-number-of-connections-made-to-a-destination-ip, Spike in Number of Connections Made to a Destination IP>> |A machine learning job has detected a high count of source IPs establishing an RDP connection with a single destination IP. Attackers might use multiple compromised systems to attack a target to ensure redundancy in case a source IP gets detected and blocked. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<spike-in-number-of-connections-made-from-a-source-ip, Spike in Number of Connections Made from a Source IP>> |A machine learning job has detected a high count of destination IPs establishing an RDP connection with a single source IP. Once an attacker has gained access to one system, they might attempt to access more in the network in search of valuable assets, data, or further access points. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<spike-in-number-of-processes-in-an-rdp-session, Spike in Number of Processes in an RDP Session>> |A machine learning job has detected unusually high number of processes started in a single RDP session. Executing a large number of processes remotely on other machines can be an indicator of lateral movement activity. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<spike-in-number-of-connections-made-to-a-destination-ip, Spike in Number of Connections Made to a Destination IP>> |A machine learning job has detected a high count of source IPs establishing an RDP connection with a single destination IP. Attackers might use multiple compromised systems to attack a target to ensure redundancy in case a source IP gets detected and blocked. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<spike-in-remote-file-transfers, Spike in Remote File Transfers>> |A machine learning job has detected an abnormal volume of remote files shared on the host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Attackers might perform multiple small transfers to match normal egress activity in the network, to evade detection. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<spike-in-number-of-processes-in-an-rdp-session, Spike in Number of Processes in an RDP Session>> |A machine learning job has detected unusually high number of processes started in a single RDP session. Executing a large number of processes remotely on other machines can be an indicator of lateral movement activity. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<spike-in-successful-logon-events-from-a-source-ip, Spike in Successful Logon Events from a Source IP>> |A machine learning job found an unusually large spike in successful authentication events from a particular source IP address. This can be due to password spraying, user enumeration or brute force activity. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access], [Tactic: Defense Evasion], [Resources: Investigation Guide] |8.3.0 |104
+|<<spike-in-remote-file-transfers, Spike in Remote File Transfers>> |A machine learning job has detected an abnormal volume of remote files shared on the host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Attackers might perform multiple small transfers to match normal egress activity in the network, to evade detection. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<startup-folder-persistence-via-unsigned-process, Startup Folder Persistence via Unsigned Process>> |Identifies files written or modified in the startup folder by unsigned processes. Adversaries may abuse this technique to maintain persistence in an environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |109
+|<<spike-in-successful-logon-events-from-a-source-ip, Spike in Successful Logon Events from a Source IP>> |A machine learning job found an unusually large spike in successful authentication events from a particular source IP address. This can be due to password spraying, user enumeration or brute force activity. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access], [Tactic: Defense Evasion], [Resources: Investigation Guide] |None |104
 
-|<<startup-persistence-by-a-suspicious-process, Startup Persistence by a Suspicious Process>> |Identifies files written to or modified in the startup folder by commonly abused processes. Adversaries may use this technique to maintain persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<startup-folder-persistence-via-unsigned-process, Startup Folder Persistence via Unsigned Process>> |Identifies files written or modified in the startup folder by unsigned processes. Adversaries may abuse this technique to maintain persistence in an environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |109
 
-|<<startup-or-run-key-registry-modification, Startup or Run Key Registry Modification>> |Identifies run key or startup key registry modifications. In order to survive reboots and other system interrupts, attackers will modify run keys within the registry or leverage startup folder items as a form of persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<startup-persistence-by-a-suspicious-process, Startup Persistence by a Suspicious Process>> |Identifies files written to or modified in the startup folder by commonly abused processes. Adversaries may use this technique to maintain persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<startup-logon-script-added-to-group-policy-object, Startup/Logon Script added to Group Policy Object>> |Detects the modification of Group Policy Objects (GPO) to add a startup/logon script to users or computer objects. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |8.3.0 |109
+|<<startup-or-run-key-registry-modification, Startup or Run Key Registry Modification>> |Identifies run key or startup key registry modifications. In order to survive reboots and other system interrupts, attackers will modify run keys within the registry or leverage startup folder items as a form of persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<statistical-model-detected-c2-beaconing-activity, Statistical Model Detected C2 Beaconing Activity>> |A statistical model has identified command-and-control (C2) beaconing activity. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network. |[Domain: Network], [Use Case: C2 Beaconing Detection], [Tactic: Command and Control] |8.10.1 |4
+|<<startup-logon-script-added-to-group-policy-object, Startup/Logon Script added to Group Policy Object>> |Detects the modification of Group Policy Objects (GPO) to add a startup/logon script to users or computer objects. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |None |109
 
-|<<statistical-model-detected-c2-beaconing-activity-with-high-confidence, Statistical Model Detected C2 Beaconing Activity with High Confidence>> |A statistical model has identified command-and-control (C2) beaconing activity with high confidence. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network. |[Domain: Network], [Use Case: C2 Beaconing Detection], [Tactic: Command and Control] |8.10.1 |4
+|<<statistical-model-detected-c2-beaconing-activity, Statistical Model Detected C2 Beaconing Activity>> |A statistical model has identified command-and-control (C2) beaconing activity. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network. |[Domain: Network], [Use Case: C2 Beaconing Detection], [Tactic: Command and Control] |8.10.1 |5
+
+|<<statistical-model-detected-c2-beaconing-activity-with-high-confidence, Statistical Model Detected C2 Beaconing Activity with High Confidence>> |A statistical model has identified command-and-control (C2) beaconing activity with high confidence. Beaconing can help attackers maintain stealthy communication with their C2 servers, receive instructions and payloads, exfiltrate data and maintain persistence in a network. |[Domain: Network], [Use Case: C2 Beaconing Detection], [Tactic: Command and Control] |8.10.1 |5
 
 |<<stolen-credentials-used-to-login-to-okta-account-after-mfa-reset, Stolen Credentials Used to Login to Okta Account After MFA Reset>> |Detects a sequence of suspicious activities on Windows hosts indicative of credential compromise, followed by efforts to undermine multi-factor authentication (MFA) and single sign-on (SSO) mechanisms for an Okta user account. |[Tactic: Persistence], [Use Case: Identity and Access Audit], [Data Source: Okta], [Data Source: Elastic Defend], [Rule Type: Higher-Order Rule], [Domain: Endpoint], [Domain: Cloud] |8.10.0 |1
 
-|<<sublime-plugin-or-application-script-modification, Sublime Plugin or Application Script Modification>> |Adversaries may create or modify the Sublime application plugins or scripts to execute a malicious payload each time the Sublime application is started. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |107
+|<<sublime-plugin-or-application-script-modification, Sublime Plugin or Application Script Modification>> |Adversaries may create or modify the Sublime application plugins or scripts to execute a malicious payload each time the Sublime application is started. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |107
 
-|<<sudo-command-enumeration-detected, Sudo Command Enumeration Detected>> |This rule monitors for the usage of the sudo -l command, which is used to list the allowed and forbidden commands for the invoking user. Attackers may execute this command to enumerate commands allowed to be executed with sudo permissions, potentially allowing to escalate privileges to root. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |8.3.0 |5
+|<<sudo-command-enumeration-detected, Sudo Command Enumeration Detected>> |This rule monitors for the usage of the sudo -l command, which is used to list the allowed and forbidden commands for the invoking user. Attackers may execute this command to enumerate commands allowed to be executed with sudo permissions, potentially allowing to escalate privileges to root. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |None |5
 
-|<<sudo-heap-based-buffer-overflow-attempt, Sudo Heap-Based Buffer Overflow Attempt>> |Identifies the attempted use of a heap-based buffer overflow vulnerability for the Sudo binary in Unix-like systems (CVE-2021-3156). Successful exploitation allows an unprivileged user to escalate to the root user. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |104
+|<<sudo-heap-based-buffer-overflow-attempt, Sudo Heap-Based Buffer Overflow Attempt>> |Identifies the attempted use of a heap-based buffer overflow vulnerability for the Sudo binary in Unix-like systems (CVE-2021-3156). Successful exploitation allows an unprivileged user to escalate to the root user. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |104
 
-|<<sudoers-file-modification, Sudoers File Modification>> |A sudoers file specifies the commands that users or groups can run and from which terminals. Adversaries can take advantage of these configurations to execute commands as other users or spawn processes with higher privileges. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.6.0 |204
+|<<sudoers-file-modification, Sudoers File Modification>> |A sudoers file specifies the commands that users or groups can run and from which terminals. Adversaries can take advantage of these configurations to execute commands as other users or spawn processes with higher privileges. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |204
 
-|<<suspicious-net-code-compilation, Suspicious .NET Code Compilation>> |Identifies executions of .NET compilers with suspicious parent processes, which can indicate an attacker's attempt to compile code after delivery in order to bypass security mechanisms. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<suspicious-net-code-compilation, Suspicious .NET Code Compilation>> |Identifies executions of .NET compilers with suspicious parent processes, which can indicate an attacker's attempt to compile code after delivery in order to bypass security mechanisms. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
 |<<suspicious-net-reflection-via-powershell, Suspicious .NET Reflection via PowerShell>> |Detects the use of Reflection.Assembly to load PEs and DLLs in memory in PowerShell scripts. Attackers use this method to load executables and DLLs without writing to the disk, bypassing security solutions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |112
 
-|<<suspicious-proc-maps-discovery, Suspicious /proc/maps Discovery>> |Monitors for /proc/*/maps file reads. The /proc/*/maps file in Linux provides a memory map for a specific process, detailing the memory segments, permissions, and what files are mapped to these segments. Attackers may read a process's memory map to identify memory addresses for code injection or process hijacking. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |8.3.0 |2
+|<<suspicious-proc-maps-discovery, Suspicious /proc/maps Discovery>> |Monitors for /proc/*/maps file reads. The /proc/*/maps file in Linux provides a memory map for a specific process, detailing the memory segments, permissions, and what files are mapped to these segments. Attackers may read a process's memory map to identify memory addresses for code injection or process hijacking. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |None |2
 
-|<<suspicious-apt-package-manager-execution, Suspicious APT Package Manager Execution>> |Detects suspicious process events executed by the APT package manager, potentially indicating persistence through an APT backdoor. In Linux, APT (Advanced Package Tool) is a command-line utility used for handling packages on Debian-based systems, providing functions for installing, updating, upgrading, and removing software along with managing package repositories. Attackers can backdoor APT to gain persistence by injecting malicious code into scripts that APT runs, thereby ensuring continued unauthorized access or control each time APT is used for package management. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |2
+|<<suspicious-apt-package-manager-execution, Suspicious APT Package Manager Execution>> |Detects suspicious process events executed by the APT package manager, potentially indicating persistence through an APT backdoor. In Linux, APT (Advanced Package Tool) is a command-line utility used for handling packages on Debian-based systems, providing functions for installing, updating, upgrading, and removing software along with managing package repositories. Attackers can backdoor APT to gain persistence by injecting malicious code into scripts that APT runs, thereby ensuring continued unauthorized access or control each time APT is used for package management. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |2
 
-|<<suspicious-apt-package-manager-network-connection, Suspicious APT Package Manager Network Connection>> |Detects suspicious network events executed by the APT package manager, potentially indicating persistence through an APT backdoor. In Linux, APT (Advanced Package Tool) is a command-line utility used for handling packages on Debian-based systems, providing functions for installing, updating, upgrading, and removing software along with managing package repositories. Attackers can backdoor APT to gain persistence by injecting malicious code into scripts that APT runs, thereby ensuring continued unauthorized access or control each time APT is used for package management. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Command and Control], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |2
+|<<suspicious-apt-package-manager-network-connection, Suspicious APT Package Manager Network Connection>> |Detects suspicious network events executed by the APT package manager, potentially indicating persistence through an APT backdoor. In Linux, APT (Advanced Package Tool) is a command-line utility used for handling packages on Debian-based systems, providing functions for installing, updating, upgrading, and removing software along with managing package repositories. Attackers can backdoor APT to gain persistence by injecting malicious code into scripts that APT runs, thereby ensuring continued unauthorized access or control each time APT is used for package management. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Command and Control], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |2
 
-|<<suspicious-access-to-ldap-attributes, Suspicious Access to LDAP Attributes>> |Identify read access to a high number of Active Directory object attributes. The knowledge of objects properties can help adversaries find vulnerabilities, elevate privileges or collect sensitive information. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: System], [Data Source: Active Directory], [Data Source: Windows] |8.3.0 |1
+|<<suspicious-access-to-ldap-attributes, Suspicious Access to LDAP Attributes>> |Identify read access to a high number of Active Directory object attributes. The knowledge of objects properties can help adversaries find vulnerabilities, elevate privileges or collect sensitive information. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: System], [Data Source: Active Directory], [Data Source: Windows] |None |1
 
 |<<suspicious-activity-reported-by-okta-user, Suspicious Activity Reported by Okta User>> |Detects when a user reports suspicious activity for their Okta account. These events should be investigated, as they can help security teams identify when an adversary is attempting to gain access to their network. |[Use Case: Identity and Access Audit], [Data Source: Okta], [Tactic: Initial Access] |8.10.0 |205
 
-|<<suspicious-antimalware-scan-interface-dll, Suspicious Antimalware Scan Interface DLL>> |Identifies the creation of the Antimalware Scan Interface (AMSI) DLL in an unusual location. This may indicate an attempt to bypass AMSI by loading a rogue AMSI module instead of the legit one. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |9
+|<<suspicious-antimalware-scan-interface-dll, Suspicious Antimalware Scan Interface DLL>> |Identifies the creation of the Antimalware Scan Interface (AMSI) DLL in an unusual location. This may indicate an attempt to bypass AMSI by loading a rogue AMSI module instead of the legit one. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |111
+
+|<<suspicious-automator-workflows-execution, Suspicious Automator Workflows Execution>> |Identifies the execution of the Automator Workflows process followed by a network connection from it's XPC service. Adversaries may drop a custom workflow template that hosts malicious JavaScript for Automation (JXA) code as an alternative to using osascript. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |None |106
 
-|<<suspicious-automator-workflows-execution, Suspicious Automator Workflows Execution>> |Identifies the execution of the Automator Workflows process followed by a network connection from it's XPC service. Adversaries may drop a custom workflow template that hosts malicious JavaScript for Automation (JXA) code as an alternative to using osascript. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |106
+|<<suspicious-browser-child-process, Suspicious Browser Child Process>> |Identifies the execution of a suspicious browser child process. Adversaries may gain access to a system through a user visiting a website over the normal course of browsing. With this technique, the user's web browser is typically targeted for exploitation. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Defend] |None |107
 
-|<<suspicious-browser-child-process, Suspicious Browser Child Process>> |Identifies the execution of a suspicious browser child process. Adversaries may gain access to a system through a user visiting a website over the normal course of browsing. With this technique, the user's web browser is typically targeted for exploitation. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |107
+|<<suspicious-calendar-file-modification, Suspicious Calendar File Modification>> |Identifies suspicious modifications of the calendar file by an unusual process. Adversaries may create a custom calendar notification procedure to execute a malicious program at a recurring interval to establish persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<suspicious-calendar-file-modification, Suspicious Calendar File Modification>> |Identifies suspicious modifications of the calendar file by an unusual process. Adversaries may create a custom calendar notification procedure to execute a malicious program at a recurring interval to establish persistence. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<suspicious-certutil-commands, Suspicious CertUtil Commands>> |Identifies suspicious commands being used with certutil.exe. CertUtil is a native Windows component which is part of Certificate Services. CertUtil is often abused by attackers to live off the land for stealthier command and control or data exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |108
 
-|<<suspicious-certutil-commands, Suspicious CertUtil Commands>> |Identifies suspicious commands being used with certutil.exe. CertUtil is a native Windows component which is part of Certificate Services. CertUtil is often abused by attackers to live off the land for stealthier command and control or data exfiltration. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |108
+|<<suspicious-child-process-of-adobe-acrobat-reader-update-service, Suspicious Child Process of Adobe Acrobat Reader Update Service>> |Detects attempts to exploit privilege escalation vulnerabilities related to the Adobe Acrobat Reader PrivilegedHelperTool responsible for installing updates. For more information, refer to CVE-2020-9615, CVE-2020-9614 and CVE-2020-9613 and verify that the impacted system is patched. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |106
 
-|<<suspicious-child-process-of-adobe-acrobat-reader-update-service, Suspicious Child Process of Adobe Acrobat Reader Update Service>> |Detects attempts to exploit privilege escalation vulnerabilities related to the Adobe Acrobat Reader PrivilegedHelperTool responsible for installing updates. For more information, refer to CVE-2020-9615, CVE-2020-9614 and CVE-2020-9613 and verify that the impacted system is patched. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |106
+|<<suspicious-cmd-execution-via-wmi, Suspicious Cmd Execution via WMI>> |Identifies suspicious command execution (cmd) via Windows Management Instrumentation (WMI) on a remote host. This could be indicative of adversary lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<suspicious-cmd-execution-via-wmi, Suspicious Cmd Execution via WMI>> |Identifies suspicious command execution (cmd) via Windows Management Instrumentation (WMI) on a remote host. This could be indicative of adversary lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<suspicious-communication-app-child-process, Suspicious Communication App Child Process>> |Identifies suspicious child processes of communications apps, which can indicate a potential masquerading as the communication app or the exploitation of a vulnerability on the application causing it to execute code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Elastic Defend] |None |4
 
-|<<suspicious-communication-app-child-process, Suspicious Communication App Child Process>> |Identifies suspicious child processes of communications apps, which can indicate a potential masquerading as the communication app or the exploitation of a vulnerability on the application causing it to execute code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |4
+|<<suspicious-content-extracted-or-decompressed-via-funzip, Suspicious Content Extracted or Decompressed via Funzip>> |Identifies when suspicious content is extracted from a file and subsequently decompressed using the funzip utility. Malware may execute the tail utility using the "-c" option to read a sequence of bytes from the end of a file. The output from tail can be piped to funzip in order to decompress malicious code before it is executed. This behavior is consistent with malware families such as Bundlore. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |5
 
-|<<suspicious-content-extracted-or-decompressed-via-funzip, Suspicious Content Extracted or Decompressed via Funzip>> |Identifies when suspicious content is extracted from a file and subsequently decompressed using the funzip utility. Malware may execute the tail utility using the "-c" option to read a sequence of bytes from the end of a file. The output from tail can be piped to funzip in order to decompress malicious code before it is executed. This behavior is consistent with malware families such as Bundlore. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |5
+|<<suspicious-crontab-creation-or-modification, Suspicious CronTab Creation or Modification>> |Identifies attempts to create or modify a crontab via a process that is not crontab (i.e python, osascript, etc.). This activity should not be highly prevalent and could indicate the use of cron as a persistence mechanism by a threat actor. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<suspicious-crontab-creation-or-modification, Suspicious CronTab Creation or Modification>> |Identifies attempts to create or modify a crontab via a process that is not crontab (i.e python, osascript, etc.). This activity should not be highly prevalent and could indicate the use of cron as a persistence mechanism by a threat actor. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<suspicious-dll-loaded-for-persistence-or-privilege-escalation, Suspicious DLL Loaded for Persistence or Privilege Escalation>> |Identifies the loading of a non Microsoft signed DLL that is missing on a default Windows install (phantom DLL) or one that can be loaded from a different location by a native Windows process. This may be abused to persist or elevate privileges via privileged file write vulnerabilities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<suspicious-dll-loaded-for-persistence-or-privilege-escalation, Suspicious DLL Loaded for Persistence or Privilege Escalation>> |Identifies the loading of a non Microsoft signed DLL that is missing on a default Windows install (phantom DLL) or one that can be loaded from a different location by a native Windows process. This may be abused to persist or elevate privileges via privileged file write vulnerabilities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<suspicious-data-encryption-via-openssl-utility, Suspicious Data Encryption via OpenSSL Utility>> |Identifies when the openssl command-line utility is used to encrypt multiple files on a host within a short time window. Adversaries may encrypt data on a single or multiple systems in order to disrupt the availability of their target's data and may attempt to hold the organization's data to ransom for the purposes of extortion. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend] |None |6
 
-|<<suspicious-data-encryption-via-openssl-utility, Suspicious Data Encryption via OpenSSL Utility>> |Identifies when the openssl command-line utility is used to encrypt multiple files on a host within a short time window. Adversaries may encrypt data on a single or multiple systems in order to disrupt the availability of their target's data and may attempt to hold the organization's data to ransom for the purposes of extortion. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend] |8.3.0 |6
+|<<suspicious-dynamic-linker-discovery-via-od, Suspicious Dynamic Linker Discovery via od>> |Monitors for dynamic linker discovery via the od utility. od (octal dump) is a command-line utility in Unix operating systems used for displaying data in various formats, including octal, hexadecimal, decimal, and ASCII, primarily used for examining and debugging binary files or data streams. Attackers can leverage od to analyze the dynamic linker by identifying injection points and craft exploits based on the observed behaviors and structures within these files. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |2
 
-|<<suspicious-dynamic-linker-discovery-via-od, Suspicious Dynamic Linker Discovery via od>> |Monitors for dynamic linker discovery via the od utility. od (octal dump) is a command-line utility in Unix operating systems used for displaying data in various formats, including octal, hexadecimal, decimal, and ASCII, primarily used for examining and debugging binary files or data streams. Attackers can leverage od to analyze the dynamic linker by identifying injection points and craft exploits based on the observed behaviors and structures within these files. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |2
+|<<suspicious-emond-child-process, Suspicious Emond Child Process>> |Identifies the execution of a suspicious child process of the Event Monitor Daemon (emond). Adversaries may abuse this service by writing a rule to execute commands when a defined event occurs, such as system start up or user authentication. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |106
 
-|<<suspicious-emond-child-process, Suspicious Emond Child Process>> |Identifies the execution of a suspicious child process of the Event Monitor Daemon (emond). Adversaries may abuse this service by writing a rule to execute commands when a defined event occurs, such as system start up or user authentication. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |106
+|<<suspicious-endpoint-security-parent-process, Suspicious Endpoint Security Parent Process>> |A suspicious Endpoint Security parent process was detected. This may indicate a process hollowing or other form of code injection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<suspicious-endpoint-security-parent-process, Suspicious Endpoint Security Parent Process>> |A suspicious Endpoint Security parent process was detected. This may indicate a process hollowing or other form of code injection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<suspicious-execution-from-inet-cache, Suspicious Execution from INET Cache>> |Identifies the execution of a process with arguments pointing to the INetCache Folder. Adversaries may deliver malicious content via WININET during initial access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |2
 
-|<<suspicious-execution-from-inet-cache, Suspicious Execution from INET Cache>> |Identifies the execution of a process with arguments pointing to the INetCache Folder. Adversaries may deliver malicious content via WININET during initial access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |2
+|<<suspicious-execution-from-a-mounted-device, Suspicious Execution from a Mounted Device>> |Identifies when a script interpreter or signed binary is launched via a non-standard working directory. An attacker may use this technique to evade defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<suspicious-execution-from-a-mounted-device, Suspicious Execution from a Mounted Device>> |Identifies when a script interpreter or signed binary is launched via a non-standard working directory. An attacker may use this technique to evade defenses. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<suspicious-execution-via-msiexec, Suspicious Execution via MSIEXEC>> |Identifies suspicious execution of the built-in Windows Installer, msiexec.exe, to install a package from usual paths or parent process. Adversaries may abuse msiexec.exe to launch malicious local MSI files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |2
 
-|<<suspicious-execution-via-msiexec, Suspicious Execution via MSIEXEC>> |Identifies suspicious execution of the built-in Windows Installer, msiexec.exe, to install a package from usual paths or parent process. Adversaries may abuse msiexec.exe to launch malicious local MSI files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<suspicious-execution-via-microsoft-office-add-ins, Suspicious Execution via Microsoft Office Add-Ins>> |Identifies execution of common Microsoft Office applications to launch an Office Add-In from a suspicious path or with an unusual parent process. This may indicate an attempt to get initial access via a malicious phishing MS Office Add-In. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |5
 
-|<<suspicious-execution-via-microsoft-office-add-ins, Suspicious Execution via Microsoft Office Add-Ins>> |Identifies execution of common Microsoft Office applications to launch an Office Add-In from a suspicious path or with an unusual parent process. This may indicate an attempt to get initial access via a malicious phishing MS Office Add-In. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |5
+|<<suspicious-execution-via-scheduled-task, Suspicious Execution via Scheduled Task>> |Identifies execution of a suspicious program via scheduled tasks by looking at process lineage and command line usage. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Defend] |None |108
 
-|<<suspicious-execution-via-scheduled-task, Suspicious Execution via Scheduled Task>> |Identifies execution of a suspicious program via scheduled tasks by looking at process lineage and command line usage. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Defend] |8.3.0 |108
+|<<suspicious-execution-via-windows-subsystem-for-linux, Suspicious Execution via Windows Subsystem for Linux>> |Detects Linux Bash commands from the the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |6
 
-|<<suspicious-execution-via-windows-subsystem-for-linux, Suspicious Execution via Windows Subsystem for Linux>> |Detects Linux Bash commands from the the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |6
+|<<suspicious-explorer-child-process, Suspicious Explorer Child Process>> |Identifies a suspicious Windows explorer child process. Explorer.exe can be abused to launch malicious scripts or executables from a trusted parent process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<suspicious-explorer-child-process, Suspicious Explorer Child Process>> |Identifies a suspicious Windows explorer child process. Explorer.exe can be abused to launch malicious scripts or executables from a trusted parent process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<suspicious-file-changes-activity-detected, Suspicious File Changes Activity Detected>> |This rule identifies a sequence of 100 file extension rename events within a set of common file paths by the same process in a timespan of 1 second. Ransomware is a type of malware that encrypts a victim's files or systems and demands payment (usually in cryptocurrency) in exchange for the decryption key. One important indicator of a ransomware attack is the mass encryption of the file system, after which a new file extension is added to the file. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend] |None |8
 
-|<<suspicious-file-changes-activity-detected, Suspicious File Changes Activity Detected>> |This rule identifies a sequence of 100 file extension rename events within a set of common file paths by the same process in a timespan of 1 second. Ransomware is a type of malware that encrypts a victim's files or systems and demands payment (usually in cryptocurrency) in exchange for the decryption key. One important indicator of a ransomware attack is the mass encryption of the file system, after which a new file extension is added to the file. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend] |8.3.0 |8
+|<<suspicious-file-creation-in-etc-for-persistence, Suspicious File Creation in /etc for Persistence>> |Detects the manual creation of files in specific etc directories, via user root, used by Linux malware to persist and elevate privileges on compromised systems. File creation in these directories should not be entirely common and could indicate a malicious binary or script installing persistence mechanisms for long term access. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Orbit], [Threat: Lightning Framework], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |114
 
-|<<suspicious-file-creation-in-etc-for-persistence, Suspicious File Creation in /etc for Persistence>> |Detects the manual creation of files in specific etc directories, via user root, used by Linux malware to persist and elevate privileges on compromised systems. File creation in these directories should not be entirely common and could indicate a malicious binary or script installing persistence mechanisms for long term access. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Threat: Orbit], [Threat: Lightning Framework], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |113
+|<<suspicious-file-creation-via-kworker, Suspicious File Creation via Kworker>> |This rule monitors for a file creation event originating from a kworker parent process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |4
 
-|<<suspicious-file-creation-via-kworker, Suspicious File Creation via Kworker>> |This rule monitors for a file creation event originating from a kworker parent process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |3
+|<<suspicious-file-downloaded-from-google-drive, Suspicious File Downloaded from Google Drive>> |Identifies suspicious file download activity from a Google Drive URL. This could indicate an attempt to deliver phishing payloads via a trusted webservice. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Command and Control] |None |3
 
-|<<suspicious-file-downloaded-from-google-drive, Suspicious File Downloaded from Google Drive>> |Identifies suspicious file download activity from a Google Drive URL. This could indicate an attempt to deliver phishing payloads via a trusted webservice. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Command and Control] |8.3.0 |3
+|<<suspicious-file-renamed-via-smb, Suspicious File Renamed via SMB>> |Identifies an incoming SMB connection followed by a suspicious file rename operation. This may indicate a remote ransomware attack via the SMB protocol. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |2
 
-|<<suspicious-file-renamed-via-smb, Suspicious File Renamed via SMB>> |Identifies an incoming SMB connection followed by a suspicious file rename operation. This may indicate a remote ransomware attack via the SMB protocol. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |1
+|<<suspicious-html-file-creation, Suspicious HTML File Creation>> |Identifies the execution of a browser process to open an HTML file with high entropy and size. Adversaries may smuggle data and files past content filters by hiding malicious payloads inside of seemingly benign HTML files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Defend] |None |107
 
-|<<suspicious-html-file-creation, Suspicious HTML File Creation>> |Identifies the execution of a browser process to open an HTML file with high entropy and size. Adversaries may smuggle data and files past content filters by hiding malicious payloads inside of seemingly benign HTML files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Defend] |8.3.0 |107
+|<<suspicious-hidden-child-process-of-launchd, Suspicious Hidden Child Process of Launchd>> |Identifies the execution of a launchd child process with a hidden file. An adversary can establish persistence by installing a new logon item, launch agent, or daemon that executes upon login. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |106
 
-|<<suspicious-hidden-child-process-of-launchd, Suspicious Hidden Child Process of Launchd>> |Identifies the execution of a launchd child process with a hidden file. An adversary can establish persistence by installing a new logon item, launch agent, or daemon that executes upon login. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |106
+|<<suspicious-image-load-taskschd-dll-from-ms-office, Suspicious Image Load (taskschd.dll) from MS Office>> |Identifies a suspicious image load (taskschd.dll) from Microsoft Office processes. This behavior may indicate adversarial activity where a scheduled task is configured via Windows Component Object Model (COM). This technique can be used to configure persistence and evade monitoring by avoiding the usage of the traditional Windows binary (schtasks.exe) used to manage scheduled tasks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<suspicious-image-load-taskschd-dll-from-ms-office, Suspicious Image Load (taskschd.dll) from MS Office>> |Identifies a suspicious image load (taskschd.dll) from Microsoft Office processes. This behavior may indicate adversarial activity where a scheduled task is configured via Windows Component Object Model (COM). This technique can be used to configure persistence and evade monitoring by avoiding the usage of the traditional Windows binary (schtasks.exe) used to manage scheduled tasks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<suspicious-imagepath-service-creation, Suspicious ImagePath Service Creation>> |Identifies the creation of a suspicious ImagePath value. This could be an indication of an adversary attempting to stealthily persist or escalate privileges through abnormal service creation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<suspicious-imagepath-service-creation, Suspicious ImagePath Service Creation>> |Identifies the creation of a suspicious ImagePath value. This could be an indication of an adversary attempting to stealthily persist or escalate privileges through abnormal service creation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<suspicious-inter-process-communication-via-outlook, Suspicious Inter-Process Communication via Outlook>> |Detects Inter-Process Communication with Outlook via Component Object Model from an unusual process. Adversaries may target user email to collect sensitive information or send email on their behalf via API. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend] |None |6
 
-|<<suspicious-inter-process-communication-via-outlook, Suspicious Inter-Process Communication via Outlook>> |Detects Inter-Process Communication with Outlook via Component Object Model from an unusual process. Adversaries may target user email to collect sensitive information or send email on their behalf via API. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Collection], [Data Source: Elastic Defend] |8.4.0 |6
+|<<suspicious-interactive-shell-spawned-from-inside-a-container, Suspicious Interactive Shell Spawned From Inside A Container>> |This rule detects when an interactive shell is spawned inside a running container. This could indicate a potential container breakout attempt or an attacker's attempt to gain unauthorized access to the underlying host. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |None |2
 
-|<<suspicious-interactive-shell-spawned-from-inside-a-container, Suspicious Interactive Shell Spawned From Inside A Container>> |This rule detects when an interactive shell is spawned inside a running container. This could indicate a potential container breakout attempt or an attacker's attempt to gain unauthorized access to the underlying host. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution] |8.8.0 |2
+|<<suspicious-java-child-process, Suspicious JAVA Child Process>> |Identifies suspicious child processes of the Java interpreter process. This may indicate an attempt to execute a malicious JAR file or an exploitation attempt via a JAVA specific vulnerability. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |208
 
-|<<suspicious-java-child-process, Suspicious JAVA Child Process>> |Identifies suspicious child processes of the Java interpreter process. This may indicate an attempt to execute a malicious JAR file or an exploitation attempt via a JAVA specific vulnerability. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.6.0 |208
+|<<suspicious-jetbrains-teamcity-child-process, Suspicious JetBrains TeamCity Child Process>> |Identifies suspicious processes being spawned by the JetBrain TeamCity process. This activity could be related to JetBrains remote code execution vulnerabilities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |1
 
-|<<suspicious-jetbrains-teamcity-child-process, Suspicious JetBrains TeamCity Child Process>> |Identifies suspicious processes being spawned by the JetBrain TeamCity process. This activity could be related to JetBrains remote code execution vulnerabilities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |1
+|<<suspicious-kworker-uid-elevation, Suspicious Kworker UID Elevation>> |Monitors for the elevation of regular user permissions to root permissions through the kworker process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process, and hijack the execution flow by hooking certain functions/syscalls through a rootkit in order to provide easy access to root via a special modified command. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |2
 
-|<<suspicious-kworker-uid-elevation, Suspicious Kworker UID Elevation>> |Monitors for the elevation of regular user permissions to root permissions through the kworker process. kworker, or kernel worker, processes are part of the kernel's workqueue mechanism. They are responsible for executing work that has been scheduled to be done in kernel space, which might include tasks like handling interrupts, background activities, and other kernel-related tasks. Attackers may attempt to evade detection by masquerading as a kernel worker process, and hijack the execution flow by hooking certain functions/syscalls through a rootkit in order to provide easy access to root via a special modified command. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<suspicious-lsass-access-via-malseclogon, Suspicious LSASS Access via MalSecLogon>> |Identifies suspicious access to LSASS handle from a call trace pointing to seclogon.dll and with a suspicious access rights value. This may indicate an attempt to leak an LSASS handle via abusing the Secondary Logon service in preparation for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |None |208
 
-|<<suspicious-lsass-access-via-malseclogon, Suspicious LSASS Access via MalSecLogon>> |Identifies suspicious access to LSASS handle from a call trace pointing to seclogon.dll and with a suspicious access rights value. This may indicate an attempt to leak an LSASS handle via abusing the Secondary Logon service in preparation for credential access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |8.8.0 |208
+|<<suspicious-lsass-process-access, Suspicious Lsass Process Access>> |Identifies access attempts to LSASS handle, this may indicate an attempt to dump credentials from Lsass memory. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |None |107
 
-|<<suspicious-lsass-process-access, Suspicious Lsass Process Access>> |Identifies access attempts to LSASS handle, this may indicate an attempt to dump credentials from Lsass memory. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Sysmon] |8.8.0 |107
+|<<suspicious-ms-office-child-process, Suspicious MS Office Child Process>> |Identifies suspicious child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, Excel). These child processes are often launched during exploitation of Office applications or from documents with malicious macros. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |112
 
-|<<suspicious-ms-office-child-process, Suspicious MS Office Child Process>> |Identifies suspicious child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, Excel). These child processes are often launched during exploitation of Office applications or from documents with malicious macros. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<suspicious-ms-outlook-child-process, Suspicious MS Outlook Child Process>> |Identifies suspicious child processes of Microsoft Outlook. These child processes are often associated with spear phishing activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne] |8.11.0 |213
 
-|<<suspicious-ms-outlook-child-process, Suspicious MS Outlook Child Process>> |Identifies suspicious child processes of Microsoft Outlook. These child processes are often associated with spear phishing activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<suspicious-managed-code-hosting-process, Suspicious Managed Code Hosting Process>> |Identifies a suspicious managed code hosting process which could indicate code injection or other form of suspicious code execution. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<suspicious-managed-code-hosting-process, Suspicious Managed Code Hosting Process>> |Identifies a suspicious managed code hosting process which could indicate code injection or other form of suspicious code execution. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<suspicious-memory-grep-activity, Suspicious Memory grep Activity>> |Monitors for grep activity related to memory mapping. The /proc/*/maps file in Linux provides a memory map for a specific process, detailing the memory segments, permissions, and what files are mapped to these segments. Attackers may read a process's memory map to identify memory addresses for code injection or process hijacking. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |2
 
-|<<suspicious-memory-grep-activity, Suspicious Memory grep Activity>> |Monitors for grep activity related to memory mapping. The /proc/*/maps file in Linux provides a memory map for a specific process, detailing the memory segments, permissions, and what files are mapped to these segments. Attackers may read a process's memory map to identify memory addresses for code injection or process hijacking. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<suspicious-microsoft-365-mail-access-by-clientappid, Suspicious Microsoft 365 Mail Access by ClientAppId>> |Identifies when a Microsoft 365 Mailbox is accessed by a ClientAppId that was observed for the fist time during the last 10 days. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |None |106
 
-|<<suspicious-microsoft-365-mail-access-by-clientappid, Suspicious Microsoft 365 Mail Access by ClientAppId>> |Identifies when a Microsoft 365 Mailbox is accessed by a ClientAppId that was observed for the fist time during the last 10 days. |[Domain: Cloud], [Data Source: Microsoft 365], [Use Case: Configuration Audit], [Tactic: Initial Access] |8.8.0 |105
+|<<suspicious-microsoft-diagnostics-wizard-execution, Suspicious Microsoft Diagnostics Wizard Execution>> |Identifies potential abuse of the Microsoft Diagnostics Troubleshooting Wizard (MSDT) to proxy malicious command or binary execution via malicious process arguments. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<suspicious-microsoft-diagnostics-wizard-execution, Suspicious Microsoft Diagnostics Wizard Execution>> |Identifies potential abuse of the Microsoft Diagnostics Troubleshooting Wizard (MSDT) to proxy malicious command or binary execution via malicious process arguments. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<suspicious-mining-process-creation-event, Suspicious Mining Process Creation Event>> |Identifies service creation events of common mining services, possibly indicating the infection of a system with a cryptominer. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |6
 
-|<<suspicious-mining-process-creation-event, Suspicious Mining Process Creation Event>> |Identifies service creation events of common mining services, possibly indicating the infection of a system with a cryptominer. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |6
+|<<suspicious-modprobe-file-event, Suspicious Modprobe File Event>> |Detects file events involving kernel modules in modprobe configuration files, which may indicate unauthorized access or manipulation of critical kernel modules. Attackers may tamper with the modprobe files to load malicious or unauthorized kernel modules, potentially bypassing security measures, escalating privileges, or hiding their activities within the system. |[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |None |107
 
-|<<suspicious-modprobe-file-event, Suspicious Modprobe File Event>> |Detects file events involving kernel modules in modprobe configuration files, which may indicate unauthorized access or manipulation of critical kernel modules. Attackers may tamper with the modprobe files to load malicious or unauthorized kernel modules, potentially bypassing security measures, escalating privileges, or hiding their activities within the system. |[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |8.6.0 |107
+|<<suspicious-module-loaded-by-lsass, Suspicious Module Loaded by LSASS>> |Identifies LSASS loading an unsigned or untrusted DLL. Windows Security Support Provider (SSP) DLLs are loaded into LSSAS process at system start. Once loaded into the LSA, SSP DLLs have access to encrypted and plaintext passwords that are stored in Windows, such as any logged-on user's Domain password or smart card PINs. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |8
 
-|<<suspicious-module-loaded-by-lsass, Suspicious Module Loaded by LSASS>> |Identifies LSASS loading an unsigned or untrusted DLL. Windows Security Support Provider (SSP) DLLs are loaded into LSSAS process at system start. Once loaded into the LSA, SSP DLLs have access to encrypted and plaintext passwords that are stored in Windows, such as any logged-on user's Domain password or smart card PINs. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.3.0 |8
+|<<suspicious-network-activity-to-the-internet-by-previously-unknown-executable, Suspicious Network Activity to the Internet by Previously Unknown Executable>> |This rule monitors for network connectivity to the internet from a previously unknown executable located in a suspicious directory. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to establish connections to unknown or suspicious destinations such as a command and control server. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |9
 
-|<<suspicious-network-activity-to-the-internet-by-previously-unknown-executable, Suspicious Network Activity to the Internet by Previously Unknown Executable>> |This rule monitors for network connectivity to the internet from a previously unknown executable located in a suspicious directory to a previously unknown destination ip. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to establish connections to unknown or suspicious destinations such as a command and control server. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |8
+|<<suspicious-network-connection-via-sudo-binary, Suspicious Network Connection via Sudo Binary>> |Detects network connections initiated by the "sudo" binary. This behavior is uncommon and may occur in instances where reverse shell shellcode is injected into a process run with elevated permissions via "sudo". Attackers may attempt to inject shellcode into processes running as root, to escalate privileges. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |2
 
-|<<suspicious-network-connection-via-sudo-binary, Suspicious Network Connection via Sudo Binary>> |Detects network connections initiated by the "sudo" binary. This behavior is uncommon and may occur in instances where reverse shell shellcode is injected into a process run with elevated permissions via "sudo". Attackers may attempt to inject shellcode into processes running as root, to escalate privileges. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<suspicious-network-connection-via-systemd, Suspicious Network Connection via systemd>> |Detects suspicious network events executed by systemd, potentially indicating persistence through a systemd backdoor. Systemd is a system and service manager for Linux operating systems, used to initialize and manage system processes. Attackers can backdoor systemd for persistence by creating or modifying systemd unit files to execute malicious scripts or commands, or by replacing legitimate systemd binaries with compromised ones, ensuring that their malicious code is automatically executed at system startup or during certain system events. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Command and Control], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |2
 
-|<<suspicious-network-connection-via-systemd, Suspicious Network Connection via systemd>> |Detects suspicious network events executed by systemd, potentially indicating persistence through a systemd backdoor. Systemd is a system and service manager for Linux operating systems, used to initialize and manage system processes. Attackers can backdoor systemd for persistence by creating or modifying systemd unit files to execute malicious scripts or commands, or by replacing legitimate systemd binaries with compromised ones, ensuring that their malicious code is automatically executed at system startup or during certain system events. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Command and Control], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |2
+|<<suspicious-network-tool-launched-inside-a-container, Suspicious Network Tool Launched Inside A Container>> |This rule detects commonly abused network utilities running inside a container. Network utilities like nc, nmap, dig, tcpdump, ngrep, telnet, mitmproxy, zmap can be used for malicious purposes such as network reconnaissance, monitoring, or exploitation, and should be monitored closely within a container. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Command and Control], [Tactic: Reconnaissance] |None |2
 
-|<<suspicious-network-tool-launched-inside-a-container, Suspicious Network Tool Launched Inside A Container>> |This rule detects commonly abused network utilities running inside a container. Network utilities like nc, nmap, dig, tcpdump, ngrep, telnet, mitmproxy, zmap can be used for malicious purposes such as network reconnaissance, monitoring, or exploitation, and should be monitored closely within a container. |[Data Source: Elastic Defend for Containers], [Domain: Container], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Command and Control], [Tactic: Reconnaissance] |8.8.0 |2
+|<<suspicious-pdf-reader-child-process, Suspicious PDF Reader Child Process>> |Identifies suspicious child processes of PDF reader applications. These child processes are often launched via exploitation of PDF applications or social engineering. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Initial Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<suspicious-pdf-reader-child-process, Suspicious PDF Reader Child Process>> |Identifies suspicious child processes of PDF reader applications. These child processes are often launched via exploitation of PDF applications or social engineering. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Initial Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<suspicious-passwd-file-event-action, Suspicious Passwd File Event Action>> |Monitors for the generation of a passwd password entry via openssl, followed by a file write activity on the "/etc/passwd" file. The "/etc/passwd" file in Linux stores user account information, including usernames, user IDs, group IDs, home directories, and default shell paths. Attackers may exploit a misconfiguration in the "/etc/passwd" file permissions or other privileges to add a new entry to the "/etc/passwd" file with root permissions, and leverage this new user account to login as root. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |3
 
-|<<suspicious-passwd-file-event-action, Suspicious Passwd File Event Action>> |Monitors for the generation of a passwd password entry via openssl, followed by a file write activity on the "/etc/passwd" file. The "/etc/passwd" file in Linux stores user account information, including usernames, user IDs, group IDs, home directories, and default shell paths. Attackers may exploit a misconfiguration in the "/etc/passwd" file permissions or other privileges to add a new entry to the "/etc/passwd" file with root permissions, and leverage this new user account to login as root. |[Data Source: Auditd Manager], [Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.3.0 |3
+|<<suspicious-portable-executable-encoded-in-powershell-script, Suspicious Portable Executable Encoded in Powershell Script>> |Detects the presence of a portable executable (PE) in a PowerShell script by looking for its encoded header. Attackers embed PEs into PowerShell scripts to inject them into memory, avoiding defences by not writing to disk. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |None |110
 
-|<<suspicious-portable-executable-encoded-in-powershell-script, Suspicious Portable Executable Encoded in Powershell Script>> |Detects the presence of a portable executable (PE) in a PowerShell script by looking for its encoded header. Attackers embed PEs into PowerShell scripts to inject them into memory, avoiding defences by not writing to disk. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: PowerShell Logs] |8.3.0 |110
+|<<suspicious-powershell-engine-imageload, Suspicious PowerShell Engine ImageLoad>> |Identifies the PowerShell engine being invoked by unexpected processes. Rather than executing PowerShell functionality with powershell.exe, some attackers do this to operate more stealthily. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |210
 
-|<<suspicious-powershell-engine-imageload, Suspicious PowerShell Engine ImageLoad>> |Identifies the PowerShell engine being invoked by unexpected processes. Rather than executing PowerShell functionality with powershell.exe, some attackers do this to operate more stealthily. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.6.0 |210
+|<<suspicious-powershell-script, Suspicious Powershell Script>> |A machine learning job detected a PowerShell script with unusual data characteristics, such as obfuscation, that may be a characteristic of malicious PowerShell script text blocks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Execution] |None |104
 
-|<<suspicious-powershell-script, Suspicious Powershell Script>> |A machine learning job detected a PowerShell script with unusual data characteristics, such as obfuscation, that may be a characteristic of malicious PowerShell script text blocks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Execution] |8.3.0 |104
+|<<suspicious-print-spooler-file-deletion, Suspicious Print Spooler File Deletion>> |Detects deletion of print driver files by an unusual process. This may indicate a clean up attempt post successful privilege escalation via Print Spooler service related vulnerabilities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<suspicious-print-spooler-file-deletion, Suspicious Print Spooler File Deletion>> |Detects deletion of print driver files by an unusual process. This may indicate a clean up attempt post successful privilege escalation via Print Spooler service related vulnerabilities. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<suspicious-print-spooler-point-and-print-dll, Suspicious Print Spooler Point and Print DLL>> |Detects attempts to exploit a privilege escalation vulnerability (CVE-2020-1030) related to the print spooler service. Exploitation involves chaining multiple primitives to load an arbitrary DLL into the print spooler process running as SYSTEM. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |106
 
-|<<suspicious-print-spooler-point-and-print-dll, Suspicious Print Spooler Point and Print DLL>> |Detects attempts to exploit a privilege escalation vulnerability (CVE-2020-1030) related to the print spooler service. Exploitation involves chaining multiple primitives to load an arbitrary DLL into the print spooler process running as SYSTEM. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |106
+|<<suspicious-print-spooler-spl-file-created, Suspicious Print Spooler SPL File Created>> |Detects attempts to exploit privilege escalation vulnerabilities related to the Print Spooler service including CVE-2020-1048 and CVE-2020-1337. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |111
 
-|<<suspicious-print-spooler-spl-file-created, Suspicious Print Spooler SPL File Created>> |Detects attempts to exploit privilege escalation vulnerabilities related to the Print Spooler service including CVE-2020-1048 and CVE-2020-1337. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |111
+|<<suspicious-printspooler-service-executable-file-creation, Suspicious PrintSpooler Service Executable File Creation>> |Detects attempts to exploit privilege escalation vulnerabilities related to the Print Spooler service. For more information refer to the following CVE's - CVE-2020-1048, CVE-2020-1337 and CVE-2020-1300 and verify that the impacted system is patched. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<suspicious-printspooler-service-executable-file-creation, Suspicious PrintSpooler Service Executable File Creation>> |Detects attempts to exploit privilege escalation vulnerabilities related to the Print Spooler service. For more information refer to the following CVE's - CVE-2020-1048, CVE-2020-1337 and CVE-2020-1300 and verify that the impacted system is patched. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<suspicious-proc-pseudo-file-system-enumeration, Suspicious Proc Pseudo File System Enumeration>> |This rule monitors for a rapid enumeration of 25 different proc cmd, stat, and exe files, which suggests an abnormal activity pattern. Such behavior could be an indicator of a malicious process scanning or gathering information about running processes, potentially for reconnaissance, privilege escalation, or identifying vulnerable targets. |[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |None |7
 
-|<<suspicious-proc-pseudo-file-system-enumeration, Suspicious Proc Pseudo File System Enumeration>> |This rule monitors for a rapid enumeration of 25 different proc cmd, stat, and exe files, which suggests an abnormal activity pattern. Such behavior could be an indicator of a malicious process scanning or gathering information about running processes, potentially for reconnaissance, privilege escalation, or identifying vulnerable targets. |[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |8.3.0 |7
+|<<suspicious-process-access-via-direct-system-call, Suspicious Process Access via Direct System Call>> |Identifies suspicious process access events from an unknown memory region. Endpoint security solutions usually hook userland Windows APIs in order to decide if the code that is being executed is malicious or not. It's possible to bypass hooked functions by writing malicious functions that call syscalls directly. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Sysmon] |None |211
 
-|<<suspicious-process-access-via-direct-system-call, Suspicious Process Access via Direct System Call>> |Identifies suspicious process access events from an unknown memory region. Endpoint security solutions usually hook userland Windows APIs in order to decide if the code that is being executed is malicious or not. It's possible to bypass hooked functions by writing malicious functions that call syscalls directly. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Sysmon] |8.8.0 |211
+|<<suspicious-process-creation-calltrace, Suspicious Process Creation CallTrace>> |Identifies when a process is created and immediately accessed from an unknown memory code region and by the same parent process. This may indicate a code injection attempt. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Sysmon] |None |208
 
-|<<suspicious-process-creation-calltrace, Suspicious Process Creation CallTrace>> |Identifies when a process is created and immediately accessed from an unknown memory code region and by the same parent process. This may indicate a code injection attempt. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Sysmon] |8.8.0 |208
+|<<suspicious-process-execution-via-renamed-psexec-executable, Suspicious Process Execution via Renamed PsExec Executable>> |Identifies suspicious psexec activity which is executing from the psexec service that has been renamed, possibly to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<suspicious-process-execution-via-renamed-psexec-executable, Suspicious Process Execution via Renamed PsExec Executable>> |Identifies suspicious psexec activity which is executing from the psexec service that has been renamed, possibly to evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<suspicious-process-spawned-from-motd-detected, Suspicious Process Spawned from MOTD Detected>> |Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" and "/usr/lib/update-notifier/" directories. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. This rule detects the execution of potentially malicious processes through the MOTD utility. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |9
 
-|<<suspicious-process-spawned-from-motd-detected, Suspicious Process Spawned from MOTD Detected>> |Message of the day (MOTD) is the message that is presented to the user when a user connects to a Linux server via SSH or a serial connection. Linux systems contain several default MOTD files located in the "/etc/update-motd.d/" and "/usr/lib/update-notifier/" directories. These scripts run as the root user every time a user connects over SSH or a serial connection. Adversaries may create malicious MOTD files that grant them persistence onto the target every time a user connects to the system by executing a backdoor script or command. This rule detects the execution of potentially malicious processes through the MOTD utility. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |8
+|<<suspicious-rdp-activex-client-loaded, Suspicious RDP ActiveX Client Loaded>> |Identifies suspicious Image Loading of the Remote Desktop Services ActiveX Client (mstscax), this may indicate the presence of RDP lateral movement capability. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<suspicious-rdp-activex-client-loaded, Suspicious RDP ActiveX Client Loaded>> |Identifies suspicious Image Loading of the Remote Desktop Services ActiveX Client (mstscax), this may indicate the presence of RDP lateral movement capability. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<suspicious-remote-registry-access-via-sebackupprivilege, Suspicious Remote Registry Access via SeBackupPrivilege>> |Identifies remote access to the registry using an account with Backup Operators group membership. This may indicate an attempt to exfiltrate credentials by dumping the Security Account Manager (SAM) registry hive in preparation for credential access and privileges elevation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Credential Access], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |None |110
 
-|<<suspicious-remote-registry-access-via-sebackupprivilege, Suspicious Remote Registry Access via SeBackupPrivilege>> |Identifies remote access to the registry using an account with Backup Operators group membership. This may indicate an attempt to exfiltrate credentials by dumping the Security Account Manager (SAM) registry hive in preparation for credential access and privileges elevation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Credential Access], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |8.3.0 |110
+|<<suspicious-renaming-of-esxi-files, Suspicious Renaming of ESXI Files>> |Identifies instances where VMware-related files, such as those with extensions like ".vmdk", ".vmx", ".vmxf", ".vmsd", ".vmsn", ".vswp", ".vmss", ".nvram", and ".vmem", are renamed on a Linux system. The rule monitors for the "rename" event action associated with these file types, which could indicate malicious activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |6
 
-|<<suspicious-renaming-of-esxi-files, Suspicious Renaming of ESXI Files>> |Identifies instances where VMware-related files, such as those with extensions like ".vmdk", ".vmx", ".vmxf", ".vmsd", ".vmsn", ".vswp", ".vmss", ".nvram", and ".vmem", are renamed on a Linux system. The rule monitors for the "rename" event action associated with these file types, which could indicate malicious activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.5.0 |6
+|<<suspicious-renaming-of-esxi-index-html-file, Suspicious Renaming of ESXI index.html File>> |Identifies instances where the "index.html" file within the "/usr/lib/vmware/*" directory is renamed on a Linux system. The rule monitors for the "rename" event action associated with this specific file and path, which could indicate malicious activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |6
 
-|<<suspicious-renaming-of-esxi-index-html-file, Suspicious Renaming of ESXI index.html File>> |Identifies instances where the "index.html" file within the "/usr/lib/vmware/*" directory is renamed on a Linux system. The rule monitors for the "rename" event action associated with this specific file and path, which could indicate malicious activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.5.0 |6
+|<<suspicious-screenconnect-client-child-process, Suspicious ScreenConnect Client Child Process>> |Identifies suspicious processes being spawned by the ScreenConnect client processes. This activity may indicate execution abusing unauthorized access to the ScreenConnect remote access software. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |103
 
-|<<suspicious-screenconnect-client-child-process, Suspicious ScreenConnect Client Child Process>> |Identifies suspicious processes being spawned by the ScreenConnect client processes. This activity may indicate execution abusing unauthorized access to the ScreenConnect remote access software. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |1
+|<<suspicious-script-object-execution, Suspicious Script Object Execution>> |Identifies scrobj.dll loaded into unusual Microsoft processes. This usually means a malicious scriptlet is being executed in the target process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<suspicious-script-object-execution, Suspicious Script Object Execution>> |Identifies scrobj.dll loaded into unusual Microsoft processes. This usually means a malicious scriptlet is being executed in the target process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<suspicious-service-was-installed-in-the-system, Suspicious Service was Installed in the System>> |Identifies the creation of a new Windows service with suspicious Service command values. Windows services typically run as SYSTEM and can be used for privilege escalation and persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide] |None |9
 
-|<<suspicious-service-was-installed-in-the-system, Suspicious Service was Installed in the System>> |Identifies the creation of a new Windows service with suspicious Service command values. Windows services typically run as SYSTEM and can be used for privilege escalation and persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide] |8.3.0 |8
+|<<suspicious-solarwinds-child-process, Suspicious SolarWinds Child Process>> |A suspicious SolarWinds child process was detected, which may indicate an attempt to execute malicious programs. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<suspicious-solarwinds-child-process, Suspicious SolarWinds Child Process>> |A suspicious SolarWinds child process was detected, which may indicate an attempt to execute malicious programs. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<suspicious-startup-shell-folder-modification, Suspicious Startup Shell Folder Modification>> |Identifies suspicious startup shell folder modifications to change the default Startup directory in order to bypass detections monitoring file creation in the Windows Startup folder. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<suspicious-startup-shell-folder-modification, Suspicious Startup Shell Folder Modification>> |Identifies suspicious startup shell folder modifications to change the default Startup directory in order to bypass detections monitoring file creation in the Windows Startup folder. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<suspicious-symbolic-link-created, Suspicious Symbolic Link Created>> |Identifies the creation of a symbolic link to a suspicious file or location. A symbolic link is a reference to a file or directory that acts as a pointer or shortcut, allowing users to access the target file or directory from a different location in the file system. An attacker can potentially leverage symbolic links for privilege escalation by tricking a privileged process into following the symbolic link to a sensitive file, giving the attacker access to data or capabilities they would not normally have. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |5
 
-|<<suspicious-symbolic-link-created, Suspicious Symbolic Link Created>> |Identifies the creation of a symbolic link to a suspicious file or location. A symbolic link is a reference to a file or directory that acts as a pointer or shortcut, allowing users to access the target file or directory from a different location in the file system. An attacker can potentially leverage symbolic links for privilege escalation by tricking a privileged process into following the symbolic link to a sensitive file, giving the attacker access to data or capabilities they would not normally have. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Credential Access], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |5
+|<<suspicious-sysctl-file-event, Suspicious Sysctl File Event>> |Monitors file events on sysctl configuration files (e.g., /etc/sysctl.conf, /etc/sysctl.d/*.conf) to identify potential unauthorized access or manipulation of system-level configuration settings. Attackers may tamper with the sysctl configuration files to modify kernel parameters, potentially compromising system stability, performance, or security. |[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |None |107
 
-|<<suspicious-sysctl-file-event, Suspicious Sysctl File Event>> |Monitors file events on sysctl configuration files (e.g., /etc/sysctl.conf, /etc/sysctl.d/*.conf) to identify potential unauthorized access or manipulation of system-level configuration settings. Attackers may tamper with the sysctl configuration files to modify kernel parameters, potentially compromising system stability, performance, or security. |[Data Source: Auditd Manager], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR] |8.6.0 |107
+|<<suspicious-system-commands-executed-by-previously-unknown-executable, Suspicious System Commands Executed by Previously Unknown Executable>> |This rule monitors for the execution of several commonly used system commands executed by a previously unknown executable located in commonly abused directories. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to run malicious code. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |105
 
-|<<suspicious-system-commands-executed-by-previously-unknown-executable, Suspicious System Commands Executed by Previously Unknown Executable>> |This rule monitors for the execution of several commonly used system commands executed by a previously unknown executable located in commonly abused directories. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to run malicious code. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.6.0 |105
+|<<suspicious-termination-of-esxi-process, Suspicious Termination of ESXI Process>> |Identifies instances where VMware processes, such as "vmware-vmx" or "vmx," are terminated on a Linux system by a "kill" command. The rule monitors for the "end" event type, which signifies the termination of a process. The presence of a "kill" command as the parent process for terminating VMware processes may indicate that a threat actor is attempting to interfere with the virtualized environment on the targeted system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |6
 
-|<<suspicious-termination-of-esxi-process, Suspicious Termination of ESXI Process>> |Identifies instances where VMware processes, such as "vmware-vmx" or "vmx," are terminated on a Linux system by a "kill" command. The rule monitors for the "end" event type, which signifies the termination of a process. The presence of a "kill" command as the parent process for terminating VMware processes may indicate that a threat actor is attempting to interfere with the virtualized environment on the targeted system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Impact], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.5.0 |6
+|<<suspicious-troubleshooting-pack-cabinet-execution, Suspicious Troubleshooting Pack Cabinet Execution>> |Identifies the execution of the Microsoft Diagnostic Wizard to open a diagcab file from a suspicious path and with an unusual parent process. This may indicate an attempt to execute malicious Troubleshooting Pack Cabinet files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |2
 
-|<<suspicious-troubleshooting-pack-cabinet-execution, Suspicious Troubleshooting Pack Cabinet Execution>> |Identifies the execution of the Microsoft Diagnostic Wizard to open a diagcab file from a suspicious path and with an unusual parent process. This may indicate an attempt to execute malicious Troubleshooting Pack Cabinet files. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<suspicious-utility-launched-via-proxychains, Suspicious Utility Launched via ProxyChains>> |This rule monitors for the execution of suspicious linux tools through ProxyChains. ProxyChains is a command-line tool that enables the routing of network connections through intermediary proxies, enhancing anonymity and enabling access to restricted resources. Attackers can exploit the ProxyChains utility to hide their true source IP address, evade detection, and perform malicious activities through a chain of proxy servers, potentially masking their identity and intentions. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |7
 
-|<<suspicious-utility-launched-via-proxychains, Suspicious Utility Launched via ProxyChains>> |This rule monitors for the execution of suspicious linux tools through ProxyChains. ProxyChains is a command-line tool that enables the routing of network connections through intermediary proxies, enhancing anonymity and enabling access to restricted resources. Attackers can exploit the ProxyChains utility to hide their true source IP address, evade detection, and perform malicious activities through a chain of proxy servers, potentially masking their identity and intentions. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Command and Control], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |7
+|<<suspicious-wmi-event-subscription-created, Suspicious WMI Event Subscription Created>> |Detects the creation of a WMI Event Subscription. Attackers can abuse this mechanism for persistence or to elevate to SYSTEM privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Sysmon] |None |106
 
-|<<suspicious-wmi-event-subscription-created, Suspicious WMI Event Subscription Created>> |Detects the creation of a WMI Event Subscription. Attackers can abuse this mechanism for persistence or to elevate to SYSTEM privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Sysmon] |8.8.0 |106
+|<<suspicious-wmi-image-load-from-ms-office, Suspicious WMI Image Load from MS Office>> |Identifies a suspicious image load (wmiutils.dll) from Microsoft Office processes. This behavior may indicate adversarial activity where child processes are spawned via Windows Management Instrumentation (WMI). This technique can be used to execute code and evade traditional parent/child processes spawned from Microsoft Office products. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<suspicious-wmi-image-load-from-ms-office, Suspicious WMI Image Load from MS Office>> |Identifies a suspicious image load (wmiutils.dll) from Microsoft Office processes. This behavior may indicate adversarial activity where child processes are spawned via Windows Management Instrumentation (WMI). This technique can be used to execute code and evade traditional parent/child processes spawned from Microsoft Office products. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<suspicious-wmic-xsl-script-execution, Suspicious WMIC XSL Script Execution>> |Identifies WMIC allowlist bypass techniques by alerting on suspicious execution of scripts. When WMIC loads scripting libraries it may be indicative of an allowlist bypass. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<suspicious-wmic-xsl-script-execution, Suspicious WMIC XSL Script Execution>> |Identifies WMIC allowlist bypass techniques by alerting on suspicious execution of scripts. When WMIC loads scripting libraries it may be indicative of an allowlist bypass. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<suspicious-web-browser-sensitive-file-access, Suspicious Web Browser Sensitive File Access>> |Identifies the access or file open of web browser sensitive files by an untrusted/unsigned process or osascript. Adversaries may acquire credentials from web browsers by reading files specific to the target browser. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.11.0 |208
 
-|<<suspicious-web-browser-sensitive-file-access, Suspicious Web Browser Sensitive File Access>> |Identifies the access or file open of web browser sensitive files by an untrusted/unsigned process or osascript. Adversaries may acquire credentials from web browsers by reading files specific to the target browser. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.11.0 |207
+|<<suspicious-werfault-child-process, Suspicious WerFault Child Process>> |A suspicious WerFault child process was detected, which may indicate an attempt to run via the SilentProcessExit registry key manipulation. Verify process details such as command line, network connections and file writes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne] |8.11.0 |214
 
-|<<suspicious-werfault-child-process, Suspicious WerFault Child Process>> |A suspicious WerFault child process was detected, which may indicate an attempt to run via the SilentProcessExit registry key manipulation. Verify process details such as command line, network connections and file writes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<suspicious-windows-process-cluster-spawned-by-a-host, Suspicious Windows Process Cluster Spawned by a Host>> |A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same host name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |None |5
 
-|<<suspicious-windows-process-cluster-spawned-by-a-host, Suspicious Windows Process Cluster Spawned by a Host>> |A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same host name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |8.9.0 |4
+|<<suspicious-windows-process-cluster-spawned-by-a-parent-process, Suspicious Windows Process Cluster Spawned by a Parent Process>> |A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same parent process name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |None |5
 
-|<<suspicious-windows-process-cluster-spawned-by-a-parent-process, Suspicious Windows Process Cluster Spawned by a Parent Process>> |A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same parent process name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |8.9.0 |4
+|<<suspicious-windows-process-cluster-spawned-by-a-user, Suspicious Windows Process Cluster Spawned by a User>> |A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same user name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |None |5
 
-|<<suspicious-windows-process-cluster-spawned-by-a-user, Suspicious Windows Process Cluster Spawned by a User>> |A machine learning job combination has detected a set of one or more suspicious Windows processes with unusually high scores for malicious probability. These process(es) have been classified as malicious in several ways. The process(es) were predicted to be malicious by the ProblemChild supervised ML model. If the anomaly contains a cluster of suspicious processes, each process has the same user name, and the aggregate score of the event cluster was calculated to be unusually high by an unsupervised ML model. Such a cluster often contains suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |8.9.0 |4
+|<<suspicious-zoom-child-process, Suspicious Zoom Child Process>> |A suspicious Zoom child process was detected, which may indicate an attempt to run unnoticed. Verify process details such as command line, network connections, file writes and associated file signature details as well. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: SentinelOne] |8.11.0 |212
 
-|<<suspicious-zoom-child-process, Suspicious Zoom Child Process>> |A suspicious Zoom child process was detected, which may indicate an attempt to run unnoticed. Verify process details such as command line, network connections, file writes and associated file signature details as well. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |110
+|<<suspicious-macos-ms-office-child-process, Suspicious macOS MS Office Child Process>> |Identifies suspicious child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, and Excel). These child processes are often launched during exploitation of Office applications or by documents with malicious macros. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Defend] |8.11.0 |207
 
-|<<suspicious-macos-ms-office-child-process, Suspicious macOS MS Office Child Process>> |Identifies suspicious child processes of frequently targeted Microsoft Office applications (Word, PowerPoint, and Excel). These child processes are often launched during exploitation of Office applications or by documents with malicious macros. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Initial Access], [Data Source: Elastic Defend] |8.11.0 |206
+|<<suspicious-which-enumeration, Suspicious which Enumeration>> |This rule monitors for the usage of the which command with an unusual amount of process arguments. Attackers may leverage the which command to enumerate the system for useful installed utilities that may be used after compromising a system to escalate privileges or move latteraly across the network. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |6
 
-|<<suspicious-which-enumeration, Suspicious which Enumeration>> |This rule monitors for the usage of the which command with an unusual amount of process arguments. Attackers may leverage the which command to enumerate the system for useful installed utilities that may be used after compromising a system to escalate privileges or move latteraly across the network. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |5
+|<<svchost-spawning-cmd, Svchost spawning Cmd>> |Identifies a suspicious parent child process relationship with cmd.exe descending from svchost.exe |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |212
 
-|<<svchost-spawning-cmd, Svchost spawning Cmd>> |Identifies a suspicious parent child process relationship with cmd.exe descending from svchost.exe |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.6.0 |212
+|<<symbolic-link-to-shadow-copy-created, Symbolic Link to Shadow Copy Created>> |Identifies the creation of symbolic links to a shadow copy. Symbolic links can be used to access files in the shadow copy, including sensitive files such as ntds.dit, System Boot Key and browser offline credentials. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<symbolic-link-to-shadow-copy-created, Symbolic Link to Shadow Copy Created>> |Identifies the creation of symbolic links to a shadow copy. Symbolic links can be used to access files in the shadow copy, including sensitive files such as ntds.dit, System Boot Key and browser offline credentials. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<system-binary-copied-and-or-moved-to-suspicious-directory, System Binary Copied and/or Moved to Suspicious Directory>> |This rule monitors for the copying or moving of a system binary to a suspicious directory. Adversaries may copy/move and rename system binaries to evade detection. Copying a system binary to a different location should not occur often, so if it does, the activity should be investigated. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |8
 
-|<<system-binary-copied-and-or-moved-to-suspicious-directory, System Binary Copied and/or Moved to Suspicious Directory>> |This rule monitors for the copying or moving of a system binary to a suspicious directory. Adversaries may copy/move and rename system binaries to evade detection. Copying a system binary to a different location should not occur often, so if it does, the activity should be investigated. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |7
+|<<system-hosts-file-access, System Hosts File Access>> |Identifies the use of built-in tools to read the contents of \etc\hosts on a local machine. Attackers may use this data to discover remote machines in an environment that may be used for Lateral Movement from the current system. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |3
 
-|<<system-hosts-file-access, System Hosts File Access>> |Identifies the use of built-in tools to read the contents of \etc\hosts on a local machine. Attackers may use this data to discover remote machines in an environment that may be used for Lateral Movement from the current system. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |3
+|<<system-information-discovery-via-windows-command-shell, System Information Discovery via Windows Command Shell>> |Identifies the execution of discovery commands to enumerate system information, files, and folders using the Windows Command Shell. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Rule Type: BBR] |None |10
 
-|<<system-information-discovery-via-windows-command-shell, System Information Discovery via Windows Command Shell>> |Identifies the execution of discovery commands to enumerate system information, files, and folders using the Windows Command Shell. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |10
+|<<system-log-file-deletion, System Log File Deletion>> |Identifies the deletion of sensitive Linux system logs. This may indicate an attempt to evade detection or destroy forensic evidence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<system-log-file-deletion, System Log File Deletion>> |Identifies the deletion of sensitive Linux system logs. This may indicate an attempt to evade detection or destroy forensic evidence on a system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<system-network-connections-discovery, System Network Connections Discovery>> |Adversaries may attempt to get a listing of network connections to or from a compromised system. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |3
 
-|<<system-network-connections-discovery, System Network Connections Discovery>> |Adversaries may attempt to get a listing of network connections to or from a compromised system. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |3
+|<<system-owner-user-discovery-linux, System Owner/User Discovery Linux>> |Identifies the use of built-in tools which adversaries may use to enumerate the system owner/user of a compromised system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |3
 
-|<<system-owner-user-discovery-linux, System Owner/User Discovery Linux>> |Identifies the use of built-in tools which adversaries may use to enumerate the system owner/user of a compromised system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |3
+|<<system-service-discovery-through-built-in-windows-utilities, System Service Discovery through built-in Windows Utilities>> |Detects the usage of commonly used system service discovery techniques, which attackers may use during the reconnaissance phase after compromising a system in order to gain a better understanding of the environment and/or escalate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR] |None |6
 
-|<<system-service-discovery-through-built-in-windows-utilities, System Service Discovery through built-in Windows Utilities>> |Detects the usage of commonly used system service discovery techniques, which attackers may use during the reconnaissance phase after compromising a system in order to gain a better understanding of the environment and/or escalate privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR] |8.3.0 |6
+|<<system-shells-via-services, System Shells via Services>> |Windows services typically run as SYSTEM and can be used as a privilege escalation opportunity. Malware or penetration testers may run a shell as a service to gain SYSTEM permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne] |8.11.0 |212
 
-|<<system-shells-via-services, System Shells via Services>> |Windows services typically run as SYSTEM and can be used as a privilege escalation opportunity. Malware or penetration testers may run a shell as a service to gain SYSTEM permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<system-time-discovery, System Time Discovery>> |Detects the usage of commonly used system time discovery techniques, which attackers may use during the reconnaissance phase after compromising a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR] |None |7
 
-|<<system-time-discovery, System Time Discovery>> |Detects the usage of commonly used system time discovery techniques, which attackers may use during the reconnaissance phase after compromising a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Rule Type: BBR] |8.3.0 |7
+|<<systemkey-access-via-command-line, SystemKey Access via Command Line>> |Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features, including Wi-Fi and website passwords, secure notes, certificates, and Kerberos. Adversaries may collect the keychain storage data from a system to acquire credentials. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |206
 
-|<<systemkey-access-via-command-line, SystemKey Access via Command Line>> |Keychains are the built-in way for macOS to keep track of users' passwords and credentials for many services and features, including Wi-Fi and website passwords, secure notes, certificates, and Kerberos. Adversaries may collect the keychain storage data from a system to acquire credentials. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.7.0 |206
+|<<systemd-service-started-by-unusual-parent-process, Systemd Service Started by Unusual Parent Process>> |Systemctl is a process used in Linux systems to manage systemd processes through service configuration files. Malicious actors can leverage systemd services to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |8.4.0 |1
 
-|<<tcc-bypass-via-mounted-apfs-snapshot-access, TCC Bypass via Mounted APFS Snapshot Access>> |Identifies the use of the mount_apfs command to mount the entire file system through Apple File System (APFS) snapshots as read-only and with the noowners flag set. This action enables the adversary to access almost any file in the file system, including all user data and files protected by Apple’s privacy framework (TCC). |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |106
+|<<tcc-bypass-via-mounted-apfs-snapshot-access, TCC Bypass via Mounted APFS Snapshot Access>> |Identifies the use of the mount_apfs command to mount the entire file system through Apple File System (APFS) snapshots as read-only and with the noowners flag set. This action enables the adversary to access almost any file in the file system, including all user data and files protected by Apple’s privacy framework (TCC). |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |106
 
-|<<tainted-kernel-module-load, Tainted Kernel Module Load>> |This rule monitors the syslog log file for messages related to instances of a tainted kernel module load. Rootkits often leverage kernel modules as their main defense evasion technique. Detecting tainted kernel module loads is crucial for ensuring system security and integrity, as malicious or unauthorized modules can compromise the kernel and lead to system vulnerabilities or unauthorized access. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |8.3.0 |4
+|<<tainted-kernel-module-load, Tainted Kernel Module Load>> |This rule monitors the syslog log file for messages related to instances of a tainted kernel module load. Rootkits often leverage kernel modules as their main defense evasion technique. Detecting tainted kernel module loads is crucial for ensuring system security and integrity, as malicious or unauthorized modules can compromise the kernel and lead to system vulnerabilities or unauthorized access. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |None |4
 
-|<<tainted-out-of-tree-kernel-module-load, Tainted Out-Of-Tree Kernel Module Load>> |This rule monitors the syslog log file for messages related to instances of a out-of-tree kernel module load, indicating the taining of the kernel. Rootkits often leverage kernel modules as their main defense evasion technique. Detecting tainted kernel module loads is crucial for ensuring system security and integrity, as malicious or unauthorized modules can compromise the kernel and lead to system vulnerabilities or unauthorized access. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |8.3.0 |2
+|<<tainted-out-of-tree-kernel-module-load, Tainted Out-Of-Tree Kernel Module Load>> |This rule monitors the syslog log file for messages related to instances of a out-of-tree kernel module load, indicating the taining of the kernel. Rootkits often leverage kernel modules as their main defense evasion technique. Detecting tainted kernel module loads is crucial for ensuring system security and integrity, as malicious or unauthorized modules can compromise the kernel and lead to system vulnerabilities or unauthorized access. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion] |None |2
 
-|<<tampering-of-shell-command-line-history, Tampering of Shell Command-Line History>> |Adversaries may attempt to clear or disable the Bash command-line history in an attempt to evade detection or forensic investigations. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |105
+|<<tampering-of-shell-command-line-history, Tampering of Shell Command-Line History>> |Adversaries may attempt to clear or disable the Bash command-line history in an attempt to evade detection or forensic investigations. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |105
 
-|<<temporarily-scheduled-task-creation, Temporarily Scheduled Task Creation>> |Indicates the creation and deletion of a scheduled task within a short time interval. Adversaries can use these to proxy malicious execution via the schedule service and perform clean up. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution] |8.3.0 |7
+|<<temporarily-scheduled-task-creation, Temporarily Scheduled Task Creation>> |Indicates the creation and deletion of a scheduled task within a short time interval. Adversaries can use these to proxy malicious execution via the schedule service and perform clean up. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Execution] |None |7
 
-|<<third-party-backup-files-deleted-via-unexpected-process, Third-party Backup Files Deleted via Unexpected Process>> |Identifies the deletion of backup files, saved using third-party software, by a process outside of the backup suite. Adversaries may delete Backup files to ensure that recovery from a ransomware attack is less likely. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<third-party-backup-files-deleted-via-unexpected-process, Third-party Backup Files Deleted via Unexpected Process>> |Identifies the deletion of backup files, saved using third-party software, by a process outside of the backup suite. Adversaries may delete Backup files to ensure that recovery from a ransomware attack is less likely. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |113
 
-|<<threat-intel-hash-indicator-match, Threat Intel Hash Indicator Match>> |This rule is triggered when a hash indicator from the Threat Intel Filebeat module or integrations has a match against an event that contains file hashes, such as antivirus alerts, process creation, library load, and file operation events. |[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Indicator Match] |8.5.0 |7
+|<<threat-intel-hash-indicator-match, Threat Intel Hash Indicator Match>> |This rule is triggered when a hash indicator from the Threat Intel Filebeat module or integrations has a match against an event that contains file hashes, such as antivirus alerts, process creation, library load, and file operation events. |[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Indicator Match] |None |7
 
-|<<threat-intel-ip-address-indicator-match, Threat Intel IP Address Indicator Match>> |This rule is triggered when an IP address indicator from the Threat Intel Filebeat module or integrations has a match against a network event. |[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Indicator Match] |8.5.0 |6
+|<<threat-intel-ip-address-indicator-match, Threat Intel IP Address Indicator Match>> |This rule is triggered when an IP address indicator from the Threat Intel Filebeat module or integrations has a match against a network event. |[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Indicator Match] |None |6
 
-|<<threat-intel-url-indicator-match, Threat Intel URL Indicator Match>> |This rule is triggered when a URL indicator from the Threat Intel Filebeat module or integrations has a match against an event that contains URL data, like DNS events, network logs, etc. |[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Indicator Match] |8.5.0 |6
+|<<threat-intel-url-indicator-match, Threat Intel URL Indicator Match>> |This rule is triggered when a URL indicator from the Threat Intel Filebeat module or integrations has a match against an event that contains URL data, like DNS events, network logs, etc. |[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Indicator Match] |None |6
 
-|<<threat-intel-windows-registry-indicator-match, Threat Intel Windows Registry Indicator Match>> |This rule is triggered when a Windows registry indicator from the Threat Intel Filebeat module or integrations has a match against an event that contains registry data. |[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Indicator Match] |8.5.0 |6
+|<<threat-intel-windows-registry-indicator-match, Threat Intel Windows Registry Indicator Match>> |This rule is triggered when a Windows registry indicator from the Threat Intel Filebeat module or integrations has a match against an event that contains registry data. |[OS: Windows], [Data Source: Elastic Endgame], [Rule Type: Indicator Match] |None |6
 
-|<<timestomping-using-touch-command, Timestomping using Touch Command>> |Timestomping is an anti-forensics technique which is used to modify the timestamps of a file, often to mimic files that are in the same folder. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.3.0 |106
+|<<timestomping-using-touch-command, Timestomping using Touch Command>> |Timestomping is an anti-forensics technique which is used to modify the timestamps of a file, often to mimic files that are in the same folder. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |106
 
-|<<trap-signals-execution, Trap Signals Execution>> |Identify activity related where adversaries can include a trap command which then allows programs and shells to specify commands that will be executed upon receiving interrupt signals. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |2
+|<<trap-signals-execution, Trap Signals Execution>> |Identify activity related where adversaries can include a trap command which then allows programs and shells to specify commands that will be executed upon receiving interrupt signals. |[Domain: Endpoint], [OS: Linux], [OS: macOS], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |2
 
-|<<uac-bypass-attempt-via-elevated-com-internet-explorer-add-on-installer, UAC Bypass Attempt via Elevated COM Internet Explorer Add-On Installer>> |Identifies User Account Control (UAC) bypass attempts by abusing an elevated COM Interface to launch a malicious program. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<uac-bypass-attempt-via-elevated-com-internet-explorer-add-on-installer, UAC Bypass Attempt via Elevated COM Internet Explorer Add-On Installer>> |Identifies User Account Control (UAC) bypass attempts by abusing an elevated COM Interface to launch a malicious program. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<uac-bypass-attempt-via-privileged-ifileoperation-com-interface, UAC Bypass Attempt via Privileged IFileOperation COM Interface>> |Identifies attempts to bypass User Account Control (UAC) via DLL side-loading. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<uac-bypass-attempt-via-privileged-ifileoperation-com-interface, UAC Bypass Attempt via Privileged IFileOperation COM Interface>> |Identifies attempts to bypass User Account Control (UAC) via DLL side-loading. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<uac-bypass-attempt-via-windows-directory-masquerading, UAC Bypass Attempt via Windows Directory Masquerading>> |Identifies an attempt to bypass User Account Control (UAC) by masquerading as a Microsoft trusted Windows directory. Attackers may bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |112
+|<<uac-bypass-attempt-via-windows-directory-masquerading, UAC Bypass Attempt via Windows Directory Masquerading>> |Identifies an attempt to bypass User Account Control (UAC) by masquerading as a Microsoft trusted Windows directory. Attackers may bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |113
 
-|<<uac-bypass-attempt-with-ieditionupgrademanager-elevated-com-interface, UAC Bypass Attempt with IEditionUpgradeManager Elevated COM Interface>> |Identifies attempts to bypass User Account Control (UAC) by abusing an elevated COM Interface to launch a rogue Windows ClipUp program. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<uac-bypass-attempt-with-ieditionupgrademanager-elevated-com-interface, UAC Bypass Attempt with IEditionUpgradeManager Elevated COM Interface>> |Identifies attempts to bypass User Account Control (UAC) by abusing an elevated COM Interface to launch a rogue Windows ClipUp program. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<uac-bypass-via-diskcleanup-scheduled-task-hijack, UAC Bypass via DiskCleanup Scheduled Task Hijack>> |Identifies User Account Control (UAC) bypass via hijacking DiskCleanup Scheduled Task. Attackers bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<uac-bypass-via-diskcleanup-scheduled-task-hijack, UAC Bypass via DiskCleanup Scheduled Task Hijack>> |Identifies User Account Control (UAC) bypass via hijacking DiskCleanup Scheduled Task. Attackers bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<uac-bypass-via-icmluautil-elevated-com-interface, UAC Bypass via ICMLuaUtil Elevated COM Interface>> |Identifies User Account Control (UAC) bypass attempts via the ICMLuaUtil Elevated COM interface. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<uac-bypass-via-icmluautil-elevated-com-interface, UAC Bypass via ICMLuaUtil Elevated COM Interface>> |Identifies User Account Control (UAC) bypass attempts via the ICMLuaUtil Elevated COM interface. Attackers may attempt to bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<uac-bypass-via-windows-firewall-snap-in-hijack, UAC Bypass via Windows Firewall Snap-In Hijack>> |Identifies attempts to bypass User Account Control (UAC) by hijacking the Microsoft Management Console (MMC) Windows Firewall snap-in. Attackers bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<uac-bypass-via-windows-firewall-snap-in-hijack, UAC Bypass via Windows Firewall Snap-In Hijack>> |Identifies attempts to bypass User Account Control (UAC) by hijacking the Microsoft Management Console (MMC) Windows Firewall snap-in. Attackers bypass UAC to stealthily execute code with elevated permissions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |112
 
-|<<uid-elevation-from-previously-unknown-executable, UID Elevation from Previously Unknown Executable>> |Monitors for the elevation of regular user permissions to root permissions through a previously unknown executable. Attackers may attempt to evade detection by hijacking the execution flow and hooking certain functions/syscalls through a rootkit in order to provide easy access to root via a special modified command. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.6.0 |2
+|<<uid-elevation-from-previously-unknown-executable, UID Elevation from Previously Unknown Executable>> |Monitors for the elevation of regular user permissions to root permissions through a previously unknown executable. Attackers may attempt to evade detection by hijacking the execution flow and hooking certain functions/syscalls through a rootkit in order to provide easy access to root via a special modified command. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |2
 
 |<<unauthorized-access-to-an-okta-application, Unauthorized Access to an Okta Application>> |Identifies unauthorized access attempts to Okta applications. |[Tactic: Initial Access], [Use Case: Identity and Access Audit], [Data Source: Okta] |8.10.0 |206
 
-|<<uncommon-registry-persistence-change, Uncommon Registry Persistence Change>> |Detects changes to registry persistence keys that are not commonly used or modified by legitimate programs. This could be an indication of an adversary's attempt to persist in a stealthy manner. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<uncommon-registry-persistence-change, Uncommon Registry Persistence Change>> |Detects changes to registry persistence keys that are not commonly used or modified by legitimate programs. This could be an indication of an adversary's attempt to persist in a stealthy manner. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<unexpected-child-process-of-macos-screensaver-engine, Unexpected Child Process of macOS Screensaver Engine>> |Identifies when a child process is spawned by the screensaver engine process, which is consistent with an attacker's malicious payload being executed after the screensaver activated on the endpoint. An adversary can maintain persistence on a macOS endpoint by creating a malicious screensaver (.saver) file and configuring the screensaver plist file to execute code each time the screensaver is activated. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |8.3.0 |107
+|<<unexpected-child-process-of-macos-screensaver-engine, Unexpected Child Process of macOS Screensaver Engine>> |Identifies when a child process is spawned by the screensaver engine process, which is consistent with an attacker's malicious payload being executed after the screensaver activated on the endpoint. An adversary can maintain persistence on a macOS endpoint by creating a malicious screensaver (.saver) file and configuring the screensaver plist file to execute code each time the screensaver is activated. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Defend] |None |107
 
-|<<unix-socket-connection, Unix Socket Connection>> |This rule monitors for inter-process communication via Unix sockets. Adversaries may attempt to communicate with local Unix sockets to enumerate application details, find vulnerabilities/configuration mistakes and potentially escalate privileges or set up malicious communication channels via Unix sockets for inter-process communication to attempt to evade detection. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |8.3.0 |2
+|<<unix-socket-connection, Unix Socket Connection>> |This rule monitors for inter-process communication via Unix sockets. Adversaries may attempt to communicate with local Unix sockets to enumerate application details, find vulnerabilities/configuration mistakes and potentially escalate privileges or set up malicious communication channels via Unix sockets for inter-process communication to attempt to evade detection. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame], [Data Source: Auditd Manager] |None |2
 
-|<<unknown-execution-of-binary-with-rwx-memory-region, Unknown Execution of Binary with RWX Memory Region>> |Monitors for the execution of a previously unknown unix binary with read, write and execute memory region permissions. The mprotect() system call is used to change the access protections on a region of memory that has already been allocated. This syscall allows a process to modify the permissions of pages in its virtual address space, enabling or disabling permissions such as read, write, and execute for those pages. RWX permissions on memory is in many cases overly permissive, and should be analyzed thoroughly. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Auditd Manager] |8.6.0 |1
+|<<unknown-execution-of-binary-with-rwx-memory-region, Unknown Execution of Binary with RWX Memory Region>> |Monitors for the execution of a previously unknown unix binary with read, write and execute memory region permissions. The mprotect() system call is used to change the access protections on a region of memory that has already been allocated. This syscall allows a process to modify the permissions of pages in its virtual address space, enabling or disabling permissions such as read, write, and execute for those pages. RWX permissions on memory is in many cases overly permissive, and should be analyzed thoroughly. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Auditd Manager] |None |1
 
-|<<unsigned-bits-service-client-process, Unsigned BITS Service Client Process>> |Identifies an unsigned Windows Background Intelligent Transfer Service (BITS) client process. Attackers may abuse BITS functionality to download or upload data using the BITS service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |2
+|<<unsigned-bits-service-client-process, Unsigned BITS Service Client Process>> |Identifies an unsigned Windows Background Intelligent Transfer Service (BITS) client process. Attackers may abuse BITS functionality to download or upload data using the BITS service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |None |3
 
-|<<unsigned-dll-loaded-by-svchost, Unsigned DLL Loaded by Svchost>> |Identifies an unsigned library created in the last 5 minutes and subsequently loaded by a shared windows service (svchost). Adversaries may use this technique to maintain persistence or run with System privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |8.4.0 |6
+|<<unsigned-dll-loaded-by-svchost, Unsigned DLL Loaded by Svchost>> |Identifies an unsigned library created in the last 5 minutes and subsequently loaded by a shared windows service (svchost). Adversaries may use this technique to maintain persistence or run with System privileges. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Tactic: Execution], [Data Source: Elastic Defend] |None |6
 
-|<<unsigned-dll-loaded-by-a-trusted-process, Unsigned DLL Loaded by a Trusted Process>> |Identifies digitally signed (trusted) processes loading unsigned DLLs. Attackers may plant their payloads into the application folder and invoke the legitimate application to execute the payload, masking actions they perform under a legitimate, trusted, and potentially elevated system or software process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |8.4.0 |102
+|<<unsigned-dll-loaded-by-a-trusted-process, Unsigned DLL Loaded by a Trusted Process>> |Identifies digitally signed (trusted) processes loading unsigned DLLs. Attackers may plant their payloads into the application folder and invoke the legitimate application to execute the payload, masking actions they perform under a legitimate, trusted, and potentially elevated system or software process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |None |102
 
-|<<unsigned-dll-side-loading-from-a-suspicious-folder, Unsigned DLL Side-Loading from a Suspicious Folder>> |Identifies a Windows trusted program running from locations often abused by adversaries to masquerade as a trusted program and loading a recently dropped DLL. This behavior may indicate an attempt to evade defenses via side-loading a malicious DLL within the memory space of a signed processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |8.4.0 |8
+|<<unsigned-dll-side-loading-from-a-suspicious-folder, Unsigned DLL Side-Loading from a Suspicious Folder>> |Identifies a Windows trusted program running from locations often abused by adversaries to masquerade as a trusted program and loading a recently dropped DLL. This behavior may indicate an attempt to evade defenses via side-loading a malicious DLL within the memory space of a signed processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend] |None |8
 
-|<<untrusted-driver-loaded, Untrusted Driver Loaded>> |Identifies attempt to load an untrusted driver. Adversaries may modify code signing policies to enable execution of unsigned or self-signed code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |8
+|<<untrusted-driver-loaded, Untrusted Driver Loaded>> |Identifies attempt to load an untrusted driver. Adversaries may modify code signing policies to enable execution of unsigned or self-signed code. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |9
 
-|<<unusual-aws-command-for-a-user, Unusual AWS Command for a User>> |A machine learning job detected an AWS API command that, while not inherently suspicious or abnormal, is being made by a user context that does not normally use the command. This can be the result of compromised credentials or keys as someone uses a valid account to persist, move laterally, or exfiltrate data. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |8.9.0 |208
+|<<unusual-aws-command-for-a-user, Unusual AWS Command for a User>> |A machine learning job detected an AWS API command that, while not inherently suspicious or abnormal, is being made by a user context that does not normally use the command. This can be the result of compromised credentials or keys as someone uses a valid account to persist, move laterally, or exfiltrate data. |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |None |208
 
-|<<unusual-child-process-from-a-system-virtual-process, Unusual Child Process from a System Virtual Process>> |Identifies a suspicious child process of the Windows virtual system process, which could indicate code injection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<unusual-child-process-from-a-system-virtual-process, Unusual Child Process from a System Virtual Process>> |Identifies a suspicious child process of the Windows virtual system process, which could indicate code injection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<unusual-child-process-of-dns-exe, Unusual Child Process of dns.exe>> |Identifies an unexpected process spawning from dns.exe, the process responsible for Windows DNS server services, which may indicate activity related to remote code execution or other forms of exploitation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |110
+|<<unusual-child-process-of-dns-exe, Unusual Child Process of dns.exe>> |Identifies an unexpected process spawning from dns.exe, the process responsible for Windows DNS server services, which may indicate activity related to remote code execution or other forms of exploitation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |110
 
-|<<unusual-child-processes-of-rundll32, Unusual Child Processes of RunDLL32>> |Identifies child processes of unusual instances of RunDLL32 where the command line parameters were suspicious. Misuse of RunDLL32 could indicate malicious activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<unusual-child-processes-of-rundll32, Unusual Child Processes of RunDLL32>> |Identifies child processes of unusual instances of RunDLL32 where the command line parameters were suspicious. Misuse of RunDLL32 could indicate malicious activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<unusual-city-for-an-aws-command, Unusual City For an AWS Command>> |A machine learning job detected AWS command activity that, while not inherently suspicious or abnormal, is sourcing from a geolocation (city) that is unusual for the command. This can be the result of compromised credentials or keys being used by a threat actor in a different geography than the authorized user(s). |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |8.9.0 |208
+|<<unusual-city-for-an-aws-command, Unusual City For an AWS Command>> |A machine learning job detected AWS command activity that, while not inherently suspicious or abnormal, is sourcing from a geolocation (city) that is unusual for the command. This can be the result of compromised credentials or keys being used by a threat actor in a different geography than the authorized user(s). |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |None |208
 
-|<<unusual-country-for-an-aws-command, Unusual Country For an AWS Command>> |A machine learning job detected AWS command activity that, while not inherently suspicious or abnormal, is sourcing from a geolocation (country) that is unusual for the command. This can be the result of compromised credentials or keys being used by a threat actor in a different geography than the authorized user(s). |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |8.9.0 |208
+|<<unusual-country-for-an-aws-command, Unusual Country For an AWS Command>> |A machine learning job detected AWS command activity that, while not inherently suspicious or abnormal, is sourcing from a geolocation (country) that is unusual for the command. This can be the result of compromised credentials or keys being used by a threat actor in a different geography than the authorized user(s). |[Domain: Cloud], [Data Source: AWS], [Data Source: Amazon Web Services], [Rule Type: ML], [Rule Type: Machine Learning], [Resources: Investigation Guide] |None |208
 
-|<<unusual-dns-activity, Unusual DNS Activity>> |A machine learning job detected a rare and unusual DNS query that indicate network activity with unusual DNS domains. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from an uncommon domain. When malware is already running, it may send requests to an uncommon DNS domain the malware uses for command-and-control communication. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |8.3.0 |103
+|<<unusual-dns-activity, Unusual DNS Activity>> |A machine learning job detected a rare and unusual DNS query that indicate network activity with unusual DNS domains. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from an uncommon domain. When malware is already running, it may send requests to an uncommon DNS domain the malware uses for command-and-control communication. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |None |103
 
-|<<unusual-discovery-activity-by-user, Unusual Discovery Activity by User>> |This rule leverages alert data from various Discovery building block rules to alert on signals with unusual unique host.id and user.id entries. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: Higher-Order Rule] |8.6.0 |1
+|<<unusual-discovery-activity-by-user, Unusual Discovery Activity by User>> |This rule leverages alert data from various Discovery building block rules to alert on signals with unusual unique host.id and user.id entries. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: Higher-Order Rule] |None |1
 
-|<<unusual-discovery-signal-alert-with-unusual-process-command-line, Unusual Discovery Signal Alert with Unusual Process Command Line>> |This rule leverages alert data from various Discovery building block rules to alert on signals with unusual unique host.id, user.id and process.command_line entries. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: Higher-Order Rule] |8.6.0 |1
+|<<unusual-discovery-signal-alert-with-unusual-process-command-line, Unusual Discovery Signal Alert with Unusual Process Command Line>> |This rule leverages alert data from various Discovery building block rules to alert on signals with unusual unique host.id, user.id and process.command_line entries. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: Higher-Order Rule] |None |1
 
-|<<unusual-discovery-signal-alert-with-unusual-process-executable, Unusual Discovery Signal Alert with Unusual Process Executable>> |This rule leverages Discovery building block rule alert data to alert on signals with unusual unique host.id, user.id and process.executable entries. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: Higher-Order Rule] |8.6.0 |2
+|<<unusual-discovery-signal-alert-with-unusual-process-executable, Unusual Discovery Signal Alert with Unusual Process Executable>> |This rule leverages Discovery building block rule alert data to alert on signals with unusual unique host.id, user.id and process.executable entries. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: Higher-Order Rule] |None |2
 
-|<<unusual-executable-file-creation-by-a-system-critical-process, Unusual Executable File Creation by a System Critical Process>> |Identifies an unexpected executable file being created or modified by a Windows system critical process, which may indicate activity related to remote code execution or other forms of exploitation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<unusual-executable-file-creation-by-a-system-critical-process, Unusual Executable File Creation by a System Critical Process>> |Identifies an unexpected executable file being created or modified by a Windows system critical process, which may indicate activity related to remote code execution or other forms of exploitation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<unusual-execution-via-microsoft-common-console-file, Unusual Execution via Microsoft Common Console File>> |Identifies the execution of a child process from a Microsoft Common Console file. Adversaries may embed a malicious command in an MSC file in order to trick victims into executing malicious commands. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Initial Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |1
+|<<unusual-execution-via-microsoft-common-console-file, Unusual Execution via Microsoft Common Console File>> |Identifies the execution of a child process from a Microsoft Common Console file. Adversaries may embed a malicious command in an MSC file in order to trick victims into executing malicious commands. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Tactic: Initial Access], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |1
 
-|<<unusual-file-creation-alternate-data-stream, Unusual File Creation - Alternate Data Stream>> |Identifies suspicious creation of Alternate Data Streams on highly targeted files. This is uncommon for legitimate files and sometimes done by adversaries to hide malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |114
+|<<unusual-file-creation-alternate-data-stream, Unusual File Creation - Alternate Data Stream>> |Identifies suspicious creation of Alternate Data Streams on highly targeted files. This is uncommon for legitimate files and sometimes done by adversaries to hide malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |114
 
-|<<unusual-file-modification-by-dns-exe, Unusual File Modification by dns.exe>> |Identifies an unexpected file being modified by dns.exe, the process responsible for Windows DNS Server services, which may indicate activity related to remote code execution or other forms of exploitation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<unusual-file-modification-by-dns-exe, Unusual File Modification by dns.exe>> |Identifies an unexpected file being modified by dns.exe, the process responsible for Windows DNS Server services, which may indicate activity related to remote code execution or other forms of exploitation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Endgame], [Use Case: Vulnerability], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<unusual-hour-for-a-user-to-logon, Unusual Hour for a User to Logon>> |A machine learning job detected a user logging in at a time of day that is unusual for the user. This can be due to credentialed access via a compromised account when the user and the threat actor are in different time zones. In addition, unauthorized user activity often takes place during non-business hours. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access], [Resources: Investigation Guide] |8.3.0 |104
+|<<unusual-hour-for-a-user-to-logon, Unusual Hour for a User to Logon>> |A machine learning job detected a user logging in at a time of day that is unusual for the user. This can be due to credentialed access via a compromised account when the user and the threat actor are in different time zones. In addition, unauthorized user activity often takes place during non-business hours. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access], [Resources: Investigation Guide] |None |104
 
-|<<unusual-linux-network-activity, Unusual Linux Network Activity>> |Identifies Linux processes that do not usually use the network but have unexpected network activity, which can indicate command-and-control, lateral movement, persistence, or data exfiltration activity. A process with unusual network activity can denote process exploitation or injection, where the process is used to run persistence mechanisms that allow a malicious actor remote access or control of the host, data exfiltration, and execution of unauthorized network applications. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |8.3.0 |103
+|<<unusual-linux-network-activity, Unusual Linux Network Activity>> |Identifies Linux processes that do not usually use the network but have unexpected network activity, which can indicate command-and-control, lateral movement, persistence, or data exfiltration activity. A process with unusual network activity can denote process exploitation or injection, where the process is used to run persistence mechanisms that allow a malicious actor remote access or control of the host, data exfiltration, and execution of unauthorized network applications. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |None |103
 
-|<<unusual-linux-network-configuration-discovery, Unusual Linux Network Configuration Discovery>> |Looks for commands related to system network configuration discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network configuration discovery in order to increase their understanding of connected networks and hosts. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |8.3.0 |104
+|<<unusual-linux-network-configuration-discovery, Unusual Linux Network Configuration Discovery>> |Looks for commands related to system network configuration discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network configuration discovery in order to increase their understanding of connected networks and hosts. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |None |104
 
-|<<unusual-linux-network-connection-discovery, Unusual Linux Network Connection Discovery>> |Looks for commands related to system network connection discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network connection discovery in order to increase their understanding of connected services and systems. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |8.3.0 |103
+|<<unusual-linux-network-connection-discovery, Unusual Linux Network Connection Discovery>> |Looks for commands related to system network connection discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system network connection discovery in order to increase their understanding of connected services and systems. This information may be used to shape follow-up behaviors such as lateral movement or additional discovery. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |None |103
 
-|<<unusual-linux-network-port-activity, Unusual Linux Network Port Activity>> |Identifies unusual destination port activity that can indicate command-and-control, persistence mechanism, or data exfiltration activity. Rarely used destination port activity is generally unusual in Linux fleets, and can indicate unauthorized access or threat actor activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |8.3.0 |103
+|<<unusual-linux-network-port-activity, Unusual Linux Network Port Activity>> |Identifies unusual destination port activity that can indicate command-and-control, persistence mechanism, or data exfiltration activity. Rarely used destination port activity is generally unusual in Linux fleets, and can indicate unauthorized access or threat actor activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |None |103
 
-|<<unusual-linux-process-calling-the-metadata-service, Unusual Linux Process Calling the Metadata Service>> |Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |8.3.0 |103
+|<<unusual-linux-process-calling-the-metadata-service, Unusual Linux Process Calling the Metadata Service>> |Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |None |103
 
-|<<unusual-linux-process-discovery-activity, Unusual Linux Process Discovery Activity>> |Looks for commands related to system process discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system process discovery in order to increase their understanding of software applications running on a target host or network. This may be a precursor to selection of a persistence mechanism or a method of privilege elevation. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |8.3.0 |103
+|<<unusual-linux-process-discovery-activity, Unusual Linux Process Discovery Activity>> |Looks for commands related to system process discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used by a threat actor to engage in system process discovery in order to increase their understanding of software applications running on a target host or network. This may be a precursor to selection of a persistence mechanism or a method of privilege elevation. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |None |103
 
-|<<unusual-linux-system-information-discovery-activity, Unusual Linux System Information Discovery Activity>> |Looks for commands related to system information discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system information discovery in order to gather detailed information about system configuration and software versions. This may be a precursor to selection of a persistence mechanism or a method of privilege elevation. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |8.3.0 |103
+|<<unusual-linux-system-information-discovery-activity, Unusual Linux System Information Discovery Activity>> |Looks for commands related to system information discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system information discovery in order to gather detailed information about system configuration and software versions. This may be a precursor to selection of a persistence mechanism or a method of privilege elevation. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |None |103
 
-|<<unusual-linux-user-calling-the-metadata-service, Unusual Linux User Calling the Metadata Service>> |Looks for anomalous access to the cloud platform metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |8.3.0 |103
+|<<unusual-linux-user-calling-the-metadata-service, Unusual Linux User Calling the Metadata Service>> |Looks for anomalous access to the cloud platform metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |None |103
 
-|<<unusual-linux-user-discovery-activity, Unusual Linux User Discovery Activity>> |Looks for commands related to system user or owner discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system owner or user discovery in order to identify currently active or primary users of a system. This may be a precursor to additional discovery, credential dumping or privilege elevation activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |8.3.0 |104
+|<<unusual-linux-user-discovery-activity, Unusual Linux User Discovery Activity>> |Looks for commands related to system user or owner discovery from an unusual user context. This can be due to uncommon troubleshooting activity or due to a compromised account. A compromised account may be used to engage in system owner or user discovery in order to identify currently active or primary users of a system. This may be a precursor to additional discovery, credential dumping or privilege elevation activity. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Discovery] |None |104
 
-|<<unusual-linux-username, Unusual Linux Username>> |A machine learning job detected activity for a username that is not normally active, which can indicate unauthorized changes, activity by unauthorized users, lateral movement, or compromised credentials. In many organizations, new usernames are not often created apart from specific types of system activities, such as creating new accounts for new employees. These user accounts quickly become active and routine. Events from rarely used usernames can point to suspicious activity. Additionally, automated Linux fleets tend to see activity from rarely used usernames only when personnel log in to make authorized or unauthorized changes, or threat actors have acquired credentials and log in for malicious purposes. Unusual usernames can also indicate pivoting, where compromised credentials are used to try and move laterally from one host to another. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |8.3.0 |103
+|<<unusual-linux-username, Unusual Linux Username>> |A machine learning job detected activity for a username that is not normally active, which can indicate unauthorized changes, activity by unauthorized users, lateral movement, or compromised credentials. In many organizations, new usernames are not often created apart from specific types of system activities, such as creating new accounts for new employees. These user accounts quickly become active and routine. Events from rarely used usernames can point to suspicious activity. Additionally, automated Linux fleets tend to see activity from rarely used usernames only when personnel log in to make authorized or unauthorized changes, or threat actors have acquired credentials and log in for malicious purposes. Unusual usernames can also indicate pivoting, where compromised credentials are used to try and move laterally from one host to another. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |None |103
 
-|<<unusual-login-activity, Unusual Login Activity>> |Identifies an unusually high number of authentication attempts. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |8.3.0 |103
+|<<unusual-login-activity, Unusual Login Activity>> |Identifies an unusually high number of authentication attempts. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |None |103
 
-|<<unusual-network-activity-from-a-windows-system-binary, Unusual Network Activity from a Windows System Binary>> |Identifies network activity from unexpected system applications. This may indicate adversarial activity as these applications are often leveraged by adversaries to execute code and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<unusual-network-activity-from-a-windows-system-binary, Unusual Network Activity from a Windows System Binary>> |Identifies network activity from unexpected system applications. This may indicate adversarial activity as these applications are often leveraged by adversaries to execute code and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |112
 
-|<<unusual-network-connection-via-dllhost, Unusual Network Connection via DllHost>> |Identifies unusual instances of dllhost.exe making outbound network connections. This may indicate adversarial Command and Control activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |107
+|<<unusual-network-connection-via-dllhost, Unusual Network Connection via DllHost>> |Identifies unusual instances of dllhost.exe making outbound network connections. This may indicate adversarial Command and Control activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |107
 
-|<<unusual-network-connection-via-rundll32, Unusual Network Connection via RunDLL32>> |Identifies unusual instances of rundll32.exe making outbound network connections. This may indicate adversarial Command and Control activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<unusual-network-connection-via-rundll32, Unusual Network Connection via RunDLL32>> |Identifies unusual instances of rundll32.exe making outbound network connections. This may indicate adversarial Command and Control activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Command and Control], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<unusual-network-destination-domain-name, Unusual Network Destination Domain Name>> |A machine learning job detected an unusual network destination domain name. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from an uncommon web server name. When malware is already running, it may send requests to an uncommon DNS domain the malware uses for command-and-control communication. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |8.3.0 |103
+|<<unusual-network-destination-domain-name, Unusual Network Destination Domain Name>> |A machine learning job detected an unusual network destination domain name. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from an uncommon web server name. When malware is already running, it may send requests to an uncommon DNS domain the malware uses for command-and-control communication. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |None |103
 
-|<<unusual-parent-process-for-cmd-exe, Unusual Parent Process for cmd.exe>> |Identifies a suspicious parent child process relationship with cmd.exe descending from an unusual process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<unusual-parent-process-for-cmd-exe, Unusual Parent Process for cmd.exe>> |Identifies a suspicious parent child process relationship with cmd.exe descending from an unusual process. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon], [Data Source: SentinelOne] |8.11.0 |212
 
-|<<unusual-parent-child-relationship, Unusual Parent-Child Relationship>> |Identifies Windows programs run from unexpected parent processes. This could indicate masquerading or other strange activity on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<unusual-parent-child-relationship, Unusual Parent-Child Relationship>> |Identifies Windows programs run from unexpected parent processes. This could indicate masquerading or other strange activity on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<unusual-persistence-via-services-registry, Unusual Persistence via Services Registry>> |Identifies processes modifying the services registry key directly, instead of through the expected Windows APIs. This could be an indication of an adversary attempting to stealthily persist through abnormal service creation or modification of an existing service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<unusual-persistence-via-services-registry, Unusual Persistence via Services Registry>> |Identifies processes modifying the services registry key directly, instead of through the expected Windows APIs. This could be an indication of an adversary attempting to stealthily persist through abnormal service creation or modification of an existing service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<unusual-print-spooler-child-process, Unusual Print Spooler Child Process>> |Detects unusual Print Spooler service (spoolsv.exe) child processes. This may indicate an attempt to exploit privilege escalation vulnerabilities related to the Printing Service on Windows. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |8.3.0 |108
+|<<unusual-print-spooler-child-process, Unusual Print Spooler Child Process>> |Detects unusual Print Spooler service (spoolsv.exe) child processes. This may indicate an attempt to exploit privilege escalation vulnerabilities related to the Printing Service on Windows. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Use Case: Vulnerability], [Data Source: Elastic Defend] |None |108
 
-|<<unusual-process-execution-path-alternate-data-stream, Unusual Process Execution Path - Alternate Data Stream>> |Identifies processes running from an Alternate Data Stream. This is uncommon for legitimate processes and sometimes done by adversaries to hide malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<unusual-process-execution-path-alternate-data-stream, Unusual Process Execution Path - Alternate Data Stream>> |Identifies processes running from an Alternate Data Stream. This is uncommon for legitimate processes and sometimes done by adversaries to hide malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |109
 
-|<<unusual-process-execution-on-wbem-path, Unusual Process Execution on WBEM Path>> |Identifies unusual processes running from the WBEM path, uncommon outside WMI-related Windows processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<unusual-process-execution-on-wbem-path, Unusual Process Execution on WBEM Path>> |Identifies unusual processes running from the WBEM path, uncommon outside WMI-related Windows processes. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |None |2
 
-|<<unusual-process-extension, Unusual Process Extension>> |Identifies processes running with unusual extensions that are not typically valid for Windows executables. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |4
+|<<unusual-process-extension, Unusual Process Extension>> |Identifies processes running with unusual extensions that are not typically valid for Windows executables. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Rule Type: BBR] |None |4
 
-|<<unusual-process-for-mssql-service-accounts, Unusual Process For MSSQL Service Accounts>> |Identifies unusual process executions using MSSQL Service accounts, which can indicate the exploitation/compromise of SQL instances. Attackers may exploit exposed MSSQL instances for initial access or lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |4
+|<<unusual-process-for-mssql-service-accounts, Unusual Process For MSSQL Service Accounts>> |Identifies unusual process executions using MSSQL Service accounts, which can indicate the exploitation/compromise of SQL instances. Attackers may exploit exposed MSSQL instances for initial access or lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Persistence], [Data Source: Elastic Defend], [Rule Type: BBR] |None |4
 
-|<<unusual-process-for-a-linux-host, Unusual Process For a Linux Host>> |Identifies rare processes that do not usually run on individual hosts, which can indicate execution of unauthorized services, malware, or persistence mechanisms. Processes are considered rare when they only run occasionally as compared with other processes running on the host. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence] |8.3.0 |104
+|<<unusual-process-for-a-linux-host, Unusual Process For a Linux Host>> |Identifies rare processes that do not usually run on individual hosts, which can indicate execution of unauthorized services, malware, or persistence mechanisms. Processes are considered rare when they only run occasionally as compared with other processes running on the host. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence] |None |104
 
-|<<unusual-process-for-a-windows-host, Unusual Process For a Windows Host>> |Identifies rare processes that do not usually run on individual hosts, which can indicate execution of unauthorized services, malware, or persistence mechanisms. Processes are considered rare when they only run occasionally as compared with other processes running on the host. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Resources: Investigation Guide] |8.3.0 |107
+|<<unusual-process-for-a-windows-host, Unusual Process For a Windows Host>> |Identifies rare processes that do not usually run on individual hosts, which can indicate execution of unauthorized services, malware, or persistence mechanisms. Processes are considered rare when they only run occasionally as compared with other processes running on the host. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Resources: Investigation Guide] |None |108
 
-|<<unusual-process-network-connection, Unusual Process Network Connection>> |Identifies network activity from unexpected system applications. This may indicate adversarial activity as these applications are often leveraged by adversaries to execute code and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |108
+|<<unusual-process-network-connection, Unusual Process Network Connection>> |Identifies network activity from unexpected system applications. This may indicate adversarial activity as these applications are often leveraged by adversaries to execute code and evade detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |108
 
-|<<unusual-process-spawned-by-a-host, Unusual Process Spawned by a Host>> |A machine learning job has detected a suspicious Windows process. This process has been classified as suspicious in two ways. It was predicted to be suspicious by the ProblemChild supervised ML model, and it was found to be an unusual process, on a host that does not commonly manifest malicious activity. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |8.9.0 |4
+|<<unusual-process-spawned-by-a-host, Unusual Process Spawned by a Host>> |A machine learning job has detected a suspicious Windows process. This process has been classified as suspicious in two ways. It was predicted to be suspicious by the ProblemChild supervised ML model, and it was found to be an unusual process, on a host that does not commonly manifest malicious activity. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |None |5
 
-|<<unusual-process-spawned-by-a-parent-process, Unusual Process Spawned by a Parent Process>> |A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be an unusual child process name, for the parent process, by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |8.9.0 |4
+|<<unusual-process-spawned-by-a-parent-process, Unusual Process Spawned by a Parent Process>> |A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be an unusual child process name, for the parent process, by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |None |5
 
-|<<unusual-process-spawned-by-a-user, Unusual Process Spawned by a User>> |A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be suspicious given that its user context is unusual and does not commonly manifest malicious activity,by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |8.9.0 |4
+|<<unusual-process-spawned-by-a-user, Unusual Process Spawned by a User>> |A machine learning job has detected a suspicious Windows process. This process has been classified as malicious in two ways. It was predicted to be malicious by the ProblemChild supervised ML model, and it was found to be suspicious given that its user context is unusual and does not commonly manifest malicious activity,by an unsupervised ML model. Such a process may be an instance of suspicious or malicious activity, possibly involving LOLbins, that may be resistant to detection using conventional search rules. |[Domain: Endpoint], [OS: Windows], [Use Case: Living off the Land Attack Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Defense Evasion] |None |5
 
-|<<unusual-process-writing-data-to-an-external-device, Unusual Process Writing Data to an External Device>> |A machine learning job has detected a rare process writing data to an external device. Malicious actors often use benign-looking processes to mask their data exfiltration activities. The discovery of such a process that has no legitimate reason to write data to external devices can indicate exfiltration. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |8.9.0 |3
+|<<unusual-process-writing-data-to-an-external-device, Unusual Process Writing Data to an External Device>> |A machine learning job has detected a rare process writing data to an external device. Malicious actors often use benign-looking processes to mask their data exfiltration activities. The discovery of such a process that has no legitimate reason to write data to external devices can indicate exfiltration. |[Use Case: Data Exfiltration Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Exfiltration] |None |4
 
-|<<unusual-remote-file-directory, Unusual Remote File Directory>> |An anomaly detection job has detected a remote file transfer on an unusual directory indicating a potential lateral movement activity on the host. Many Security solutions monitor well-known directories for suspicious activities, so attackers might use less common directories to bypass monitoring. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<unusual-remote-file-directory, Unusual Remote File Directory>> |An anomaly detection job has detected a remote file transfer on an unusual directory indicating a potential lateral movement activity on the host. Many Security solutions monitor well-known directories for suspicious activities, so attackers might use less common directories to bypass monitoring. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<unusual-remote-file-extension, Unusual Remote File Extension>> |An anomaly detection job has detected a remote file transfer with a rare extension, which could indicate potential lateral movement activity on the host. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<unusual-remote-file-extension, Unusual Remote File Extension>> |An anomaly detection job has detected a remote file transfer with a rare extension, which could indicate potential lateral movement activity on the host. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<unusual-remote-file-size, Unusual Remote File Size>> |A machine learning job has detected an unusually high file size shared by a remote host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Instead of multiple small transfers that can raise alarms, attackers might choose to bundle data into a single large file transfer. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<unusual-remote-file-size, Unusual Remote File Size>> |A machine learning job has detected an unusually high file size shared by a remote host indicating potential lateral movement activity. One of the primary goals of attackers after gaining access to a network is to locate and exfiltrate valuable information. Instead of multiple small transfers that can raise alarms, attackers might choose to bundle data into a single large file transfer. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<unusual-service-host-child-process-childless-service, Unusual Service Host Child Process - Childless Service>> |Identifies unusual child processes of Service Host (svchost.exe) that traditionally do not spawn any child processes. This may indicate a code injection or an equivalent form of exploitation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<unusual-service-host-child-process-childless-service, Unusual Service Host Child Process - Childless Service>> |Identifies unusual child processes of Service Host (svchost.exe) that traditionally do not spawn any child processes. This may indicate a code injection or an equivalent form of exploitation. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Privilege Escalation], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<unusual-source-ip-for-a-user-to-logon-from, Unusual Source IP for a User to Logon from>> |A machine learning job detected a user logging in from an IP address that is unusual for the user. This can be due to credentialed access via a compromised account when the user and the threat actor are in different locations. An unusual source IP address for a username could also be due to lateral movement when a compromised account is used to pivot between hosts. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |8.3.0 |103
+|<<unusual-source-ip-for-a-user-to-logon-from, Unusual Source IP for a User to Logon from>> |A machine learning job detected a user logging in from an IP address that is unusual for the user. This can be due to credentialed access via a compromised account when the user and the threat actor are in different locations. An unusual source IP address for a username could also be due to lateral movement when a compromised account is used to pivot between hosts. |[Use Case: Identity and Access Audit], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |None |103
 
-|<<unusual-sudo-activity, Unusual Sudo Activity>> |Looks for sudo activity from an unusual user context. An unusual sudo user could be due to troubleshooting activity or it could be a sign of credentialed access via compromised accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<unusual-sudo-activity, Unusual Sudo Activity>> |Looks for sudo activity from an unusual user context. An unusual sudo user could be due to troubleshooting activity or it could be a sign of credentialed access via compromised accounts. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Privilege Escalation] |None |103
 
-|<<unusual-time-or-day-for-an-rdp-session, Unusual Time or Day for an RDP Session>> |A machine learning job has detected an RDP session started at an usual time or weekday. An RDP session at an unusual time could be followed by other suspicious activities, so catching this is a good first step in detecting a larger attack. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |8.9.0 |3
+|<<unusual-time-or-day-for-an-rdp-session, Unusual Time or Day for an RDP Session>> |A machine learning job has detected an RDP session started at an usual time or weekday. An RDP session at an unusual time could be followed by other suspicious activities, so catching this is a good first step in detecting a larger attack. |[Use Case: Lateral Movement Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Lateral Movement] |None |4
 
-|<<unusual-user-privilege-enumeration-via-id, Unusual User Privilege Enumeration via id>> |This rule monitors for a sequence of 20 "id" command executions within 1 second by the same parent process. This behavior is unusual, and may be indicative of the execution of an enumeration script such as LinPEAS or LinEnum. These scripts leverage the "id" command to enumerate the privileges of all users present on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |8.3.0 |4
+|<<unusual-user-privilege-enumeration-via-id, Unusual User Privilege Enumeration via id>> |This rule monitors for a sequence of 20 "id" command executions within 1 second by the same parent process. This behavior is unusual, and may be indicative of the execution of an enumeration script such as LinPEAS or LinEnum. These scripts leverage the "id" command to enumerate the privileges of all users present on the system. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |None |4
 
-|<<unusual-web-request, Unusual Web Request>> |A machine learning job detected a rare and unusual URL that indicates unusual web browsing activity. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, in a strategic web compromise or watering hole attack, when a trusted website is compromised to target a particular sector or organization, targeted users may receive emails with uncommon URLs for trusted websites. These URLs can be used to download and run a payload. When malware is already running, it may send requests to uncommon URLs on trusted websites the malware uses for command-and-control communication. When rare URLs are observed being requested for a local web server by a remote source, these can be due to web scanning, enumeration or attack traffic, or they can be due to bots and web scrapers which are part of common Internet background traffic. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |8.3.0 |103
+|<<unusual-web-request, Unusual Web Request>> |A machine learning job detected a rare and unusual URL that indicates unusual web browsing activity. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, in a strategic web compromise or watering hole attack, when a trusted website is compromised to target a particular sector or organization, targeted users may receive emails with uncommon URLs for trusted websites. These URLs can be used to download and run a payload. When malware is already running, it may send requests to uncommon URLs on trusted websites the malware uses for command-and-control communication. When rare URLs are observed being requested for a local web server by a remote source, these can be due to web scanning, enumeration or attack traffic, or they can be due to bots and web scrapers which are part of common Internet background traffic. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |None |103
 
-|<<unusual-web-user-agent, Unusual Web User Agent>> |A machine learning job detected a rare and unusual user agent indicating web browsing activity by an unusual process other than a web browser. This can be due to persistence, command-and-control, or exfiltration activity. Uncommon user agents coming from remote sources to local destinations are often the result of scanners, bots, and web scrapers, which are part of common Internet background traffic. Much of this is noise, but more targeted attacks on websites using tools like Burp or SQLmap can sometimes be discovered by spotting uncommon user agents. Uncommon user agents in traffic from local sources to remote destinations can be any number of things, including harmless programs like weather monitoring or stock-trading programs. However, uncommon user agents from local sources can also be due to malware or scanning activity. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |8.3.0 |103
+|<<unusual-web-user-agent, Unusual Web User Agent>> |A machine learning job detected a rare and unusual user agent indicating web browsing activity by an unusual process other than a web browser. This can be due to persistence, command-and-control, or exfiltration activity. Uncommon user agents coming from remote sources to local destinations are often the result of scanners, bots, and web scrapers, which are part of common Internet background traffic. Much of this is noise, but more targeted attacks on websites using tools like Burp or SQLmap can sometimes be discovered by spotting uncommon user agents. Uncommon user agents in traffic from local sources to remote destinations can be any number of things, including harmless programs like weather monitoring or stock-trading programs. However, uncommon user agents from local sources can also be due to malware or scanning activity. |[Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Command and Control] |None |103
 
-|<<unusual-windows-network-activity, Unusual Windows Network Activity>> |Identifies Windows processes that do not usually use the network but have unexpected network activity, which can indicate command-and-control, lateral movement, persistence, or data exfiltration activity. A process with unusual network activity can denote process exploitation or injection, where the process is used to run persistence mechanisms that allow a malicious actor remote access or control of the host, data exfiltration, and execution of unauthorized network applications. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |8.3.0 |103
+|<<unusual-windows-network-activity, Unusual Windows Network Activity>> |Identifies Windows processes that do not usually use the network but have unexpected network activity, which can indicate command-and-control, lateral movement, persistence, or data exfiltration activity. A process with unusual network activity can denote process exploitation or injection, where the process is used to run persistence mechanisms that allow a malicious actor remote access or control of the host, data exfiltration, and execution of unauthorized network applications. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning] |None |103
 
-|<<unusual-windows-path-activity, Unusual Windows Path Activity>> |Identifies processes started from atypical folders in the file system, which might indicate malware execution or persistence mechanisms. In corporate Windows environments, software installation is centrally managed and it is unusual for programs to be executed from user or temporary directories. Processes executed from these locations can denote that a user downloaded software directly from the Internet or a malicious script or macro executed malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Tactic: Execution] |8.3.0 |104
+|<<unusual-windows-path-activity, Unusual Windows Path Activity>> |Identifies processes started from atypical folders in the file system, which might indicate malware execution or persistence mechanisms. In corporate Windows environments, software installation is centrally managed and it is unusual for programs to be executed from user or temporary directories. Processes executed from these locations can denote that a user downloaded software directly from the Internet or a malicious script or macro executed malware. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence], [Tactic: Execution] |None |104
 
-|<<unusual-windows-process-calling-the-metadata-service, Unusual Windows Process Calling the Metadata Service>> |Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |8.3.0 |103
+|<<unusual-windows-process-calling-the-metadata-service, Unusual Windows Process Calling the Metadata Service>> |Looks for anomalous access to the metadata service by an unusual process. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |None |103
 
-|<<unusual-windows-remote-user, Unusual Windows Remote User>> |A machine learning job detected an unusual remote desktop protocol (RDP) username, which can indicate account takeover or credentialed persistence using compromised accounts. RDP attacks, such as BlueKeep, also tend to use unusual usernames. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |8.3.0 |103
+|<<unusual-windows-remote-user, Unusual Windows Remote User>> |A machine learning job detected an unusual remote desktop protocol (RDP) username, which can indicate account takeover or credentialed persistence using compromised accounts. RDP attacks, such as BlueKeep, also tend to use unusual usernames. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |None |103
 
-|<<unusual-windows-service, Unusual Windows Service>> |A machine learning job detected an unusual Windows service, This can indicate execution of unauthorized services, malware, or persistence mechanisms. In corporate Windows environments, hosts do not generally run many rare or unique services. This job helps detect malware and persistence mechanisms that have been installed and run as a service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence] |8.3.0 |103
+|<<unusual-windows-service, Unusual Windows Service>> |A machine learning job detected an unusual Windows service, This can indicate execution of unauthorized services, malware, or persistence mechanisms. In corporate Windows environments, hosts do not generally run many rare or unique services. This job helps detect malware and persistence mechanisms that have been installed and run as a service. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Persistence] |None |103
 
-|<<unusual-windows-user-calling-the-metadata-service, Unusual Windows User Calling the Metadata Service>> |Looks for anomalous access to the cloud platform metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |8.3.0 |103
+|<<unusual-windows-user-calling-the-metadata-service, Unusual Windows User Calling the Metadata Service>> |Looks for anomalous access to the cloud platform metadata service by an unusual user. The metadata service may be targeted in order to harvest credentials or user data scripts containing secrets. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Credential Access] |None |103
 
-|<<unusual-windows-user-privilege-elevation-activity, Unusual Windows User Privilege Elevation Activity>> |A machine learning job detected an unusual user context switch, using the runas command or similar techniques, which can indicate account takeover or privilege escalation using compromised accounts. Privilege elevation using tools like runas are more commonly used by domain and network administrators than by regular Windows users. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Privilege Escalation] |8.3.0 |103
+|<<unusual-windows-user-privilege-elevation-activity, Unusual Windows User Privilege Elevation Activity>> |A machine learning job detected an unusual user context switch, using the runas command or similar techniques, which can indicate account takeover or privilege escalation using compromised accounts. Privilege elevation using tools like runas are more commonly used by domain and network administrators than by regular Windows users. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Privilege Escalation] |None |103
 
-|<<unusual-windows-username, Unusual Windows Username>> |A machine learning job detected activity for a username that is not normally active, which can indicate unauthorized changes, activity by unauthorized users, lateral movement, or compromised credentials. In many organizations, new usernames are not often created apart from specific types of system activities, such as creating new accounts for new employees. These user accounts quickly become active and routine. Events from rarely used usernames can point to suspicious activity. Additionally, automated Linux fleets tend to see activity from rarely used usernames only when personnel log in to make authorized or unauthorized changes, or threat actors have acquired credentials and log in for malicious purposes. Unusual usernames can also indicate pivoting, where compromised credentials are used to try and move laterally from one host to another. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |8.3.0 |104
+|<<unusual-windows-username, Unusual Windows Username>> |A machine learning job detected activity for a username that is not normally active, which can indicate unauthorized changes, activity by unauthorized users, lateral movement, or compromised credentials. In many organizations, new usernames are not often created apart from specific types of system activities, such as creating new accounts for new employees. These user accounts quickly become active and routine. Events from rarely used usernames can point to suspicious activity. Additionally, automated Linux fleets tend to see activity from rarely used usernames only when personnel log in to make authorized or unauthorized changes, or threat actors have acquired credentials and log in for malicious purposes. Unusual usernames can also indicate pivoting, where compromised credentials are used to try and move laterally from one host to another. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Rule Type: ML], [Rule Type: Machine Learning], [Tactic: Initial Access] |None |104
 
-|<<user-account-creation, User Account Creation>> |Identifies attempts to create new users. This is sometimes done by attackers to increase access or establish persistence on a system or domain. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |109
+|<<user-account-creation, User Account Creation>> |Identifies attempts to create new users. This is sometimes done by attackers to increase access or establish persistence on a system or domain. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |109
 
-|<<user-added-as-owner-for-azure-application, User Added as Owner for Azure Application>> |Identifies when a user is added as an owner for an Azure application. An adversary may add a user account as an owner for an Azure application in order to grant additional permissions and modify the application's configuration using another account. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |8.3.0 |102
+|<<user-added-as-owner-for-azure-application, User Added as Owner for Azure Application>> |Identifies when a user is added as an owner for an Azure application. An adversary may add a user account as an owner for an Azure application in order to grant additional permissions and modify the application's configuration using another account. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |None |102
 
-|<<user-added-as-owner-for-azure-service-principal, User Added as Owner for Azure Service Principal>> |Identifies when a user is added as an owner for an Azure service principal. The service principal object defines what the application can do in the specific tenant, who can access the application, and what resources the app can access. A service principal object is created when an application is given permission to access resources in a tenant. An adversary may add a user account as an owner for a service principal and use that account in order to define what an application can do in the Azure AD tenant. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |8.3.0 |102
+|<<user-added-as-owner-for-azure-service-principal, User Added as Owner for Azure Service Principal>> |Identifies when a user is added as an owner for an Azure service principal. The service principal object defines what the application can do in the specific tenant, who can access the application, and what resources the app can access. A service principal object is created when an application is given permission to access resources in a tenant. An adversary may add a user account as an owner for a service principal and use that account in order to define what an application can do in the Azure AD tenant. |[Domain: Cloud], [Data Source: Azure], [Use Case: Configuration Audit], [Tactic: Persistence] |None |102
 
-|<<user-added-to-privileged-group, User Added to Privileged Group>> |Identifies a user being added to a privileged group in Active Directory. Privileged accounts and groups in Active Directory are those to which powerful rights, privileges, and permissions are granted that allow them to perform nearly any action in Active Directory and on domain-joined systems. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |8.3.0 |109
+|<<user-added-to-privileged-group, User Added to Privileged Group>> |Identifies a user being added to a privileged group in Active Directory. Privileged accounts and groups in Active Directory are those to which powerful rights, privileges, and permissions are granted that allow them to perform nearly any action in Active Directory and on domain-joined systems. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring], [Data Source: Active Directory] |None |109
 
-|<<user-account-exposed-to-kerberoasting, User account exposed to Kerberoasting>> |Detects when a user account has the servicePrincipalName attribute modified. Attackers can abuse write privileges over a user to configure Service Principle Names (SPNs) so that they can perform Kerberoasting. Administrators can also configure this for legitimate purposes, exposing the account to Kerberoasting. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |8.3.0 |109
+|<<user-account-exposed-to-kerberoasting, User account exposed to Kerberoasting>> |Detects when a user account has the servicePrincipalName attribute modified. Attackers can abuse write privileges over a user to configure Service Principle Names (SPNs) so that they can perform Kerberoasting. Administrators can also configure this for legitimate purposes, exposing the account to Kerberoasting. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Active Directory], [Resources: Investigation Guide], [Use Case: Active Directory Monitoring] |None |109
 
-|<<vnc-virtual-network-computing-from-the-internet, VNC (Virtual Network Computing) from the Internet>> |This rule detects network events that may indicate the use of VNC traffic from the Internet. VNC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |8.3.0 |104
+|<<vnc-virtual-network-computing-from-the-internet, VNC (Virtual Network Computing) from the Internet>> |This rule detects network events that may indicate the use of VNC traffic from the Internet. VNC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |None |104
 
-|<<vnc-virtual-network-computing-to-the-internet, VNC (Virtual Network Computing) to the Internet>> |This rule detects network events that may indicate the use of VNC traffic to the Internet. VNC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |8.3.0 |104
+|<<vnc-virtual-network-computing-to-the-internet, VNC (Virtual Network Computing) to the Internet>> |This rule detects network events that may indicate the use of VNC traffic to the Internet. VNC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. |[Tactic: Command and Control], [Domain: Endpoint], [Use Case: Threat Detection] |None |104
 
-|<<veeam-backup-library-loaded-by-unusual-process, Veeam Backup Library Loaded by Unusual Process>> |Identifies potential credential decrypt operations by PowerShell or unsigned processes using the Veeam.Backup.Common.dll library. Attackers can use Veeam Credentials to target backups as part of destructive operations such as Ransomware attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.3.0 |2
+|<<veeam-backup-library-loaded-by-unusual-process, Veeam Backup Library Loaded by Unusual Process>> |Identifies potential credential decrypt operations by PowerShell or unsigned processes using the Veeam.Backup.Common.dll library. Attackers can use Veeam Credentials to target backups as part of destructive operations such as Ransomware attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |2
 
-|<<virtual-machine-fingerprinting, Virtual Machine Fingerprinting>> |An adversary may attempt to get detailed information about the operating system and hardware. This rule identifies common locations used to discover virtual machine hardware by a non-root user. This technique has been used by the Pupy RAT and other malware. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |108
+|<<virtual-machine-fingerprinting, Virtual Machine Fingerprinting>> |An adversary may attempt to get detailed information about the operating system and hardware. This rule identifies common locations used to discover virtual machine hardware by a non-root user. This technique has been used by the Pupy RAT and other malware. |[Domain: Endpoint], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |108
 
-|<<virtual-machine-fingerprinting-via-grep, Virtual Machine Fingerprinting via Grep>> |An adversary may attempt to get detailed information about the operating system and hardware. This rule identifies common locations used to discover virtual machine hardware by a non-root user. This technique has been used by the Pupy RAT and other malware. |[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |8.3.0 |105
+|<<virtual-machine-fingerprinting-via-grep, Virtual Machine Fingerprinting via Grep>> |An adversary may attempt to get detailed information about the operating system and hardware. This rule identifies common locations used to discover virtual machine hardware by a non-root user. This technique has been used by the Pupy RAT and other malware. |[Domain: Endpoint], [OS: macOS], [OS: Linux], [Use Case: Threat Detection], [Tactic: Discovery], [Data Source: Elastic Defend] |None |105
 
-|<<virtual-private-network-connection-attempt, Virtual Private Network Connection Attempt>> |Identifies the execution of macOS built-in commands to connect to an existing Virtual Private Network (VPN). Adversaries may use VPN connections to laterally move and control remote systems on a network. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |8.3.0 |107
+|<<virtual-private-network-connection-attempt, Virtual Private Network Connection Attempt>> |Identifies the execution of macOS built-in commands to connect to an existing Virtual Private Network (VPN). Adversaries may use VPN connections to laterally move and control remote systems on a network. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend] |None |107
 
-|<<volume-shadow-copy-deleted-or-resized-via-vssadmin, Volume Shadow Copy Deleted or Resized via VssAdmin>> |Identifies use of vssadmin.exe for shadow copy deletion or resizing on endpoints. This commonly occurs in tandem with ransomware or other destructive attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<volume-shadow-copy-deleted-or-resized-via-vssadmin, Volume Shadow Copy Deleted or Resized via VssAdmin>> |Identifies use of vssadmin.exe for shadow copy deletion or resizing on endpoints. This commonly occurs in tandem with ransomware or other destructive attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<volume-shadow-copy-deletion-via-powershell, Volume Shadow Copy Deletion via PowerShell>> |Identifies the use of the Win32_ShadowCopy class and related cmdlets to achieve shadow copy deletion. This commonly occurs in tandem with ransomware or other destructive attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<volume-shadow-copy-deletion-via-powershell, Volume Shadow Copy Deletion via PowerShell>> |Identifies the use of the Win32_ShadowCopy class and related cmdlets to achieve shadow copy deletion. This commonly occurs in tandem with ransomware or other destructive attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<volume-shadow-copy-deletion-via-wmic, Volume Shadow Copy Deletion via WMIC>> |Identifies use of wmic.exe for shadow copy deletion on endpoints. This commonly occurs in tandem with ransomware or other destructive attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<volume-shadow-copy-deletion-via-wmic, Volume Shadow Copy Deletion via WMIC>> |Identifies use of wmic.exe for shadow copy deletion on endpoints. This commonly occurs in tandem with ransomware or other destructive attacks. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Impact], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<wmi-incoming-lateral-movement, WMI Incoming Lateral Movement>> |Identifies processes executed via Windows Management Instrumentation (WMI) on a remote host. This could be indicative of adversary lateral movement, but could be noisy if administrators use WMI to remotely manage hosts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |110
+|<<wmi-incoming-lateral-movement, WMI Incoming Lateral Movement>> |Identifies processes executed via Windows Management Instrumentation (WMI) on a remote host. This could be indicative of adversary lateral movement, but could be noisy if administrators use WMI to remotely manage hosts. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<wmi-wbemtest-utility-execution, WMI WBEMTEST Utility Execution>> |Adversaries may abuse the WMI diagnostic tool, wbemtest.exe, to enumerate WMI object instances or invoke methods against local or remote endpoints. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |8.3.0 |2
+|<<wmi-wbemtest-utility-execution, WMI WBEMTEST Utility Execution>> |Adversaries may abuse the WMI diagnostic tool, wbemtest.exe, to enumerate WMI object instances or invoke methods against local or remote endpoints. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Execution], [Data Source: Elastic Defend], [Rule Type: BBR], [Data Source: Elastic Endgame] |None |2
 
-|<<wmic-remote-command, WMIC Remote Command>> |Identifies the use of wmic.exe to run commands on remote hosts. While this can be used by administrators legitimately, attackers can abuse this built-in utility to achieve lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |4
+|<<wmic-remote-command, WMIC Remote Command>> |Identifies the use of wmic.exe to run commands on remote hosts. While this can be used by administrators legitimately, attackers can abuse this built-in utility to achieve lateral movement. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Data Source: Elastic Defend], [Rule Type: BBR] |None |4
 
 |<<wpad-service-exploit, WPAD Service Exploit>> |Identifies probable exploitation of the Web Proxy Auto-Discovery Protocol (WPAD) service. Attackers who have access to the local network or upstream DNS traffic can inject malicious JavaScript to the WPAD service which can lead to a full system compromise. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation], [Data Source: Elastic Defend] |None |1
 
-|<<writedac-access-on-active-directory-object, WRITEDAC Access on Active Directory Object>> |Identifies the access on an object with WRITEDAC permissions. With the WRITEDAC permission, the user can perform a Write Discretionary Access Control List (WriteDACL) operation, which is used to modify the access control rules associated with a specific object within Active Directory. Attackers may abuse this privilege to grant themselves or other compromised accounts additional rights, ultimately compromising the target object, resulting in privilege escalation, lateral movement, and persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Active Directory], [Use Case: Active Directory Monitoring], [Rule Type: BBR] |8.3.0 |4
+|<<writedac-access-on-active-directory-object, WRITEDAC Access on Active Directory Object>> |Identifies the access on an object with WRITEDAC permissions. With the WRITEDAC permission, the user can perform a Write Discretionary Access Control List (WriteDACL) operation, which is used to modify the access control rules associated with a specific object within Active Directory. Attackers may abuse this privilege to grant themselves or other compromised accounts additional rights, ultimately compromising the target object, resulting in privilege escalation, lateral movement, and persistence. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Active Directory], [Use Case: Active Directory Monitoring], [Rule Type: BBR] |None |4
 
-|<<web-application-suspicious-activity-post-request-declined, Web Application Suspicious Activity: POST Request Declined>> |A POST request to a web application returned a 403 response, which indicates the web application declined to process the request because the action requested was not allowed. |[Data Source: APM] |8.3.0 |102
+|<<web-application-suspicious-activity-post-request-declined, Web Application Suspicious Activity: POST Request Declined>> |A POST request to a web application returned a 403 response, which indicates the web application declined to process the request because the action requested was not allowed. |[Data Source: APM] |None |102
 
-|<<web-application-suspicious-activity-unauthorized-method, Web Application Suspicious Activity: Unauthorized Method>> |A request to a web application returned a 405 response, which indicates the web application declined to process the request because the HTTP method is not allowed for the resource. |[Data Source: APM] |8.3.0 |102
+|<<web-application-suspicious-activity-unauthorized-method, Web Application Suspicious Activity: Unauthorized Method>> |A request to a web application returned a 405 response, which indicates the web application declined to process the request because the HTTP method is not allowed for the resource. |[Data Source: APM] |None |102
 
-|<<web-application-suspicious-activity-sqlmap-user-agent, Web Application Suspicious Activity: sqlmap User Agent>> |This is an example of how to detect an unwanted web client user agent. This search matches the user agent for sqlmap 1.3.11, which is a popular FOSS tool for testing web applications for SQL injection vulnerabilities. |[Data Source: APM] |8.3.0 |102
+|<<web-application-suspicious-activity-sqlmap-user-agent, Web Application Suspicious Activity: sqlmap User Agent>> |This is an example of how to detect an unwanted web client user agent. This search matches the user agent for sqlmap 1.3.11, which is a popular FOSS tool for testing web applications for SQL injection vulnerabilities. |[Data Source: APM] |None |102
 
-|<<web-shell-detection-script-process-child-of-common-web-processes, Web Shell Detection: Script Process Child of Common Web Processes>> |Identifies suspicious commands executed via a web server, which may suggest a vulnerability and remote shell access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Initial Access], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<web-shell-detection-script-process-child-of-common-web-processes, Web Shell Detection: Script Process Child of Common Web Processes>> |Identifies suspicious commands executed via a web server, which may suggest a vulnerability and remote shell access. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Tactic: Initial Access], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: SentinelOne] |8.11.0 |213
 
-|<<webproxy-settings-modification, WebProxy Settings Modification>> |Identifies the use of the built-in networksetup command to configure webproxy settings. This may indicate an attempt to hijack web browser traffic for credential access via traffic sniffing or redirection. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |8.7.0 |206
+|<<webproxy-settings-modification, WebProxy Settings Modification>> |Identifies the use of the built-in networksetup command to configure webproxy settings. This may indicate an attempt to hijack web browser traffic for credential access via traffic sniffing or redirection. |[Domain: Endpoint], [OS: macOS], [Use Case: Threat Detection], [Tactic: Credential Access], [Data Source: Elastic Defend] |None |206
 
-|<<webserver-access-logs-deleted, WebServer Access Logs Deleted>> |Identifies the deletion of WebServer access logs. This may indicate an attempt to evade detection or destroy forensic evidence on a system. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |105
+|<<webserver-access-logs-deleted, WebServer Access Logs Deleted>> |Identifies the deletion of WebServer access logs. This may indicate an attempt to evade detection or destroy forensic evidence on a system. |[Domain: Endpoint], [OS: Linux], [OS: Windows], [OS: macOS], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |105
 
-|<<werfault-reflectdebugger-persistence, Werfault ReflectDebugger Persistence>> |Identifies the registration of a Werfault Debugger. Attackers may abuse this mechanism to execute malicious payloads every time the utility is executed with the "-pr" parameter. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |2
+|<<werfault-reflectdebugger-persistence, Werfault ReflectDebugger Persistence>> |Identifies the registration of a Werfault Debugger. Attackers may abuse this mechanism to execute malicious payloads every time the utility is executed with the "-pr" parameter. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |2
 
-|<<whoami-process-activity, Whoami Process Activity>> |Identifies suspicious use of whoami.exe which displays user, group, and privileges information for the user who is currently logged on to the local system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |111
+|<<whoami-process-activity, Whoami Process Activity>> |Identifies suspicious use of whoami.exe which displays user, group, and privileges information for the user who is currently logged on to the local system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |111
 
-|<<windows-account-or-group-discovery, Windows Account or Group Discovery>> |This rule identifies the execution of commands that enumerates account or group information. Adversaries may use built-in applications to get a listing of local system or domain accounts and groups. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |4
+|<<windows-account-or-group-discovery, Windows Account or Group Discovery>> |This rule identifies the execution of commands that enumerates account or group information. Adversaries may use built-in applications to get a listing of local system or domain accounts and groups. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |None |5
 
-|<<windows-cryptoapi-spoofing-vulnerability-cve-2020-0601-curveball, Windows CryptoAPI Spoofing Vulnerability (CVE-2020-0601 - CurveBall)>> |A spoofing vulnerability exists in the way Windows CryptoAPI (Crypt32.dll) validates Elliptic Curve Cryptography (ECC) certificates. An attacker could exploit the vulnerability by using a spoofed code-signing certificate to sign a malicious executable, making it appear the file was from a trusted, legitimate source. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Use Case: Vulnerability] |8.3.0 |104
+|<<windows-cryptoapi-spoofing-vulnerability-cve-2020-0601-curveball, Windows CryptoAPI Spoofing Vulnerability (CVE-2020-0601 - CurveBall)>> |A spoofing vulnerability exists in the way Windows CryptoAPI (Crypt32.dll) validates Elliptic Curve Cryptography (ECC) certificates. An attacker could exploit the vulnerability by using a spoofed code-signing certificate to sign a malicious executable, making it appear the file was from a trusted, legitimate source. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Use Case: Vulnerability] |None |104
 
-|<<windows-defender-disabled-via-registry-modification, Windows Defender Disabled via Registry Modification>> |Identifies modifications to the Windows Defender registry settings to disable the service or set the service to be started manually. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<windows-defender-disabled-via-registry-modification, Windows Defender Disabled via Registry Modification>> |Identifies modifications to the Windows Defender registry settings to disable the service or set the service to be started manually. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |112
 
-|<<windows-defender-exclusions-added-via-powershell, Windows Defender Exclusions Added via PowerShell>> |Identifies modifications to the Windows Defender configuration settings using PowerShell to add exclusions at the folder directory or process level. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<windows-defender-exclusions-added-via-powershell, Windows Defender Exclusions Added via PowerShell>> |Identifies modifications to the Windows Defender configuration settings using PowerShell to add exclusions at the folder directory or process level. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<windows-event-logs-cleared, Windows Event Logs Cleared>> |Identifies attempts to clear Windows event log stores. This is often done by attackers in an attempt to evade detection or destroy forensic evidence on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide] |8.3.0 |108
+|<<windows-event-logs-cleared, Windows Event Logs Cleared>> |Identifies attempts to clear Windows event log stores. This is often done by attackers in an attempt to evade detection or destroy forensic evidence on a system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Resources: Investigation Guide] |None |108
 
-|<<windows-firewall-disabled-via-powershell, Windows Firewall Disabled via PowerShell>> |Identifies when the Windows Firewall is disabled using PowerShell cmdlets, which can help attackers evade network constraints, like internet and network lateral communication restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |110
+|<<windows-firewall-disabled-via-powershell, Windows Firewall Disabled via PowerShell>> |Identifies when the Windows Firewall is disabled using PowerShell cmdlets, which can help attackers evade network constraints, like internet and network lateral communication restrictions. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |110
 
-|<<windows-installer-with-suspicious-properties, Windows Installer with Suspicious Properties>> |Identifies the execution of an installer from an archive or with suspicious properties. Adversaries may abuse msiexec.exe to launch local or network accessible MSI files in an attempt to bypass application whitelisting. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |1
+|<<windows-installer-with-suspicious-properties, Windows Installer with Suspicious Properties>> |Identifies the execution of an installer from an archive or with suspicious properties. Adversaries may abuse msiexec.exe to launch local or network accessible MSI files in an attempt to bypass application whitelisting. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Rule Type: BBR], [Data Source: Elastic Defend] |None |1
 
-|<<windows-network-enumeration, Windows Network Enumeration>> |Identifies attempts to enumerate hosts in a network using the built-in Windows net.exe tool. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |8.3.0 |111
+|<<windows-network-enumeration, Windows Network Enumeration>> |Identifies attempts to enumerate hosts in a network using the built-in Windows net.exe tool. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Tactic: Collection], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Rule Type: BBR] |None |111
 
-|<<windows-registry-file-creation-in-smb-share, Windows Registry File Creation in SMB Share>> |Identifies the creation or modification of a medium-size registry hive file on a Server Message Block (SMB) share, which may indicate an exfiltration attempt of a previously dumped Security Account Manager (SAM) registry hive for credential extraction on an attacker-controlled system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |108
+|<<windows-registry-file-creation-in-smb-share, Windows Registry File Creation in SMB Share>> |Identifies the creation or modification of a medium-size registry hive file on a Server Message Block (SMB) share, which may indicate an exfiltration attempt of a previously dumped Security Account Manager (SAM) registry hive for credential extraction on an attacker-controlled system. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Lateral Movement], [Tactic: Credential Access], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |108
 
-|<<windows-script-executing-powershell, Windows Script Executing PowerShell>> |Identifies a PowerShell process launched by either cscript.exe or wscript.exe. Observing Windows scripting processes executing a PowerShell script, may be indicative of malicious activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |111
+|<<windows-script-executing-powershell, Windows Script Executing PowerShell>> |Identifies a PowerShell process launched by either cscript.exe or wscript.exe. Observing Windows scripting processes executing a PowerShell script, may be indicative of malicious activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Resources: Investigation Guide], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |111
 
-|<<windows-script-interpreter-executing-process-via-wmi, Windows Script Interpreter Executing Process via WMI>> |Identifies use of the built-in Windows script interpreters (cscript.exe or wscript.exe) being used to execute a process via Windows Management Instrumentation (WMI). This may be indicative of malicious activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |109
+|<<windows-script-interpreter-executing-process-via-wmi, Windows Script Interpreter Executing Process via WMI>> |Identifies use of the built-in Windows script interpreters (cscript.exe or wscript.exe) being used to execute a process via Windows Management Instrumentation (WMI). This may be indicative of malicious activity. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Initial Access], [Tactic: Execution], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |110
 
-|<<windows-service-installed-via-an-unusual-client, Windows Service Installed via an Unusual Client>> |Identifies the creation of a Windows service by an unusual client process. Services may be created with administrator privileges but are executed under SYSTEM privileges, so an adversary may also use a service to escalate privileges from administrator to SYSTEM. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |8.3.0 |109
+|<<windows-service-installed-via-an-unusual-client, Windows Service Installed via an Unusual Client>> |Identifies the creation of a Windows service by an unusual client process. Services may be created with administrator privileges but are executed under SYSTEM privileges, so an adversary may also use a service to escalate privileges from administrator to SYSTEM. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Privilege Escalation] |None |109
 
-|<<windows-subsystem-for-linux-distribution-installed, Windows Subsystem for Linux Distribution Installed>> |Detects changes to the registry that indicates the install of a new Windows Subsystem for Linux distribution by name. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |8.3.0 |7
+|<<windows-subsystem-for-linux-distribution-installed, Windows Subsystem for Linux Distribution Installed>> |Detects changes to the registry that indicates the install of a new Windows Subsystem for Linux distribution by name. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend], [Data Source: Sysmon] |None |7
 
-|<<windows-subsystem-for-linux-enabled-via-dism-utility, Windows Subsystem for Linux Enabled via Dism Utility>> |Detects attempts to enable the Windows Subsystem for Linux using Microsoft Dism utility. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |8.3.0 |7
+|<<windows-subsystem-for-linux-enabled-via-dism-utility, Windows Subsystem for Linux Enabled via Dism Utility>> |Detects attempts to enable the Windows Subsystem for Linux using Microsoft Dism utility. Adversaries may enable and use WSL for Linux to avoid detection. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Defense Evasion], [Data Source: Elastic Endgame], [Data Source: Elastic Defend] |None |7
 
-|<<windows-system-information-discovery, Windows System Information Discovery>> |Detects the execution of commands used to discover information about the system, which attackers may use after compromising a system to gain situational awareness. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |8.3.0 |4
+|<<windows-system-information-discovery, Windows System Information Discovery>> |Detects the execution of commands used to discover information about the system, which attackers may use after compromising a system to gain situational awareness. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend], [Data Source: Elastic Endgame] |None |4
 
-|<<windows-system-network-connections-discovery, Windows System Network Connections Discovery>> |This rule identifies the execution of commands that can be used to enumerate network connections. Adversaries may attempt to get a listing of network connections to or from a compromised system to identify targets within an environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |8.3.0 |4
+|<<windows-system-network-connections-discovery, Windows System Network Connections Discovery>> |This rule identifies the execution of commands that can be used to enumerate network connections. Adversaries may attempt to get a listing of network connections to or from a compromised system to identify targets within an environment. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Discovery], [Rule Type: BBR], [Data Source: Elastic Defend] |None |4
 
 |<<windows-user-account-creation, Windows User Account Creation>> |Identifies attempts to create a Windows User Account. This is sometimes done by attackers to persist or increase access to a system or domain. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Persistence] |None |1
 
-|<<wireless-credential-dumping-using-netsh-command, Wireless Credential Dumping using Netsh Command>> |Identifies attempts to dump Wireless saved access keys in clear text using the Windows built-in utility Netsh. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Discovery], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |8.3.0 |8
+|<<wireless-credential-dumping-using-netsh-command, Wireless Credential Dumping using Netsh Command>> |Identifies attempts to dump Wireless saved access keys in clear text using the Windows built-in utility Netsh. |[Domain: Endpoint], [OS: Windows], [Use Case: Threat Detection], [Tactic: Credential Access], [Tactic: Discovery], [Data Source: Elastic Endgame], [Resources: Investigation Guide], [Data Source: Elastic Defend] |None |8
 
-|<<zoom-meeting-with-no-passcode, Zoom Meeting with no Passcode>> |This rule identifies Zoom meetings that are created without a passcode. Meetings without a passcode are susceptible to Zoombombing. Zoombombing is carried out by taking advantage of Zoom sessions that are not protected with a passcode. Zoombombing refers to the unwanted, disruptive intrusion, generally by Internet trolls and hackers, into a video conference call. In a typical Zoombombing incident, a teleconferencing session is hijacked by the insertion of material that is lewd, obscene, racist, or antisemitic in nature, typically resulting of the shutdown of the session. |[Data Source: Zoom], [Use Case: Configuration Audit], [Tactic: Initial Access] |8.3.0 |103
+|<<zoom-meeting-with-no-passcode, Zoom Meeting with no Passcode>> |This rule identifies Zoom meetings that are created without a passcode. Meetings without a passcode are susceptible to Zoombombing. Zoombombing is carried out by taking advantage of Zoom sessions that are not protected with a passcode. Zoombombing refers to the unwanted, disruptive intrusion, generally by Internet trolls and hackers, into a video conference call. In a typical Zoombombing incident, a teleconferencing session is hijacked by the insertion of material that is lewd, obscene, racist, or antisemitic in nature, typically resulting of the shutdown of the session. |[Data Source: Zoom], [Use Case: Configuration Audit], [Tactic: Initial Access] |None |103
 
 |==============================================
diff --git a/docs/detections/prebuilt-rules/rule-desc-index.asciidoc b/docs/detections/prebuilt-rules/rule-desc-index.asciidoc
index f1d6db5ef0..d9d99c89bc 100644
--- a/docs/detections/prebuilt-rules/rule-desc-index.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-desc-index.asciidoc
@@ -50,6 +50,7 @@ include::rule-details/aws-route-table-created.asciidoc[]
 include::rule-details/aws-route-table-modified-or-deleted.asciidoc[]
 include::rule-details/aws-route53-private-hosted-zone-associated-with-a-vpc.asciidoc[]
 include::rule-details/aws-s3-bucket-configuration-deletion.asciidoc[]
+include::rule-details/aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc[]
 include::rule-details/aws-saml-activity.asciidoc[]
 include::rule-details/aws-sts-getsessiontoken-abuse.asciidoc[]
 include::rule-details/aws-security-group-configuration-change-detection.asciidoc[]
@@ -110,6 +111,7 @@ include::rule-details/attempt-to-modify-an-okta-policy.asciidoc[]
 include::rule-details/attempt-to-modify-an-okta-policy-rule.asciidoc[]
 include::rule-details/attempt-to-mount-smb-share-via-command-line.asciidoc[]
 include::rule-details/attempt-to-reset-mfa-factors-for-an-okta-user-account.asciidoc[]
+include::rule-details/attempt-to-retrieve-user-data-from-aws-ec2-instance.asciidoc[]
 include::rule-details/attempt-to-revoke-okta-api-token.asciidoc[]
 include::rule-details/attempt-to-unload-elastic-endpoint-security-kernel-extension.asciidoc[]
 include::rule-details/attempted-bypass-of-okta-mfa.asciidoc[]
@@ -368,6 +370,7 @@ include::rule-details/incoming-execution-via-powershell-remoting.asciidoc[]
 include::rule-details/incoming-execution-via-winrm-remote-shell.asciidoc[]
 include::rule-details/indirect-command-execution-via-forfiles-pcalua.asciidoc[]
 include::rule-details/ingress-transfer-via-windows-bits.asciidoc[]
+include::rule-details/insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc[]
 include::rule-details/installutil-activity.asciidoc[]
 include::rule-details/installutil-process-making-network-connections.asciidoc[]
 include::rule-details/installation-of-custom-shim-databases.asciidoc[]
@@ -799,6 +802,7 @@ include::rule-details/ssh-authorized-keys-file-modification.asciidoc[]
 include::rule-details/ssh-authorized-keys-file-modified-inside-a-container.asciidoc[]
 include::rule-details/ssh-connection-established-inside-a-running-container.asciidoc[]
 include::rule-details/ssh-process-launched-from-inside-a-container.asciidoc[]
+include::rule-details/ssm-session-started-to-ec2-instance.asciidoc[]
 include::rule-details/suid-sguid-enumeration-detected.asciidoc[]
 include::rule-details/sunburst-command-and-control-activity.asciidoc[]
 include::rule-details/scheduled-task-created-by-a-windows-script.asciidoc[]
@@ -965,6 +969,7 @@ include::rule-details/system-service-discovery-through-built-in-windows-utilitie
 include::rule-details/system-shells-via-services.asciidoc[]
 include::rule-details/system-time-discovery.asciidoc[]
 include::rule-details/systemkey-access-via-command-line.asciidoc[]
+include::rule-details/systemd-service-started-by-unusual-parent-process.asciidoc[]
 include::rule-details/tcc-bypass-via-mounted-apfs-snapshot-access.asciidoc[]
 include::rule-details/tainted-kernel-module-load.asciidoc[]
 include::rule-details/tainted-out-of-tree-kernel-module-load.asciidoc[]
diff --git a/docs/detections/prebuilt-rules/rule-details/account-password-reset-remotely.asciidoc b/docs/detections/prebuilt-rules/rule-details/account-password-reset-remotely.asciidoc
index dff16ebc71..88a79e96b4 100644
--- a/docs/detections/prebuilt-rules/rule-details/account-password-reset-remotely.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/account-password-reset-remotely.asciidoc
@@ -36,7 +36,7 @@ Identifies an attempt to reset a potentially privileged account password remotel
 * Tactic: Persistence
 * Tactic: Impact
 
-*Version*: 114
+*Version*: 115
 
 *Rule authors*: 
 
@@ -49,7 +49,6 @@ Identifies an attempt to reset a potentially privileged account password remotel
 
 
 
-
 *Performance*
 
 This rule may cause medium to high performance impact due to logic scoping all remote Windows logon activity.
diff --git a/docs/detections/prebuilt-rules/rule-details/adding-hidden-file-attribute-via-attrib.asciidoc b/docs/detections/prebuilt-rules/rule-details/adding-hidden-file-attribute-via-attrib.asciidoc
index ef7eb94205..22bfeea743 100644
--- a/docs/detections/prebuilt-rules/rule-details/adding-hidden-file-attribute-via-attrib.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/adding-hidden-file-attribute-via-attrib.asciidoc
@@ -36,7 +36,7 @@ Adversaries can add the 'hidden' attribute to files to hide them from the user i
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -130,14 +130,6 @@ process where host.os.type == "windows" and event.type == "start" and
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Hide Artifacts
-** ID: T1564
-** Reference URL: https://attack.mitre.org/techniques/T1564/
-* Sub-technique:
-** Name: Hidden Files and Directories
-** ID: T1564.001
-** Reference URL: https://attack.mitre.org/techniques/T1564/001/
-* Technique:
 ** Name: File and Directory Permissions Modification
 ** ID: T1222
 ** Reference URL: https://attack.mitre.org/techniques/T1222/
@@ -145,6 +137,14 @@ process where host.os.type == "windows" and event.type == "start" and
 ** Name: Windows File and Directory Permissions Modification
 ** ID: T1222.001
 ** Reference URL: https://attack.mitre.org/techniques/T1222/001/
+* Technique:
+** Name: Hide Artifacts
+** ID: T1564
+** Reference URL: https://attack.mitre.org/techniques/T1564/
+* Sub-technique:
+** Name: Hidden Files and Directories
+** ID: T1564.001
+** Reference URL: https://attack.mitre.org/techniques/T1564/001/
 * Tactic:
 ** Name: Persistence
 ** ID: TA0003
diff --git a/docs/detections/prebuilt-rules/rule-details/adfind-command-activity.asciidoc b/docs/detections/prebuilt-rules/rule-details/adfind-command-activity.asciidoc
index d115b66d5e..f802ec5c4d 100644
--- a/docs/detections/prebuilt-rules/rule-details/adfind-command-activity.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/adfind-command-activity.asciidoc
@@ -42,7 +42,7 @@ This rule detects the Active Directory query tool, AdFind.exe. AdFind has legiti
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -140,6 +140,10 @@ process where host.os.type == "windows" and event.type == "start" and
 ** ID: TA0007
 ** Reference URL: https://attack.mitre.org/tactics/TA0007/
 * Technique:
+** Name: System Network Configuration Discovery
+** ID: T1016
+** Reference URL: https://attack.mitre.org/techniques/T1016/
+* Technique:
 ** Name: Remote System Discovery
 ** ID: T1018
 ** Reference URL: https://attack.mitre.org/techniques/T1018/
@@ -163,7 +167,3 @@ process where host.os.type == "windows" and event.type == "start" and
 ** Name: Domain Trust Discovery
 ** ID: T1482
 ** Reference URL: https://attack.mitre.org/techniques/T1482/
-* Technique:
-** Name: System Network Configuration Discovery
-** ID: T1016
-** Reference URL: https://attack.mitre.org/techniques/T1016/
diff --git a/docs/detections/prebuilt-rules/rule-details/adobe-hijack-persistence.asciidoc b/docs/detections/prebuilt-rules/rule-details/adobe-hijack-persistence.asciidoc
index b84db7c4b0..57c6f9c111 100644
--- a/docs/detections/prebuilt-rules/rule-details/adobe-hijack-persistence.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/adobe-hijack-persistence.asciidoc
@@ -11,6 +11,7 @@ Detects writing executable files that will be automatically launched by Adobe on
 * logs-endpoint.events.file-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: low
 
@@ -36,8 +37,9 @@ Detects writing executable files that will be automatically launched by Adobe on
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 111
+*Version*: 213
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/attempt-to-clear-kernel-ring-buffer.asciidoc b/docs/detections/prebuilt-rules/rule-details/attempt-to-clear-kernel-ring-buffer.asciidoc
index a14b6de570..4b7c02f5e4 100644
--- a/docs/detections/prebuilt-rules/rule-details/attempt-to-clear-kernel-ring-buffer.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/attempt-to-clear-kernel-ring-buffer.asciidoc
@@ -34,7 +34,7 @@ Monitors for the deletion of the kernel ring buffer events through dmesg. Attack
 * Data Source: Elastic Endgame
 * Data Source: Auditd Manager
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -97,14 +97,6 @@ process where host.os.type == "linux" and event.type == "start" and event.action
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Impair Defenses
-** ID: T1562
-** Reference URL: https://attack.mitre.org/techniques/T1562/
-* Sub-technique:
-** Name: Disable or Modify Tools
-** ID: T1562.001
-** Reference URL: https://attack.mitre.org/techniques/T1562/001/
-* Technique:
 ** Name: Indicator Removal
 ** ID: T1070
 ** Reference URL: https://attack.mitre.org/techniques/T1070/
@@ -112,3 +104,11 @@ process where host.os.type == "linux" and event.type == "start" and event.action
 ** Name: Clear Linux or Mac System Logs
 ** ID: T1070.002
 ** Reference URL: https://attack.mitre.org/techniques/T1070/002/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Tools
+** ID: T1562.001
+** Reference URL: https://attack.mitre.org/techniques/T1562/001/
diff --git a/docs/detections/prebuilt-rules/rule-details/attempt-to-retrieve-user-data-from-aws-ec2-instance.asciidoc b/docs/detections/prebuilt-rules/rule-details/attempt-to-retrieve-user-data-from-aws-ec2-instance.asciidoc
new file mode 100644
index 0000000000..70180191b9
--- /dev/null
+++ b/docs/detections/prebuilt-rules/rule-details/attempt-to-retrieve-user-data-from-aws-ec2-instance.asciidoc
@@ -0,0 +1,67 @@
+[[attempt-to-retrieve-user-data-from-aws-ec2-instance]]
+=== Attempt to Retrieve User Data from AWS EC2 Instance
+
+Identifies discovery request `DescribeInstanceAttribute` with the attribute userData and instanceId in AWS CloudTrail logs. This may indicate an attempt to retrieve user data from an EC2 instance. Adversaries may use this information to gather sensitive data from the instance or to identify potential vulnerabilities. This is a building block rule that does not generate an alert on its own, but serves as a signal for anomalous activity.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* filebeat-*
+* logs.aws.cloudtrail-*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 60m
+
+*Searches indices from*: now-119m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/AWSEC2/latest/APIReference/API_DescribeInstanceAttribute.html
+* https://hackingthe.cloud/aws/exploitation/local_ec2_priv_esc_through_user_data
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: Amazon EC2
+* Use Case: Log Auditing
+* Tactic: Discovery
+* Rule Type: BBR
+
+*Version*: 1
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset:aws.cloudtrail
+    and event.action:DescribeInstanceAttribute
+    and aws.cloudtrail.request_parameters:(*attribute=userData* and *instanceId*)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Discovery
+** ID: TA0007
+** Reference URL: https://attack.mitre.org/tactics/TA0007/
+* Technique:
+** Name: Cloud Infrastructure Discovery
+** ID: T1580
+** Reference URL: https://attack.mitre.org/techniques/T1580/
diff --git a/docs/detections/prebuilt-rules/rule-details/aws-ec2-admin-credential-fetch-via-assumed-role.asciidoc b/docs/detections/prebuilt-rules/rule-details/aws-ec2-admin-credential-fetch-via-assumed-role.asciidoc
index 7babe60235..7e97da6021 100644
--- a/docs/detections/prebuilt-rules/rule-details/aws-ec2-admin-credential-fetch-via-assumed-role.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/aws-ec2-admin-credential-fetch-via-assumed-role.asciidoc
@@ -34,7 +34,7 @@ Identifies the first occurrence of a user identity in AWS using `GetPassword` fo
 * Resources: Investigation Guide
 * Tactic: Credential Access
 
-*Version*: 2
+*Version*: 3
 
 *Rule authors*: 
 
@@ -47,7 +47,6 @@ Identifies the first occurrence of a user identity in AWS using `GetPassword` fo
 
 
 
-
 *Triage and Analysis*
 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/aws-iam-login-profile-added-to-user.asciidoc b/docs/detections/prebuilt-rules/rule-details/aws-iam-login-profile-added-to-user.asciidoc
index b6a7f84d3b..8bcde60190 100644
--- a/docs/detections/prebuilt-rules/rule-details/aws-iam-login-profile-added-to-user.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/aws-iam-login-profile-added-to-user.asciidoc
@@ -32,7 +32,7 @@ Identifies when an AWS IAM login profile is added to a user. Adversaries may add
 * Tactic: Persistence
 * Rule Type: BBR
 
-*Version*: 1
+*Version*: 2
 
 *Rule authors*: 
 
@@ -58,14 +58,6 @@ event.dataset: aws.cloudtrail and event.provider: "iam.amazonaws.com"
 ** ID: TA0003
 ** Reference URL: https://attack.mitre.org/tactics/TA0003/
 * Technique:
-** Name: Account Manipulation
-** ID: T1098
-** Reference URL: https://attack.mitre.org/techniques/T1098/
-* Sub-technique:
-** Name: Additional Cloud Roles
-** ID: T1098.003
-** Reference URL: https://attack.mitre.org/techniques/T1098/003/
-* Technique:
 ** Name: Valid Accounts
 ** ID: T1078
 ** Reference URL: https://attack.mitre.org/techniques/T1078/
@@ -73,3 +65,11 @@ event.dataset: aws.cloudtrail and event.provider: "iam.amazonaws.com"
 ** Name: Cloud Accounts
 ** ID: T1078.004
 ** Reference URL: https://attack.mitre.org/techniques/T1078/004/
+* Technique:
+** Name: Account Manipulation
+** ID: T1098
+** Reference URL: https://attack.mitre.org/techniques/T1098/
+* Sub-technique:
+** Name: Additional Cloud Roles
+** ID: T1098.003
+** Reference URL: https://attack.mitre.org/techniques/T1098/003/
diff --git a/docs/detections/prebuilt-rules/rule-details/aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc b/docs/detections/prebuilt-rules/rule-details/aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc
new file mode 100644
index 0000000000..47fc6aab67
--- /dev/null
+++ b/docs/detections/prebuilt-rules/rule-details/aws-s3-bucket-expiration-lifecycle-configuration-added.asciidoc
@@ -0,0 +1,128 @@
+[[aws-s3-bucket-expiration-lifecycle-configuration-added]]
+=== AWS S3 Bucket Expiration Lifecycle Configuration Added
+
+Identifies an expiration lifecycle configuration added to an S3 bucket. Lifecycle configurations can be used to manage objects in a bucket, including setting expiration policies. This rule detects when a lifecycle configuration is added to an S3 bucket, which could indicate that objects in the bucket will be automatically deleted after a specified period of time. This could be used to evade detection by deleting objects that contain evidence of malicious activity.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail*
+
+*Severity*: low
+
+*Risk score*: 21
+
+*Runs every*: 10m
+
+*Searches indices from*: now-60m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/AmazonS3/latest/userguide/lifecycle-expire-general-considerations.html
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: Amazon S3
+* Use Case: Asset Visibility
+* Tactic: Defense Evasion
+
+*Version*: 1
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+
+*Triage and Analysis*
+
+
+
+*Investigating AWS S3 Bucket Expiration Lifecycle Configuration Added*
+
+
+This rule detects when an expiration lifecycle configuration is added to an S3 bucket in AWS. Such configurations can automate the deletion of objects within a bucket after a specified period, potentially obfuscating evidence of unauthorized access or malicious activity by automatically removing logs or other data.
+
+
+*Detailed Investigation Steps*
+
+
+- **Review the Affected S3 Bucket**: Check the bucket details (`bucketName`) where the lifecycle configuration has been added.
+    - Determine the contents and importance of the data stored in this bucket to assess the impact of the lifecycle policy.
+- **Analyze the Lifecycle Configuration**:
+  - **Expiration Policy**: Note the `Days` parameter under `Expiration` in the lifecycle rule. This indicates how long after creation data will remain in the bucket before being automatically deleted.
+  - **Rule ID and Status**: Review the `ID` and `Status` of the lifecycle rule to understand its operational scope and activation status.
+- **User Identity and Activity**:
+  - **User Details**: Investigate the user (`user_identity.arn`) who made the change. Determine whether this user's role typically involves managing S3 bucket configurations.
+  - **Authentication Details**: Examine the authentication method and whether the access key used (`access_key_id`) is routinely used for such configurations or if it has deviated from normal usage patterns.
+- **Source IP and User Agent**:
+  - **Source IP Address**: The IP address (`source.ip`) from which the request was made can provide clues about the geographical location of the requester. Determine if this location aligns with the user’s known locations.
+  - **User Agent**: Analyze the user agent string to understand the type of client or service that made the request, which can help identify scripted automation versus manual changes.
+
+
+*Possible Indicators of Compromise or Misuse*
+
+
+- **Frequent Changes**: Look for frequent modifications to lifecycle policies in the same or multiple buckets, which can indicate attempts to manipulate data retention dynamically.
+- **Unusual User Activity**: Activities that do not correlate with the user's typical behavior patterns, such as making changes during odd hours or from unusual locations, should be flagged for further investigation.
+
+
+*False Positive Analysis*
+
+
+- Verify the operational requirements that might necessitate such lifecycle policies, especially in environments where data retention policies are strictly governed for compliance and cost-saving reasons.
+
+
+*Response and Remediation*
+
+
+- **Immediate Review**: If the change was unauthorized, consider reverting the lifecycle configuration change immediately to prevent potential data loss.
+- **Enhance Monitoring**: Implement monitoring to alert on changes to lifecycle configurations across your S3 environments.
+- **User Education**: Ensure that users with access to critical resources like S3 buckets are aware of the best practices and company policies regarding data retention and security.
+
+
+*Additional Information*
+
+
+For further guidance on managing S3 lifecycle policies and ensuring compliance with organizational data retention and security policies, refer to the AWS official documentation on https://docs.aws.amazon.com/AmazonS3/latest/userguide/lifecycle-expire-general-considerations.html[S3 Lifecycle Configuration].
+
+
+==== Setup
+
+
+This rule requires S3 data events to be logged to CloudTrail. CloudTrail trails can be configured to log S3 data events in the AWS Management Console or using the AWS CLI.
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset: "aws.cloudtrail" and event.provider: "s3.amazonaws.com" and
+    event.action: PutBucketLifecycle and event.outcome: success and
+    aws.cloudtrail.request_parameters: (*LifecycleConfiguration* and *Expiration=*)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Indicator Removal
+** ID: T1070
+** Reference URL: https://attack.mitre.org/techniques/T1070/
diff --git a/docs/detections/prebuilt-rules/rule-details/chkconfig-service-add.asciidoc b/docs/detections/prebuilt-rules/rule-details/chkconfig-service-add.asciidoc
index d0e9bf9a5f..0bde880a91 100644
--- a/docs/detections/prebuilt-rules/rule-details/chkconfig-service-add.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/chkconfig-service-add.asciidoc
@@ -34,7 +34,7 @@ Detects the use of the chkconfig binary to manually add a service for management
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -73,7 +73,7 @@ This rule monitors the usage of the `chkconfig` binary to manually add a service
 - Search for the `rc.d` or `init.d` service files that were created or modified, and analyze their contents.
 - Investigate whether any other files in any of the available `rc.d` or `init.d` directories have been altered through OSQuery.
   - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (path LIKE '/etc/init.d/%' OR path LIKE '/etc/rc%.d/%')"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (path LIKE '/etc/init.d/%' OR path LIKE '/etc/rc%.d/%')\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE (path LIKE '/etc/init.d/%' OR path LIKE\n'/etc/rc%.d/%')\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate syslog through the `sudo cat /var/log/syslog | grep 'LSB'` command to find traces of the LSB header of the script (if present). If syslog is being ingested into Elasticsearch, the same can be accomplished through Kibana.
diff --git a/docs/detections/prebuilt-rules/rule-details/code-signing-policy-modification-through-built-in-tools.asciidoc b/docs/detections/prebuilt-rules/rule-details/code-signing-policy-modification-through-built-in-tools.asciidoc
index f6f1772ef3..74e56e6832 100644
--- a/docs/detections/prebuilt-rules/rule-details/code-signing-policy-modification-through-built-in-tools.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/code-signing-policy-modification-through-built-in-tools.asciidoc
@@ -35,7 +35,7 @@ Identifies attempts to disable/modify the code signing policy through system nat
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 7
+*Version*: 8
 
 *Rule authors*: 
 
@@ -72,8 +72,8 @@ This rule identifies commands that can disable the Driver Signature Enforcement
 - Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
 - Investigate other alerts associated with the user/host during the past 48 hours.
 - Use Osquery and endpoint driver events (`event.category = "driver"`) to investigate if suspicious drivers were loaded into the system after the command was executed.
-  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
-  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
 - Identify the driver's `Device Name` and `Service Name`.
 - Check for alerts from the rules specified in the `Related Rules` section.
 
diff --git a/docs/detections/prebuilt-rules/rule-details/code-signing-policy-modification-through-registry.asciidoc b/docs/detections/prebuilt-rules/rule-details/code-signing-policy-modification-through-registry.asciidoc
index d78859bdb9..e7b7e87c10 100644
--- a/docs/detections/prebuilt-rules/rule-details/code-signing-policy-modification-through-registry.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/code-signing-policy-modification-through-registry.asciidoc
@@ -35,7 +35,7 @@ Identifies attempts to disable the code signing policy through the registry. Cod
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 9
+*Version*: 10
 
 *Rule authors*: 
 
@@ -72,8 +72,8 @@ This rule identifies registry modifications that can disable DSE.
 - Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence, whether they are located in expected locations, and if they are signed with valid digital signatures.
 - Investigate other alerts associated with the user/host during the past 48 hours.
 - Use Osquery and endpoint driver events (`event.category = "driver"`) to investigate if suspicious drivers were loaded into the system after the registry was modified.
-  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
-  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
 - Identify the driver's `Device Name` and `Service Name`.
 - Check for alerts from the rules specified in the `Related Rules` section.
 
@@ -133,6 +133,10 @@ registry where host.os.type == "windows" and event.type : ("creation", "change")
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
 ** Name: Subvert Trust Controls
 ** ID: T1553
 ** Reference URL: https://attack.mitre.org/techniques/T1553/
@@ -140,7 +144,3 @@ registry where host.os.type == "windows" and event.type : ("creation", "change")
 ** Name: Code Signing Policy Modification
 ** ID: T1553.006
 ** Reference URL: https://attack.mitre.org/techniques/T1553/006/
-* Technique:
-** Name: Modify Registry
-** ID: T1112
-** Reference URL: https://attack.mitre.org/techniques/T1112/
diff --git a/docs/detections/prebuilt-rules/rule-details/creation-or-modification-of-domain-backup-dpapi-private-key.asciidoc b/docs/detections/prebuilt-rules/rule-details/creation-or-modification-of-domain-backup-dpapi-private-key.asciidoc
index 737b8fa047..6c78911f4f 100644
--- a/docs/detections/prebuilt-rules/rule-details/creation-or-modification-of-domain-backup-dpapi-private-key.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/creation-or-modification-of-domain-backup-dpapi-private-key.asciidoc
@@ -11,6 +11,7 @@ Identifies the creation or modification of Domain Backup private keys. Adversari
 * logs-endpoint.events.file-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: high
 
@@ -36,8 +37,9 @@ Identifies the creation or modification of Domain Backup private keys. Adversari
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 108
+*Version*: 210
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/cron-job-created-or-changed-by-previously-unknown-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/cron-job-created-or-changed-by-previously-unknown-process.asciidoc
index eb5cba29ad..7ce6439bcc 100644
--- a/docs/detections/prebuilt-rules/rule-details/cron-job-created-or-changed-by-previously-unknown-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/cron-job-created-or-changed-by-previously-unknown-process.asciidoc
@@ -35,7 +35,7 @@ Linux cron jobs are scheduled tasks that can be leveraged by malicious actors fo
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 9
+*Version*: 10
 
 *Rule authors*: 
 
@@ -70,9 +70,9 @@ This rule monitors the creation of previously unknown cron jobs by monitoring fo
 
 - Investigate the cron job file that was created or modified.
 - Investigate whether any other files in any of the available cron job directories have been altered through OSQuery.
-  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (\n  path LIKE '/etc/cron.allow.d/%' OR\n  path LIKE '/etc/cron.d/%' OR\n  path LIKE '/etc/cron.hourly/%' OR\n  path LIKE '/etc/cron.daily/%' OR\n  path LIKE '/etc/cron.weekly/%' OR\n  path LIKE '/etc/cron.monthly/%'\n)\n"}}
-  - !{osquery{"label":"Osquery - Retrieve rc-local.service File Information","query":"SELECT * FROM file WHERE (\n  path = '/etc/cron.allow' OR\n  path = '/etc/cron.deny' OR\n  path = '/etc/crontab' OR\n  path = '/usr/sbin/cron' OR\n  path = '/usr/sbin/anacron'\n)\n"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (\n  path LIKE '/etc/cron.allow.d/%' OR\n  path LIKE '/etc/cron.d/%' OR\n  path LIKE '/etc/cron.hourly/%' OR\n  path LIKE '/etc/cron.daily/%' OR\n  path LIKE '/etc/cron.weekly/%' OR\n  path LIKE '/etc/cron.monthly/%'\n)\n"}}
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/etc/cron.allow.d/%' OR path LIKE '/etc/cron.d/%' OR path LIKE\n'/etc/cron.hourly/%' OR path LIKE '/etc/cron.daily/%' OR path LIKE '/etc/cron.weekly/%' OR path LIKE\n'/etc/cron.monthly/%' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve rc-local.service File Information","query":"SELECT * FROM file WHERE ( path = '/etc/cron.allow' OR path = '/etc/cron.deny' OR path = '/etc/crontab' OR path =\n'/usr/sbin/cron' OR path = '/usr/sbin/anacron' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/etc/cron.allow.d/%' OR path LIKE\n'/etc/cron.d/%' OR path LIKE '/etc/cron.hourly/%' OR path LIKE '/etc/cron.daily/%' OR path LIKE '/etc/cron.weekly/%' OR\npath LIKE '/etc/cron.monthly/%' )\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
@@ -172,16 +172,20 @@ For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/
 
 [source, js]
 ----------------------------------
-host.os.type : "linux" and event.action : ("change" or "file_modify_event" or "creation" or "file_create_event") and 
-file.path : (/etc/cron.allow or /etc/cron.deny or /etc/cron.d/* or /etc/cron.hourly/* or /etc/cron.daily/* or 
-/etc/cron.weekly/* or /etc/cron.monthly/* or /etc/crontab or /usr/sbin/cron or /usr/sbin/anacron) 
-and not (
-  (process.name : ("dpkg" or "dockerd" or "rpm" or "snapd" or "yum" or "exe" or "dnf" or "podman" or 
-  "dnf-automatic" or puppet or autossl_check )) or 
-  (file.extension : ("swp" or "swpx")) or 
-  (process.name : "sed" and file.name : sed*) or 
-  (process.name : "perl" and file.name : e2scrub_all.tmp*) or
-  (process.executable : /var/lib/dpkg*)
+host.os.type : "linux" and event.action : (
+  change or file_modify_event or creation or file_create_event or rename or file_rename_event
+) and file.path : (
+  /etc/cron.allow or /etc/cron.deny or /etc/cron.d/* or /etc/cron.hourly/* or /etc/cron.daily/* or /etc/cron.weekly/* or
+  /etc/cron.monthly/* or /etc/crontab or /usr/sbin/cron or /usr/sbin/anacron or /var/spool/cron/crontabs/*
+) and not (
+  (process.name : (
+    dpkg or dockerd or rpm or snapd or yum or exe or dnf or podman or dnf-automatic or puppet or autossl_check)
+  ) or 
+  (file.extension : (swp or swpx)) or 
+  (process.name : sed and file.name : sed*) or 
+  (process.name : perl and file.name : e2scrub_all.tmp*) or
+  (process.executable : /var/lib/dpkg*) or
+  (file.path:/var/spool/cron/crontabs/tmp.*)
 )
 
 ----------------------------------
diff --git a/docs/detections/prebuilt-rules/rule-details/delayed-execution-via-ping.asciidoc b/docs/detections/prebuilt-rules/rule-details/delayed-execution-via-ping.asciidoc
index 1ae574eb6f..54d0a45eec 100644
--- a/docs/detections/prebuilt-rules/rule-details/delayed-execution-via-ping.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/delayed-execution-via-ping.asciidoc
@@ -30,7 +30,7 @@ Identifies the execution of commonly abused Windows utilities via a delayed Ping
 * Tactic: Defense Evasion
 * Data Source: Elastic Defend
 
-*Version*: 2
+*Version*: 3
 
 *Rule authors*: 
 
@@ -91,25 +91,21 @@ sequence by process.parent.entity_id with maxspan=1m
 ** ID: T1059
 ** Reference URL: https://attack.mitre.org/techniques/T1059/
 * Sub-technique:
-** Name: Visual Basic
-** ID: T1059.005
-** Reference URL: https://attack.mitre.org/techniques/T1059/005/
-* Sub-technique:
 ** Name: PowerShell
 ** ID: T1059.001
 ** Reference URL: https://attack.mitre.org/techniques/T1059/001/
+* Sub-technique:
+** Name: Visual Basic
+** ID: T1059.005
+** Reference URL: https://attack.mitre.org/techniques/T1059/005/
 * Tactic:
 ** Name: Defense Evasion
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Virtualization/Sandbox Evasion
-** ID: T1497
-** Reference URL: https://attack.mitre.org/techniques/T1497/
-* Sub-technique:
-** Name: Time Based Evasion
-** ID: T1497.003
-** Reference URL: https://attack.mitre.org/techniques/T1497/003/
+** Name: System Script Proxy Execution
+** ID: T1216
+** Reference URL: https://attack.mitre.org/techniques/T1216/
 * Technique:
 ** Name: System Binary Proxy Execution
 ** ID: T1218
@@ -139,10 +135,14 @@ sequence by process.parent.entity_id with maxspan=1m
 ** ID: T1218.011
 ** Reference URL: https://attack.mitre.org/techniques/T1218/011/
 * Technique:
-** Name: System Script Proxy Execution
-** ID: T1216
-** Reference URL: https://attack.mitre.org/techniques/T1216/
-* Technique:
 ** Name: XSL Script Processing
 ** ID: T1220
 ** Reference URL: https://attack.mitre.org/techniques/T1220/
+* Technique:
+** Name: Virtualization/Sandbox Evasion
+** ID: T1497
+** Reference URL: https://attack.mitre.org/techniques/T1497/
+* Sub-technique:
+** Name: Time Based Evasion
+** ID: T1497.003
+** Reference URL: https://attack.mitre.org/techniques/T1497/003/
diff --git a/docs/detections/prebuilt-rules/rule-details/deleting-backup-catalogs-with-wbadmin.asciidoc b/docs/detections/prebuilt-rules/rule-details/deleting-backup-catalogs-with-wbadmin.asciidoc
index b529b077f0..c0060ad30d 100644
--- a/docs/detections/prebuilt-rules/rule-details/deleting-backup-catalogs-with-wbadmin.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/deleting-backup-catalogs-with-wbadmin.asciidoc
@@ -35,7 +35,7 @@ Identifies use of the wbadmin.exe to delete the backup catalog. Ransomware and o
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -131,10 +131,10 @@ process where host.os.type == "windows" and event.type == "start" and
 ** ID: TA0040
 ** Reference URL: https://attack.mitre.org/tactics/TA0040/
 * Technique:
-** Name: Inhibit System Recovery
-** ID: T1490
-** Reference URL: https://attack.mitre.org/techniques/T1490/
-* Technique:
 ** Name: Data Destruction
 ** ID: T1485
 ** Reference URL: https://attack.mitre.org/techniques/T1485/
+* Technique:
+** Name: Inhibit System Recovery
+** ID: T1490
+** Reference URL: https://attack.mitre.org/techniques/T1490/
diff --git a/docs/detections/prebuilt-rules/rule-details/disabling-user-account-control-via-registry-modification.asciidoc b/docs/detections/prebuilt-rules/rule-details/disabling-user-account-control-via-registry-modification.asciidoc
index d9073a9d1a..cb782c52f0 100644
--- a/docs/detections/prebuilt-rules/rule-details/disabling-user-account-control-via-registry-modification.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/disabling-user-account-control-via-registry-modification.asciidoc
@@ -39,7 +39,7 @@ User Account Control (UAC) can help mitigate the impact of malware on Windows ho
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 110
+*Version*: 111
 
 *Rule authors*: 
 
@@ -161,6 +161,10 @@ registry where host.os.type == "windows" and event.type == "change" and
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
 ** Name: Abuse Elevation Control Mechanism
 ** ID: T1548
 ** Reference URL: https://attack.mitre.org/techniques/T1548/
@@ -176,7 +180,3 @@ registry where host.os.type == "windows" and event.type == "change" and
 ** Name: Disable or Modify Tools
 ** ID: T1562.001
 ** Reference URL: https://attack.mitre.org/techniques/T1562/001/
-* Technique:
-** Name: Modify Registry
-** ID: T1112
-** Reference URL: https://attack.mitre.org/techniques/T1112/
diff --git a/docs/detections/prebuilt-rules/rule-details/dns-over-https-enabled-via-registry.asciidoc b/docs/detections/prebuilt-rules/rule-details/dns-over-https-enabled-via-registry.asciidoc
index 6bce6db15d..e165617b91 100644
--- a/docs/detections/prebuilt-rules/rule-details/dns-over-https-enabled-via-registry.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/dns-over-https-enabled-via-registry.asciidoc
@@ -37,7 +37,7 @@ Identifies when a user enables DNS-over-HTTPS. This can be used to hide internet
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 109
+*Version*: 110
 
 *Rule authors*: 
 
@@ -82,10 +82,10 @@ registry where host.os.type == "windows" and event.type in ("creation", "change"
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Impair Defenses
-** ID: T1562
-** Reference URL: https://attack.mitre.org/techniques/T1562/
-* Technique:
 ** Name: Modify Registry
 ** ID: T1112
 ** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
diff --git a/docs/detections/prebuilt-rules/rule-details/dynamic-linker-copy.asciidoc b/docs/detections/prebuilt-rules/rule-details/dynamic-linker-copy.asciidoc
index bd2446f141..d02b906339 100644
--- a/docs/detections/prebuilt-rules/rule-details/dynamic-linker-copy.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/dynamic-linker-copy.asciidoc
@@ -32,7 +32,7 @@ Detects the copying of the Linux dynamic loader binary and subsequent file creat
 * Threat: Orbit
 * Data Source: Elastic Defend
 
-*Version*: 108
+*Version*: 109
 
 *Rule authors*: 
 
@@ -67,8 +67,8 @@ The detection rule 'Dynamic Linker Copy' is designed to identify such abuse by m
 
 
 - Investigate the dynamic linker that was copied or altered.
-  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (\n  path = '/etc/ld.so.preload' OR\n  path = '/lib64/ld-linux-x86-64.so.2' OR\n  path = '/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' OR\n  path = '/usr/lib64/ld-linux-x86-64.so.2' OR\n  path = '/usr/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2'\n)\n"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (\n  path = '/etc/ld.so.preload' OR\n  path = '/lib64/ld-linux-x86-64.so.2' OR\n  path = '/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' OR\n  path = '/usr/lib64/ld-linux-x86-64.so.2' OR\n  path = '/usr/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2'\n)\n"}}
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path = '/etc/ld.so.preload' OR path = '/lib64/ld-linux-x86-64.so.2' OR path =\n'/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' OR path = '/usr/lib64/ld-linux-x86-64.so.2' OR path =\n'/usr/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path = '/etc/ld.so.preload' OR path =\n'/lib64/ld-linux-x86-64.so.2' OR path = '/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' OR path =\n'/usr/lib64/ld-linux-x86-64.so.2' OR path = '/usr/lib/x86_64-linux-gnu/ld-linux-x86-64.so.2' )\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
diff --git a/docs/detections/prebuilt-rules/rule-details/ec2-ami-shared-with-another-account.asciidoc b/docs/detections/prebuilt-rules/rule-details/ec2-ami-shared-with-another-account.asciidoc
index 865413477f..c06d9ed6dc 100644
--- a/docs/detections/prebuilt-rules/rule-details/ec2-ami-shared-with-another-account.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/ec2-ami-shared-with-another-account.asciidoc
@@ -35,7 +35,7 @@ Identifies an AWS Amazon Machine Image (AMI) being shared with another AWS accou
 * Use Case: Threat Detection
 * Tactic: Exfiltration
 
-*Version*: 1
+*Version*: 2
 
 *Rule authors*: 
 
@@ -48,7 +48,6 @@ Identifies an AWS Amazon Machine Image (AMI) being shared with another AWS accou
 
 
 
-
 *Triage and Analysis*
 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/encoded-executable-stored-in-the-registry.asciidoc b/docs/detections/prebuilt-rules/rule-details/encoded-executable-stored-in-the-registry.asciidoc
index 1265231cb6..0f98509bb9 100644
--- a/docs/detections/prebuilt-rules/rule-details/encoded-executable-stored-in-the-registry.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/encoded-executable-stored-in-the-registry.asciidoc
@@ -10,6 +10,7 @@ Identifies registry write modifications to hide an encoded portable executable.
 * logs-endpoint.events.registry-*
 * endgame-*
 * logs-windows.sysmon_operational-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -32,8 +33,9 @@ Identifies registry write modifications to hide an encoded portable executable.
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 107
+*Version*: 209
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/encrypting-files-with-winrar-or-7z.asciidoc b/docs/detections/prebuilt-rules/rule-details/encrypting-files-with-winrar-or-7z.asciidoc
index 954b5a1420..3f4eb3f980 100644
--- a/docs/detections/prebuilt-rules/rule-details/encrypting-files-with-winrar-or-7z.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/encrypting-files-with-winrar-or-7z.asciidoc
@@ -36,7 +36,7 @@ Identifies use of WinRar or 7z to create an encrypted files. Adversaries will of
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -140,6 +140,10 @@ process where host.os.type == "windows" and event.type == "start" and
 ** ID: TA0009
 ** Reference URL: https://attack.mitre.org/tactics/TA0009/
 * Technique:
+** Name: Data from Local System
+** ID: T1005
+** Reference URL: https://attack.mitre.org/techniques/T1005/
+* Technique:
 ** Name: Archive Collected Data
 ** ID: T1560
 ** Reference URL: https://attack.mitre.org/techniques/T1560/
@@ -147,7 +151,3 @@ process where host.os.type == "windows" and event.type == "start" and
 ** Name: Archive via Utility
 ** ID: T1560.001
 ** Reference URL: https://attack.mitre.org/techniques/T1560/001/
-* Technique:
-** Name: Data from Local System
-** ID: T1005
-** Reference URL: https://attack.mitre.org/techniques/T1005/
diff --git a/docs/detections/prebuilt-rules/rule-details/enumerating-domain-trusts-via-dsquery-exe.asciidoc b/docs/detections/prebuilt-rules/rule-details/enumerating-domain-trusts-via-dsquery-exe.asciidoc
index 91daf0bbda..84657dcedf 100644
--- a/docs/detections/prebuilt-rules/rule-details/enumerating-domain-trusts-via-dsquery-exe.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/enumerating-domain-trusts-via-dsquery-exe.asciidoc
@@ -38,7 +38,7 @@ Identifies the use of dsquery.exe for domain trust discovery purposes. Adversari
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 7
+*Version*: 8
 
 *Rule authors*: 
 
@@ -112,10 +112,10 @@ process where host.os.type == "windows" and event.type == "start" and
 ** ID: TA0007
 ** Reference URL: https://attack.mitre.org/tactics/TA0007/
 * Technique:
-** Name: Domain Trust Discovery
-** ID: T1482
-** Reference URL: https://attack.mitre.org/techniques/T1482/
-* Technique:
 ** Name: Remote System Discovery
 ** ID: T1018
 ** Reference URL: https://attack.mitre.org/techniques/T1018/
+* Technique:
+** Name: Domain Trust Discovery
+** ID: T1482
+** Reference URL: https://attack.mitre.org/techniques/T1482/
diff --git a/docs/detections/prebuilt-rules/rule-details/enumerating-domain-trusts-via-nltest-exe.asciidoc b/docs/detections/prebuilt-rules/rule-details/enumerating-domain-trusts-via-nltest-exe.asciidoc
index a4ef8f7e03..5298a908b7 100644
--- a/docs/detections/prebuilt-rules/rule-details/enumerating-domain-trusts-via-nltest-exe.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/enumerating-domain-trusts-via-nltest-exe.asciidoc
@@ -38,7 +38,7 @@ Identifies the use of nltest.exe for domain trust discovery purposes. Adversarie
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 110
+*Version*: 111
 
 *Rule authors*: 
 
@@ -117,10 +117,10 @@ not user.id in ("S-1-5-18", "S-1-5-19", "S-1-5-20")
 ** ID: TA0007
 ** Reference URL: https://attack.mitre.org/tactics/TA0007/
 * Technique:
-** Name: Domain Trust Discovery
-** ID: T1482
-** Reference URL: https://attack.mitre.org/techniques/T1482/
-* Technique:
 ** Name: Remote System Discovery
 ** ID: T1018
 ** Reference URL: https://attack.mitre.org/techniques/T1018/
+* Technique:
+** Name: Domain Trust Discovery
+** ID: T1482
+** Reference URL: https://attack.mitre.org/techniques/T1482/
diff --git a/docs/detections/prebuilt-rules/rule-details/enumeration-command-spawned-via-wmiprvse.asciidoc b/docs/detections/prebuilt-rules/rule-details/enumeration-command-spawned-via-wmiprvse.asciidoc
index daa58230f0..eb8dbc0abe 100644
--- a/docs/detections/prebuilt-rules/rule-details/enumeration-command-spawned-via-wmiprvse.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/enumeration-command-spawned-via-wmiprvse.asciidoc
@@ -34,7 +34,7 @@ Identifies native Windows host and network enumeration commands spawned by the W
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -112,18 +112,6 @@ process where host.os.type == "windows" and event.type == "start" and process.co
 ** ID: TA0007
 ** Reference URL: https://attack.mitre.org/tactics/TA0007/
 * Technique:
-** Name: Remote System Discovery
-** ID: T1018
-** Reference URL: https://attack.mitre.org/techniques/T1018/
-* Technique:
-** Name: Account Discovery
-** ID: T1087
-** Reference URL: https://attack.mitre.org/techniques/T1087/
-* Technique:
-** Name: Software Discovery
-** ID: T1518
-** Reference URL: https://attack.mitre.org/techniques/T1518/
-* Technique:
 ** Name: System Network Configuration Discovery
 ** ID: T1016
 ** Reference URL: https://attack.mitre.org/techniques/T1016/
@@ -132,6 +120,18 @@ process where host.os.type == "windows" and event.type == "start" and process.co
 ** ID: T1016.001
 ** Reference URL: https://attack.mitre.org/techniques/T1016/001/
 * Technique:
+** Name: Remote System Discovery
+** ID: T1018
+** Reference URL: https://attack.mitre.org/techniques/T1018/
+* Technique:
 ** Name: Process Discovery
 ** ID: T1057
 ** Reference URL: https://attack.mitre.org/techniques/T1057/
+* Technique:
+** Name: Account Discovery
+** ID: T1087
+** Reference URL: https://attack.mitre.org/techniques/T1087/
+* Technique:
+** Name: Software Discovery
+** ID: T1518
+** Reference URL: https://attack.mitre.org/techniques/T1518/
diff --git a/docs/detections/prebuilt-rules/rule-details/executable-masquerading-as-kernel-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/executable-masquerading-as-kernel-process.asciidoc
index bdb258f624..9f64a80878 100644
--- a/docs/detections/prebuilt-rules/rule-details/executable-masquerading-as-kernel-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/executable-masquerading-as-kernel-process.asciidoc
@@ -33,7 +33,7 @@ Monitors for kernel processes with associated process executable fields that are
 * Data Source: Elastic Defend
 * Data Source: Elastic Endgame
 
-*Version*: 2
+*Version*: 3
 
 *Rule authors*: 
 
@@ -97,10 +97,6 @@ process.name : ("kworker*", "kthread*") and process.executable != null
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Hide Artifacts
-** ID: T1564
-** Reference URL: https://attack.mitre.org/techniques/T1564/
-* Technique:
 ** Name: Masquerading
 ** ID: T1036
 ** Reference URL: https://attack.mitre.org/techniques/T1036/
@@ -108,3 +104,7 @@ process.name : ("kworker*", "kthread*") and process.executable != null
 ** Name: Masquerade Task or Service
 ** ID: T1036.004
 ** Reference URL: https://attack.mitre.org/techniques/T1036/004/
+* Technique:
+** Name: Hide Artifacts
+** ID: T1564
+** Reference URL: https://attack.mitre.org/techniques/T1564/
diff --git a/docs/detections/prebuilt-rules/rule-details/exporting-exchange-mailbox-via-powershell.asciidoc b/docs/detections/prebuilt-rules/rule-details/exporting-exchange-mailbox-via-powershell.asciidoc
index c164891164..f88cb2e265 100644
--- a/docs/detections/prebuilt-rules/rule-details/exporting-exchange-mailbox-via-powershell.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/exporting-exchange-mailbox-via-powershell.asciidoc
@@ -12,6 +12,7 @@ Identifies the use of the Exchange PowerShell cmdlet, New-MailBoxExportRequest,
 * logs-windows.*
 * endgame-*
 * logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -38,8 +39,9 @@ Identifies the use of the Exchange PowerShell cmdlet, New-MailBoxExportRequest,
 * Resources: Investigation Guide
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
+* Data Source: SentinelOne
 
-*Version*: 111
+*Version*: 213
 
 *Rule authors*: 
 
@@ -123,7 +125,7 @@ For more details on adding a custom ingest pipeline refer - https://www.elastic.
 [source, js]
 ----------------------------------
 process where host.os.type == "windows" and event.type == "start" and
-  process.name: ("powershell.exe", "pwsh.exe", "powershell_ise.exe") and 
+  process.name: ("powershell.exe", "pwsh.exe", "powershell_ise.exe") and
   process.command_line : ("*MailboxExportRequest*", "*-Mailbox*-ContentFilter*")
 
 ----------------------------------
diff --git a/docs/detections/prebuilt-rules/rule-details/file-compressed-or-archived-into-common-format.asciidoc b/docs/detections/prebuilt-rules/rule-details/file-compressed-or-archived-into-common-format.asciidoc
index 8c5ed1501e..ad1a3c6642 100644
--- a/docs/detections/prebuilt-rules/rule-details/file-compressed-or-archived-into-common-format.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/file-compressed-or-archived-into-common-format.asciidoc
@@ -32,7 +32,7 @@ Detects files being compressed or archived into common formats. This is a common
 * Tactic: Collection
 * Rule Type: BBR
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -131,14 +131,6 @@ file where host.os.type == "windows" and event.type in ("creation", "change") an
 ** ID: TA0009
 ** Reference URL: https://attack.mitre.org/tactics/TA0009/
 * Technique:
-** Name: Archive Collected Data
-** ID: T1560
-** Reference URL: https://attack.mitre.org/techniques/T1560/
-* Sub-technique:
-** Name: Archive via Utility
-** ID: T1560.001
-** Reference URL: https://attack.mitre.org/techniques/T1560/001/
-* Technique:
 ** Name: Data Staged
 ** ID: T1074
 ** Reference URL: https://attack.mitre.org/techniques/T1074/
@@ -146,6 +138,14 @@ file where host.os.type == "windows" and event.type in ("creation", "change") an
 ** Name: Local Data Staging
 ** ID: T1074.001
 ** Reference URL: https://attack.mitre.org/techniques/T1074/001/
+* Technique:
+** Name: Archive Collected Data
+** ID: T1560
+** Reference URL: https://attack.mitre.org/techniques/T1560/
+* Sub-technique:
+** Name: Archive via Utility
+** ID: T1560.001
+** Reference URL: https://attack.mitre.org/techniques/T1560/001/
 * Tactic:
 ** Name: Command and Control
 ** ID: TA0011
diff --git a/docs/detections/prebuilt-rules/rule-details/first-time-seen-aws-secret-value-accessed-in-secrets-manager.asciidoc b/docs/detections/prebuilt-rules/rule-details/first-time-seen-aws-secret-value-accessed-in-secrets-manager.asciidoc
index 4d8bfd92ab..6ebc419031 100644
--- a/docs/detections/prebuilt-rules/rule-details/first-time-seen-aws-secret-value-accessed-in-secrets-manager.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/first-time-seen-aws-secret-value-accessed-in-secrets-manager.asciidoc
@@ -1,7 +1,7 @@
 [[first-time-seen-aws-secret-value-accessed-in-secrets-manager]]
 === First Time Seen AWS Secret Value Accessed in Secrets Manager
 
-An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service may attempt to leverage the compromised service to access secrets in AWS Secrets Manager. This rule looks for the first time a specific user identity has programmatically retrieved a specific secret value from Secrets Manager using the `GetSecretValue` action.  This rule assumes that AWS services such as Lambda functions and EC2 instances are setup with IAM role's assigned that have the necessary permissions to access the secrets in Secrets Manager. An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service would rely on the compromised service's IAM role to access the secrets in Secrets Manager.
+An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service may attempt to leverage the compromised service to access secrets in AWS Secrets Manager. This rule looks for the first time a specific user identity has programmatically retrieved a specific secret value from Secrets Manager using the `GetSecretValue` action. This rule assumes that AWS services such as Lambda functions and EC2 instances are setup with IAM role's assigned that have the necessary permissions to access the secrets in Secrets Manager. An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service would rely on the compromised service's IAM role to access the secrets in Secrets Manager.
 
 *Rule type*: new_terms
 
@@ -34,7 +34,7 @@ An adversary with access to a compromised AWS service such as an EC2 instance, L
 * Tactic: Credential Access
 * Resources: Investigation Guide
 
-*Version*: 310
+*Version*: 311
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/first-time-seen-driver-loaded.asciidoc b/docs/detections/prebuilt-rules/rule-details/first-time-seen-driver-loaded.asciidoc
index a181841fbd..d2dd5ff740 100644
--- a/docs/detections/prebuilt-rules/rule-details/first-time-seen-driver-loaded.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/first-time-seen-driver-loaded.asciidoc
@@ -33,7 +33,7 @@ Identifies the load of a driver with an original file name and signature values
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 7
+*Version*: 8
 
 *Rule authors*: 
 
@@ -79,8 +79,8 @@ This rule identifies the load of a driver with an original file name and signatu
 - Investigate other alerts associated with the user/host during the past 48 hours.
 - Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
 - Use Osquery to investigate the drivers loaded into the system.
-  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
-  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
 - Identify the driver's `Device Name` and `Service Name`.
 - Check for alerts from the rules specified in the `Related Rules` section.
 
diff --git a/docs/detections/prebuilt-rules/rule-details/github-protected-branch-settings-changed.asciidoc b/docs/detections/prebuilt-rules/rule-details/github-protected-branch-settings-changed.asciidoc
index 62934e6b62..918bad38ef 100644
--- a/docs/detections/prebuilt-rules/rule-details/github-protected-branch-settings-changed.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/github-protected-branch-settings-changed.asciidoc
@@ -28,7 +28,7 @@ This rule detects setting modifications for protected branches of a GitHub repos
 * Tactic: Defense Evasion
 * Data Source: Github
 
-*Version*: 2
+*Version*: 3
 
 *Rule authors*: 
 
@@ -43,7 +43,7 @@ This rule detects setting modifications for protected branches of a GitHub repos
 [source, js]
 ----------------------------------
 configuration where event.dataset == "github.audit" 
-  and github.category == "protected_branch" and event.type == "change" 
+  and github.category == "protected_branch" and event.type == "change"
 
 ----------------------------------
 
diff --git a/docs/detections/prebuilt-rules/rule-details/high-mean-of-process-arguments-in-an-rdp-session.asciidoc b/docs/detections/prebuilt-rules/rule-details/high-mean-of-process-arguments-in-an-rdp-session.asciidoc
index fc91a1e8fe..ff3915e4e8 100644
--- a/docs/detections/prebuilt-rules/rule-details/high-mean-of-process-arguments-in-an-rdp-session.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/high-mean-of-process-arguments-in-an-rdp-session.asciidoc
@@ -31,7 +31,7 @@ A machine learning job has detected unusually high number of process arguments i
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,17 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Before enabling the Anomaly Detection jobs, confirm that the Pivot Transform asset is installed and actively gathering data in the destination index `ml-rdp-lmd`.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your transformed RDP process data i.e.`ml-rdp-lmd`.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/high-mean-of-rdp-session-duration.asciidoc b/docs/detections/prebuilt-rules/rule-details/high-mean-of-rdp-session-duration.asciidoc
index 465bb2ecaf..b0c0e846ef 100644
--- a/docs/detections/prebuilt-rules/rule-details/high-mean-of-rdp-session-duration.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/high-mean-of-rdp-session-duration.asciidoc
@@ -31,7 +31,7 @@ A machine learning job has detected unusually high mean of RDP session duration.
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,17 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Before enabling the Anomaly Detection jobs, confirm that the Pivot Transform asset is installed and actively gathering data in the destination index `ml-rdp-lmd`.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your transformed RDP process data i.e.`ml-rdp-lmd`.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/high-variance-in-rdp-session-duration.asciidoc b/docs/detections/prebuilt-rules/rule-details/high-variance-in-rdp-session-duration.asciidoc
index 94d1ce4ded..a61121e9bb 100644
--- a/docs/detections/prebuilt-rules/rule-details/high-variance-in-rdp-session-duration.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/high-variance-in-rdp-session-duration.asciidoc
@@ -31,7 +31,7 @@ A machine learning job has detected unusually high variance of RDP session durat
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,17 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Before enabling the Anomaly Detection jobs, confirm that the Pivot Transform asset is installed and actively gathering data in the destination index `ml-rdp-lmd`.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your transformed RDP process data i.e.`ml-rdp-lmd`.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc b/docs/detections/prebuilt-rules/rule-details/insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc
new file mode 100644
index 0000000000..5cf7a773b6
--- /dev/null
+++ b/docs/detections/prebuilt-rules/rule-details/insecure-aws-ec2-vpc-security-group-ingress-rule-added.asciidoc
@@ -0,0 +1,124 @@
+[[insecure-aws-ec2-vpc-security-group-ingress-rule-added]]
+=== Insecure AWS EC2 VPC Security Group Ingress Rule Added
+
+Identifies when a specified inbound (ingress) rule is added or adjusted for a VPC security group in AWS EC2. This rule detects when a security group rule is added that allows traffic from any IP address or from a specific IP address to common remote access ports, such as 22 (SSH) or 3389 (RDP). Adversaries may add these rules to allow remote access to VPC instances from any location, increasing the attack surface and potentially exposing the instances to unauthorized access.
+
+*Rule type*: query
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 10m
+
+*Searches indices from*: now-60m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/AWSEC2/latest/APIReference/API_AuthorizeSecurityGroupEgress.html
+* https://docs.aws.amazon.com/AWSEC2/latest/APIReference/API_AuthorizeSecurityGroupIngress.html
+* https://www.linkedin.com/pulse/my-backdoors-your-aws-infrastructure-part-3-network-micha%C5%82-brygidyn/
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: AWS EC2
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+
+*Version*: 1
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and Analysis*
+
+
+
+*Investigating Insecure AWS EC2 VPC Security Group Ingress Rule Added*
+
+
+This rule detects the addition of ingress rules to a VPC security group that allow traffic from any IP address (`0.0.0.0/0` or `::/0`) to sensitive ports commonly used for remote access, such as SSH (port 22) and RDP (port 3389). This configuration change can significantly increase the exposure of EC2 instances to potential threats, making it crucial to understand the context and legitimacy of such changes.
+
+
+*Possible Investigation Steps:*
+
+
+- **Identify the Actor**: Review the `aws.cloudtrail.user_identity.arn` and `aws.cloudtrail.user_identity.access_key_id` fields to identify who made the change. Investigate whether this actor has the necessary permissions and typically performs these actions.
+- **Review the Request Details**: Examine the `aws.cloudtrail.request_parameters` to understand exactly what changes were made to the security group. Check for any unusual parameters that could suggest a misconfiguration or malicious intent.
+- **Analyze the Source of the Request**: Look at the `source.ip` and `source.geo` fields to determine the geographical origin of the request. An external or unusual location could indicate compromised credentials.
+- **Contextualize with Timestamp**: Use the `@timestamp` field to check when the change occurred. Modifications outside of typical business hours might warrant additional scrutiny.
+- **Correlate with Other Activities**: Search for related CloudTrail events before and after this change to see if the same actor engaged in other potentially suspicious activities.
+
+
+*False Positive Analysis:*
+
+
+- **Legitimate Administrative Actions**: Verify if the ingress rule change aligns with scheduled updates, maintenance activities, or legitimate administrative tasks documented in change management tickets or systems.
+- **Consistency Check**: Compare the action against historical data of similar actions performed by the user or within the organization. Consistency with past legitimate actions might indicate a false alarm.
+- **Verify through Outcomes**: Check the `aws.cloudtrail.response_elements` and the `event.outcome` to confirm if the change was successful and intended as per policy.
+
+
+*Response and Remediation:*
+
+
+- **Immediate Review and Reversal if Necessary**: If the change was unauthorized, revert the security group rules to their previous state to close any unintended access.
+- **Enhance Monitoring and Alerts**: Adjust monitoring systems to alert on similar security group changes, especially those that open access to well-known ports from any IP address.
+- **Educate and Train**: Provide additional training to users with administrative rights on the importance of security best practices concerning security group management.
+- **Audit Security Groups and Policies**: Conduct a comprehensive audit of all security groups and associated policies to ensure they adhere to the principle of least privilege.
+- **Incident Response**: If there's an indication of malicious intent or a security breach, initiate the incident response protocol to mitigate any damage and prevent future occurrences.
+
+
+*Additional Information:*
+
+
+For further guidance on managing security group rules and securing AWS environments, refer to the https://docs.aws.amazon.com/vpc/latest/userguide/VPC_SecurityGroups.html[Amazon VPC Security Groups documentation] and AWS best practices for security.
+
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset: "aws.cloudtrail"
+    and event.provider: ec2.amazonaws.com
+    and event.action: AuthorizeSecurityGroupIngress
+    and event.outcome: success
+    and aws.cloudtrail.flattened.request_parameters.cidrIp: ("0.0.0.0/0" or "::/0")
+    and aws.cloudtrail.flattened.request_parameters.fromPort: (
+        21 or 22 or 23 or 445 or 3389 or 5985 or 5986)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Defense Evasion
+** ID: TA0005
+** Reference URL: https://attack.mitre.org/tactics/TA0005/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
+* Sub-technique:
+** Name: Disable or Modify Cloud Firewall
+** ID: T1562.007
+** Reference URL: https://attack.mitre.org/techniques/T1562/007/
diff --git a/docs/detections/prebuilt-rules/rule-details/kirbi-file-creation.asciidoc b/docs/detections/prebuilt-rules/rule-details/kirbi-file-creation.asciidoc
index e60ee80ee9..c177ff0fc5 100644
--- a/docs/detections/prebuilt-rules/rule-details/kirbi-file-creation.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/kirbi-file-creation.asciidoc
@@ -9,12 +9,13 @@ Identifies the creation of .kirbi files. The creation of this kind of file is an
 
 * logs-endpoint.events.file-*
 * logs-windows.sysmon_operational-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
 *Risk score*: 47
 
-*Runs every*: 60m
+*Runs every*: 5m
 
 *Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
 
@@ -30,8 +31,9 @@ Identifies the creation of .kirbi files. The creation of this kind of file is an
 * Tactic: Credential Access
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 5
+*Version*: 107
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/local-account-tokenfilter-policy-disabled.asciidoc b/docs/detections/prebuilt-rules/rule-details/local-account-tokenfilter-policy-disabled.asciidoc
index e95c4a0f7c..3eeaf2c5b9 100644
--- a/docs/detections/prebuilt-rules/rule-details/local-account-tokenfilter-policy-disabled.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/local-account-tokenfilter-policy-disabled.asciidoc
@@ -11,6 +11,7 @@ Identifies registry modification to the LocalAccountTokenFilterPolicy policy. If
 * logs-endpoint.events.registry-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -38,8 +39,9 @@ Identifies registry modification to the LocalAccountTokenFilterPolicy policy. If
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 8
+*Version*: 110
 
 *Rule authors*: 
 
@@ -55,7 +57,8 @@ Identifies registry modification to the LocalAccountTokenFilterPolicy policy. If
 ----------------------------------
 registry where host.os.type == "windows" and registry.path : (
   "HKLM\\*\\LocalAccountTokenFilterPolicy",
-  "\\REGISTRY\\MACHINE\\*\\LocalAccountTokenFilterPolicy") and
+  "\\REGISTRY\\MACHINE\\*\\LocalAccountTokenFilterPolicy",
+  "MACHINE\\*\\LocalAccountTokenFilterPolicy") and
   registry.data.strings : ("1", "0x00000001")
 
 ----------------------------------
diff --git a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain.asciidoc b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain.asciidoc
index e0c48c1aca..0854a8b368 100644
--- a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-dns-request-predicted-to-be-a-dga-domain.asciidoc
@@ -36,7 +36,7 @@ A supervised machine learning model has identified a DNS question name that is p
 * Rule Type: Machine Learning
 * Tactic: Command and Control
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -74,37 +74,8 @@ The DGA Detection integration consists of an ML-based framework to detect DGA ac
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Domain Generation Algorithm Detection and select the integration to see more details about it.
-- Under Settings, click Install Domain Generation Algorithm Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-Before you can enable this rule, you'll need to enrich DNS events with predictions from the Supervised DGA Detection model. This is done via the ingest pipeline named `<package_version>-ml_dga_ingest_pipeline` installed with the DGA Detection package.
-- If using an Elastic Beat such as Packetbeat, add the DGA ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `packetbeat.yml`.
-- If adding the DGA ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the DGA ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "ml_is_dga": {
-      "properties": {
-        "malicious_prediction": {
-          "type": "long"
-        },
-        "malicious_probability": {
-          "type": "float"
-        }
-      }
-    }
-  }
-}
-```
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
 
 
 ==== Rule query
diff --git a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-dns-request-with-a-high-dga-probability-score.asciidoc b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-dns-request-with-a-high-dga-probability-score.asciidoc
index e19070ebe9..b4abe66a79 100644
--- a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-dns-request-with-a-high-dga-probability-score.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-dns-request-with-a-high-dga-probability-score.asciidoc
@@ -36,7 +36,7 @@ A supervised machine learning model has identified a DNS question name with a hi
 * Rule Type: Machine Learning
 * Tactic: Command and Control
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -74,37 +74,8 @@ The DGA Detection integration consists of an ML-based framework to detect DGA ac
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Domain Generation Algorithm Detection and select the integration to see more details about it.
-- Under Settings, click Install Domain Generation Algorithm Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-Before you can enable this rule, you'll need to enrich DNS events with predictions from the Supervised DGA Detection model. This is done via the ingest pipeline named `<package_version>-ml_dga_ingest_pipeline` installed with the DGA Detection package.
-- If using an Elastic Beat such as Packetbeat, add the DGA ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `packetbeat.yml`.
-- If adding the DGA ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the DGA ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "ml_is_dga": {
-      "properties": {
-        "malicious_prediction": {
-          "type": "long"
-        },
-        "malicious_probability": {
-          "type": "float"
-        }
-      }
-    }
-  }
-}
-```
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
 
 
 ==== Rule query
diff --git a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity.asciidoc b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity.asciidoc
index e2be5d6857..9c0149800c 100644
--- a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-suspicious-windows-event-predicted-to-be-malicious-activity.asciidoc
@@ -36,7 +36,7 @@ A supervised machine learning model (ProblemChild) has identified a suspicious W
 * Rule Type: Machine Learning
 * Tactic: Defense Evasion
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -73,40 +73,8 @@ The LotL Attack Detection integration detects living-off-the-land activity in Wi
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
-- Under Settings, click Install Living off the Land Attack Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-**Before you can enable this rule**, you'll need to enrich Windows process events with predictions from the Supervised LotL Attack Detection model. This is done via the ingest pipeline named `<package_version>-problem_child_ingest_pipeline` installed with the LotL Attack Detection package.
-- If using an Elastic Beat such as Winlogbeat, add the LotL ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `winlogbeat.yml`.
-- If adding the LotL ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor]. For example, you can check if your winlogbeat or Elastic Defend (the https://docs.elastic.co/en/integrations/endpoint#logs[default index pattern] being `logs-endpoint*`) already has an ingest pipeline by navigating to `Data > Index Management`, finding the index (sometimes you need to toggle "Include hidden indices"), and checking the index's settings for a default or final https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#set-default-pipeline[pipeline].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the LotL ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "problemchild": {
-      "properties": {
-        "prediction": {
-          "type": "long"
-        },
-        "prediction_probability": {
-          "type": "float"
-        }
-      }
-    },
-    "blocklist_label": {
-      "type": "long"
-    }
-  }
-}
-```
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
 
 
 ==== Rule query
diff --git a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score.asciidoc b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score.asciidoc
index 13b2bfe6d6..551768f145 100644
--- a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-a-suspicious-windows-event-with-a-high-malicious-probability-score.asciidoc
@@ -36,7 +36,7 @@ A supervised machine learning model (ProblemChild) has identified a suspicious W
 * Rule Type: Machine Learning
 * Tactic: Defense Evasion
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -73,40 +73,8 @@ The LotL Attack Detection integration detects living-off-the-land activity in Wi
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
-- Under Settings, click Install Living off the Land Attack Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-**Before you can enable this rule**, you'll need to enrich Windows process events with predictions from the Supervised LotL Attack Detection model. This is done via the ingest pipeline named `<package_version>-problem_child_ingest_pipeline` installed with the LotL Attack Detection package.
-- If using an Elastic Beat such as Winlogbeat, add the LotL ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `winlogbeat.yml`.
-- If adding the LotL ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor]. For example, you can check if your winlogbeat or Elastic Defend (the https://docs.elastic.co/en/integrations/endpoint#logs[default index pattern] being `logs-endpoint*`) already has an ingest pipeline by navigating to `Data > Index Management`, finding the index (sometimes you need to toggle "Include hidden indices"), and checking the index's settings for a default or final https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#set-default-pipeline[pipeline].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the LotL ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "problemchild": {
-      "properties": {
-        "prediction": {
-          "type": "long"
-        },
-        "prediction_probability": {
-          "type": "float"
-        }
-      }
-    },
-    "blocklist_label": {
-      "type": "long"
-    }
-  }
-}
-```
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
 
 
 ==== Rule query
diff --git a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain.asciidoc b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain.asciidoc
index a03efbd550..a64b568833 100644
--- a/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/machine-learning-detected-dga-activity-using-a-known-sunburst-dns-domain.asciidoc
@@ -36,7 +36,7 @@ A supervised machine learning model has identified a DNS question name that used
 * Rule Type: Machine Learning
 * Tactic: Command and Control
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -74,37 +74,8 @@ The DGA Detection integration consists of an ML-based framework to detect DGA ac
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Domain Generation Algorithm Detection and select the integration to see more details about it.
-- Under Settings, click Install Domain Generation Algorithm Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-Before you can enable this rule, you'll need to enrich DNS events with predictions from the Supervised DGA Detection model. This is done via the ingest pipeline named `<package_version>-ml_dga_ingest_pipeline` installed with the DGA Detection package.
-- If using an Elastic Beat such as Packetbeat, add the DGA ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `packetbeat.yml`.
-- If adding the DGA ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the DGA ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "ml_is_dga": {
-      "properties": {
-        "malicious_prediction": {
-          "type": "long"
-        },
-        "malicious_probability": {
-          "type": "float"
-        }
-      }
-    }
-  }
-}
-``` 
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Configure the ingest pipeline**.
 
 
 ==== Rule query
diff --git a/docs/detections/prebuilt-rules/rule-details/microsoft-windows-defender-tampering.asciidoc b/docs/detections/prebuilt-rules/rule-details/microsoft-windows-defender-tampering.asciidoc
index 045e981903..32063c5557 100644
--- a/docs/detections/prebuilt-rules/rule-details/microsoft-windows-defender-tampering.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/microsoft-windows-defender-tampering.asciidoc
@@ -42,7 +42,7 @@ Identifies when one or more features on Microsoft Defender are disabled. Adversa
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 110
+*Version*: 111
 
 *Rule authors*: 
 
@@ -162,10 +162,10 @@ registry where host.os.type == "windows" and event.type in ("creation", "change"
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Impair Defenses
-** ID: T1562
-** Reference URL: https://attack.mitre.org/techniques/T1562/
-* Technique:
 ** Name: Modify Registry
 ** ID: T1112
 ** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
+** Name: Impair Defenses
+** ID: T1562
+** Reference URL: https://attack.mitre.org/techniques/T1562/
diff --git a/docs/detections/prebuilt-rules/rule-details/mimikatz-memssp-log-file-detected.asciidoc b/docs/detections/prebuilt-rules/rule-details/mimikatz-memssp-log-file-detected.asciidoc
index 1ee3343f02..3d7fe9aee1 100644
--- a/docs/detections/prebuilt-rules/rule-details/mimikatz-memssp-log-file-detected.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/mimikatz-memssp-log-file-detected.asciidoc
@@ -11,6 +11,7 @@ Identifies the password log file from the default Mimikatz memssp module.
 * logs-endpoint.events.file-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: high
 
@@ -36,8 +37,9 @@ Identifies the password log file from the default Mimikatz memssp module.
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 109
+*Version*: 211
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/modification-of-amsienable-registry-key.asciidoc b/docs/detections/prebuilt-rules/rule-details/modification-of-amsienable-registry-key.asciidoc
index abc0cbd0fd..b5ffb52051 100644
--- a/docs/detections/prebuilt-rules/rule-details/modification-of-amsienable-registry-key.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/modification-of-amsienable-registry-key.asciidoc
@@ -38,7 +38,7 @@ Identifies modifications of the AmsiEnable registry key to 0, which disables the
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 110
+*Version*: 111
 
 *Rule authors*: 
 
@@ -149,6 +149,10 @@ registry where host.os.type == "windows" and event.type in ("creation", "change"
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
 ** Name: Impair Defenses
 ** ID: T1562
 ** Reference URL: https://attack.mitre.org/techniques/T1562/
@@ -156,7 +160,3 @@ registry where host.os.type == "windows" and event.type in ("creation", "change"
 ** Name: Disable or Modify Tools
 ** ID: T1562.001
 ** Reference URL: https://attack.mitre.org/techniques/T1562/001/
-* Technique:
-** Name: Modify Registry
-** ID: T1112
-** Reference URL: https://attack.mitre.org/techniques/T1112/
diff --git a/docs/detections/prebuilt-rules/rule-details/network-activity-detected-via-kworker.asciidoc b/docs/detections/prebuilt-rules/rule-details/network-activity-detected-via-kworker.asciidoc
index cf1b872f28..6d747e06a1 100644
--- a/docs/detections/prebuilt-rules/rule-details/network-activity-detected-via-kworker.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/network-activity-detected-via-kworker.asciidoc
@@ -29,7 +29,7 @@ This rule monitors for network connections from a kworker process. kworker, or k
 * Tactic: Command and Control
 * Data Source: Elastic Defend
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -107,13 +107,13 @@ process.name:kworker* and not destination.ip:(
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Masquerading
-** ID: T1036
-** Reference URL: https://attack.mitre.org/techniques/T1036/
-* Technique:
 ** Name: Rootkit
 ** ID: T1014
 ** Reference URL: https://attack.mitre.org/techniques/T1014/
+* Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
 * Tactic:
 ** Name: Exfiltration
 ** ID: TA0010
diff --git a/docs/detections/prebuilt-rules/rule-details/new-systemd-service-created-by-previously-unknown-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/new-systemd-service-created-by-previously-unknown-process.asciidoc
index 56c9a3ff10..e375210421 100644
--- a/docs/detections/prebuilt-rules/rule-details/new-systemd-service-created-by-previously-unknown-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/new-systemd-service-created-by-previously-unknown-process.asciidoc
@@ -35,7 +35,7 @@ Systemd service files are configuration files in Linux systems used to define an
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 9
+*Version*: 10
 
 *Rule authors*: 
 
@@ -73,8 +73,8 @@ This rule monitors the creation of new systemd service files, potentially indica
   - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
 - Investigate the currently enabled systemd services through the following command `sudo systemctl list-unit-files`.
 - Investigate whether any other files in any of the available systemd directories have been altered through OSQuery.
-  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (\npath LIKE '/etc/systemd/system/%' OR \npath LIKE '/usr/local/lib/systemd/system/%' OR \npath LIKE '/lib/systemd/system/%' OR\npath LIKE '/usr/lib/systemd/system/%' OR\npath LIKE '/home/user/.config/systemd/user/%'\n)\n"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (\npath LIKE '/etc/systemd/system/%' OR \npath LIKE '/usr/local/lib/systemd/system/%' OR \npath LIKE '/lib/systemd/system/%' OR\npath LIKE '/usr/lib/systemd/system/%' OR\npath LIKE '/home/{{user.name}}/.config/systemd/user/%'\n)\n"}}
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/etc/systemd/system/%' OR path LIKE '/usr/local/lib/systemd/system/%' OR path LIKE\n'/lib/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' OR path LIKE '/home/user/.config/systemd/user/%' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/etc/systemd/system/%' OR path LIKE\n'/usr/local/lib/systemd/system/%' OR path LIKE '/lib/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' OR path\nLIKE '/home/{{user.name}}/.config/systemd/user/%' )\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
diff --git a/docs/detections/prebuilt-rules/rule-details/new-systemd-timer-created.asciidoc b/docs/detections/prebuilt-rules/rule-details/new-systemd-timer-created.asciidoc
index b1dcab6ef3..ba03a46689 100644
--- a/docs/detections/prebuilt-rules/rule-details/new-systemd-timer-created.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/new-systemd-timer-created.asciidoc
@@ -35,7 +35,7 @@ Detects the creation of a systemd timer within any of the default systemd timer
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 9
+*Version*: 10
 
 *Rule authors*: 
 
@@ -74,8 +74,8 @@ This rule monitors the creation of new systemd timer files, potentially indicati
 - Investigate the currently enabled systemd timers through the following command `sudo systemctl list-timers`.
 - Search for the systemd service file named similarly to the timer that was created.
 - Investigate whether any other files in any of the available systemd directories have been altered through OSQuery.
-  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (\npath LIKE '/etc/systemd/system/%' OR \npath LIKE '/usr/local/lib/systemd/system/%' OR \npath LIKE '/lib/systemd/system/%' OR\npath LIKE '/usr/lib/systemd/system/%' OR\npath LIKE '/home/user/.config/systemd/user/%'\n)\n"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (\npath LIKE '/etc/systemd/system/%' OR \npath LIKE '/usr/local/lib/systemd/system/%' OR \npath LIKE '/lib/systemd/system/%' OR\npath LIKE '/usr/lib/systemd/system/%' OR\npath LIKE '/home/{{user.name}}/.config/systemd/user/%'\n)\n"}}
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/etc/systemd/system/%' OR path LIKE '/usr/local/lib/systemd/system/%' OR path LIKE\n'/lib/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' OR path LIKE '/home/user/.config/systemd/user/%' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/etc/systemd/system/%' OR path LIKE\n'/usr/local/lib/systemd/system/%' OR path LIKE '/lib/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' OR path\nLIKE '/home/{{user.name}}/.config/systemd/user/%' )\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
diff --git a/docs/detections/prebuilt-rules/rule-details/persistence-via-bits-job-notify-cmdline.asciidoc b/docs/detections/prebuilt-rules/rule-details/persistence-via-bits-job-notify-cmdline.asciidoc
index b87dbe6abb..2ff5e38cca 100644
--- a/docs/detections/prebuilt-rules/rule-details/persistence-via-bits-job-notify-cmdline.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/persistence-via-bits-job-notify-cmdline.asciidoc
@@ -11,6 +11,7 @@ An adversary can use the Background Intelligent Transfer Service (BITS) SetNotif
 * winlogbeat-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -38,8 +39,9 @@ An adversary can use the Background Intelligent Transfer Service (BITS) SetNotif
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 107
+*Version*: 209
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/persistence-via-kde-autostart-script-or-desktop-file-modification.asciidoc b/docs/detections/prebuilt-rules/rule-details/persistence-via-kde-autostart-script-or-desktop-file-modification.asciidoc
index 98c6941439..29fcbcefb4 100644
--- a/docs/detections/prebuilt-rules/rule-details/persistence-via-kde-autostart-script-or-desktop-file-modification.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/persistence-via-kde-autostart-script-or-desktop-file-modification.asciidoc
@@ -36,7 +36,7 @@ Identifies the creation or modification of a K Desktop Environment (KDE) AutoSta
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 110
+*Version*: 111
 
 *Rule authors*: 
 
@@ -71,8 +71,8 @@ The detection rule 'Persistence via KDE AutoStart Script or Desktop File Modific
 
 
 - Investigate the file that was created or modified.
-  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (\n  path LIKE '/home/%/.config/autostart/%.sh' OR path LIKE '/home/%/.config/autostart/%.desktop' OR\n  path LIKE '/root/.config/autostart/%.sh' OR path LIKE '/root/.config/autostart/%.desktop' OR\n  path LIKE '/home/%/.kde/Autostart/%.sh' OR path LIKE '/home/%/.kde/Autostart/%.desktop' OR\n  path LIKE '/root/.kde/Autostart/%.sh' OR path LIKE '/root/.kde/Autostart/%.desktop' OR\n  path LIKE '/home/%/.kde4/Autostart/%.sh' OR path LIKE '/home/%/.kde4/Autostart/%.desktop' OR\n  path LIKE '/root/.kde4/Autostart/%.sh' OR path LIKE '/root/.kde4/Autostart/%.desktop' OR\n  path LIKE '/home/%/.kde/share/autostart/%.sh' OR path LIKE '/home/%/.kde/share/autostart/%.desktop' OR\n  path LIKE '/root/.kde/share/autostart/%.sh' OR path LIKE '/root/.kde/share/autostart/%.desktop' OR\n  path LIKE '/home/%/.kde4/share/autostart/%.sh' OR path LIKE '/home/%/.kde4/share/autostart/%.desktop' OR\n  path LIKE '/root/.kde4/share/autostart/%.sh' OR path LIKE '/root/.kde4/share/autostart/%.desktop' OR\n  path LIKE '/home/%/.local/share/autostart/%.sh' OR path LIKE '/home/%/.local/share/autostart/%.desktop' OR\n  path LIKE '/root/.local/share/autostart/%.sh' OR path LIKE '/root/.local/share/autostart/%.desktop' OR\n  path LIKE '/home/%/.config/autostart-scripts/%.sh' OR path LIKE '/home/%/.config/autostart-scripts/%.desktop' OR\n  path LIKE '/root/.config/autostart-scripts/%.sh' OR path LIKE '/root/.config/autostart-scripts/%.desktop' OR\n  path LIKE '/etc/xdg/autostart/%.sh' OR path LIKE '/etc/xdg/autostart/%.desktop' OR\n  path LIKE '/usr/share/autostart/%.sh' OR path LIKE '/usr/share/autostart/%.desktop'\n)\n"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (\n  path LIKE '/home/%/.config/autostart/%.sh' OR path LIKE '/home/%/.config/autostart/%.desktop' OR\n  path LIKE '/root/.config/autostart/%.sh' OR path LIKE '/root/.config/autostart/%.desktop' OR\n  path LIKE '/home/%/.kde/Autostart/%.sh' OR path LIKE '/home/%/.kde/Autostart/%.desktop' OR\n  path LIKE '/root/.kde/Autostart/%.sh' OR path LIKE '/root/.kde/Autostart/%.desktop' OR\n  path LIKE '/home/%/.kde4/Autostart/%.sh' OR path LIKE '/home/%/.kde4/Autostart/%.desktop' OR\n  path LIKE '/root/.kde4/Autostart/%.sh' OR path LIKE '/root/.kde4/Autostart/%.desktop' OR\n  path LIKE '/home/%/.kde/share/autostart/%.sh' OR path LIKE '/home/%/.kde/share/autostart/%.desktop' OR\n  path LIKE '/root/.kde/share/autostart/%.sh' OR path LIKE '/root/.kde/share/autostart/%.desktop' OR\n  path LIKE '/home/%/.kde4/share/autostart/%.sh' OR path LIKE '/home/%/.kde4/share/autostart/%.desktop' OR\n  path LIKE '/root/.kde4/share/autostart/%.sh' OR path LIKE '/root/.kde4/share/autostart/%.desktop' OR\n  path LIKE '/home/%/.local/share/autostart/%.sh' OR path LIKE '/home/%/.local/share/autostart/%.desktop' OR\n  path LIKE '/root/.local/share/autostart/%.sh' OR path LIKE '/root/.local/share/autostart/%.desktop' OR\n  path LIKE '/home/%/.config/autostart-scripts/%.sh' OR path LIKE '/home/%/.config/autostart-scripts/%.desktop' OR\n  path LIKE '/root/.config/autostart-scripts/%.sh' OR path LIKE '/root/.config/autostart-scripts/%.desktop' OR\n  path LIKE '/etc/xdg/autostart/%.sh' OR path LIKE '/etc/xdg/autostart/%.desktop' OR\n  path LIKE '/usr/share/autostart/%.sh' OR path LIKE '/usr/share/autostart/%.desktop'\n)\n"}}
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/home/%/.config/autostart/%.sh' OR path LIKE '/home/%/.config/autostart/%.desktop'\nOR path LIKE '/root/.config/autostart/%.sh' OR path LIKE '/root/.config/autostart/%.desktop' OR path LIKE\n'/home/%/.kde/Autostart/%.sh' OR path LIKE '/home/%/.kde/Autostart/%.desktop' OR path LIKE '/root/.kde/Autostart/%.sh'\nOR path LIKE '/root/.kde/Autostart/%.desktop' OR path LIKE '/home/%/.kde4/Autostart/%.sh' OR path LIKE\n'/home/%/.kde4/Autostart/%.desktop' OR path LIKE '/root/.kde4/Autostart/%.sh' OR path LIKE\n'/root/.kde4/Autostart/%.desktop' OR path LIKE '/home/%/.kde/share/autostart/%.sh' OR path LIKE\n'/home/%/.kde/share/autostart/%.desktop' OR path LIKE '/root/.kde/share/autostart/%.sh' OR path LIKE\n'/root/.kde/share/autostart/%.desktop' OR path LIKE '/home/%/.kde4/share/autostart/%.sh' OR path LIKE\n'/home/%/.kde4/share/autostart/%.desktop' OR path LIKE '/root/.kde4/share/autostart/%.sh' OR path LIKE\n'/root/.kde4/share/autostart/%.desktop' OR path LIKE '/home/%/.local/share/autostart/%.sh' OR path LIKE\n'/home/%/.local/share/autostart/%.desktop' OR path LIKE '/root/.local/share/autostart/%.sh' OR path LIKE\n'/root/.local/share/autostart/%.desktop' OR path LIKE '/home/%/.config/autostart-scripts/%.sh' OR path LIKE\n'/home/%/.config/autostart-scripts/%.desktop' OR path LIKE '/root/.config/autostart-scripts/%.sh' OR path LIKE\n'/root/.config/autostart-scripts/%.desktop' OR path LIKE '/etc/xdg/autostart/%.sh' OR path LIKE\n'/etc/xdg/autostart/%.desktop' OR path LIKE '/usr/share/autostart/%.sh' OR path LIKE '/usr/share/autostart/%.desktop' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/home/%/.config/autostart/%.sh' OR\npath LIKE '/home/%/.config/autostart/%.desktop' OR path LIKE '/root/.config/autostart/%.sh' OR path LIKE\n'/root/.config/autostart/%.desktop' OR path LIKE '/home/%/.kde/Autostart/%.sh' OR path LIKE\n'/home/%/.kde/Autostart/%.desktop' OR path LIKE '/root/.kde/Autostart/%.sh' OR path LIKE\n'/root/.kde/Autostart/%.desktop' OR path LIKE '/home/%/.kde4/Autostart/%.sh' OR path LIKE\n'/home/%/.kde4/Autostart/%.desktop' OR path LIKE '/root/.kde4/Autostart/%.sh' OR path LIKE\n'/root/.kde4/Autostart/%.desktop' OR path LIKE '/home/%/.kde/share/autostart/%.sh' OR path LIKE\n'/home/%/.kde/share/autostart/%.desktop' OR path LIKE '/root/.kde/share/autostart/%.sh' OR path LIKE\n'/root/.kde/share/autostart/%.desktop' OR path LIKE '/home/%/.kde4/share/autostart/%.sh' OR path LIKE\n'/home/%/.kde4/share/autostart/%.desktop' OR path LIKE '/root/.kde4/share/autostart/%.sh' OR path LIKE\n'/root/.kde4/share/autostart/%.desktop' OR path LIKE '/home/%/.local/share/autostart/%.sh' OR path LIKE\n'/home/%/.local/share/autostart/%.desktop' OR path LIKE '/root/.local/share/autostart/%.sh' OR path LIKE\n'/root/.local/share/autostart/%.desktop' OR path LIKE '/home/%/.config/autostart-scripts/%.sh' OR path LIKE\n'/home/%/.config/autostart-scripts/%.desktop' OR path LIKE '/root/.config/autostart-scripts/%.sh' OR path LIKE\n'/root/.config/autostart-scripts/%.desktop' OR path LIKE '/etc/xdg/autostart/%.sh' OR path LIKE\n'/etc/xdg/autostart/%.desktop' OR path LIKE '/usr/share/autostart/%.sh' OR path LIKE '/usr/share/autostart/%.desktop' )\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
diff --git a/docs/detections/prebuilt-rules/rule-details/persistence-via-scheduled-job-creation.asciidoc b/docs/detections/prebuilt-rules/rule-details/persistence-via-scheduled-job-creation.asciidoc
index 979060630a..be3a4bae50 100644
--- a/docs/detections/prebuilt-rules/rule-details/persistence-via-scheduled-job-creation.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/persistence-via-scheduled-job-creation.asciidoc
@@ -11,6 +11,7 @@ A job can be used to schedule programs or scripts to be executed at a specified
 * logs-endpoint.events.file-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -33,8 +34,9 @@ A job can be used to schedule programs or scripts to be executed at a specified
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 108
+*Version*: 210
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/port-forwarding-rule-addition.asciidoc b/docs/detections/prebuilt-rules/rule-details/port-forwarding-rule-addition.asciidoc
index 162c846cbc..335bfe595e 100644
--- a/docs/detections/prebuilt-rules/rule-details/port-forwarding-rule-addition.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/port-forwarding-rule-addition.asciidoc
@@ -11,6 +11,7 @@ Identifies the creation of a new port forwarding rule. An adversary may abuse th
 * logs-endpoint.events.registry-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -37,8 +38,9 @@ Identifies the creation of a new port forwarding rule. An adversary may abuse th
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 110
+*Version*: 212
 
 *Rule authors*: 
 
@@ -123,7 +125,8 @@ For more details on adding a custom ingest pipeline refer - https://www.elastic.
 ----------------------------------
 registry where host.os.type == "windows" and registry.path : (
   "HKLM\\SYSTEM\\*ControlSet*\\Services\\PortProxy\\v4tov4\\*",
-  "\\REGISTRY\\MACHINE\\SYSTEM\\*ControlSet*\\Services\\PortProxy\\v4tov4\\*"
+  "\\REGISTRY\\MACHINE\\SYSTEM\\*ControlSet*\\Services\\PortProxy\\v4tov4\\*",
+  "MACHINE\\SYSTEM\\*ControlSet*\\Services\\PortProxy\\v4tov4\\*"
 )
 
 ----------------------------------
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-buffer-overflow-attack-detected.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-buffer-overflow-attack-detected.asciidoc
index 57af69941b..c64594419a 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-buffer-overflow-attack-detected.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-buffer-overflow-attack-detected.asciidoc
@@ -31,7 +31,7 @@ Detects potential buffer overflow attacks by querying the "Segfault Detected" pr
 * Use Case: Vulnerability
 * Rule Type: Higher-Order Rule
 
-*Version*: 2
+*Version*: 3
 
 *Rule authors*: 
 
@@ -62,7 +62,7 @@ As a higher-order rule (based on other detections), this rule also requires the
 
 [source, js]
 ----------------------------------
-kibana.alert.rule.rule_id:5c81fc9d-1eae-437f-ba07-268472967013 and event.kind:signal
+kibana.alert.rule.rule_id:"5c81fc9d-1eae-437f-ba07-268472967013" and host.os.type:linux and event.kind:signal
 
 ----------------------------------
 
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-destination-port.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-destination-port.asciidoc
index 8b9714d938..dfc9496204 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-destination-port.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-destination-port.asciidoc
@@ -30,7 +30,7 @@ A machine learning job has detected data exfiltration to a particular destinatio
 * Rule Type: Machine Learning
 * Tactic: Exfiltration
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,16 +67,8 @@ The Data Exfiltration Detection integration detects data exfiltration activity b
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
-- Under Settings, click Install Data Exfiltration Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Data Exfiltration Detection, you'll need to enable the corresponding Anomaly Detection jobs. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your network data. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `logs-network_traffic.*` if you used Network Packet Capture.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/ded/kibana/ml_module/ded-ml.json[this] configuration file, you will see a card for Data Exfiltration Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-ip-address.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-ip-address.asciidoc
index 5732f82689..271dab79a8 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-ip-address.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-ip-address.asciidoc
@@ -30,7 +30,7 @@ A machine learning job has detected data exfiltration to a particular geo-locati
 * Rule Type: Machine Learning
 * Tactic: Exfiltration
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,16 +67,8 @@ The Data Exfiltration Detection integration detects data exfiltration activity b
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
-- Under Settings, click Install Data Exfiltration Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Data Exfiltration Detection, you'll need to enable the corresponding Anomaly Detection jobs. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your network data. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `logs-network_traffic.*` if you used Network Packet Capture.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/ded/kibana/ml_module/ded-ml.json[this] configuration file, you will see a card for Data Exfiltration Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-iso-code.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-iso-code.asciidoc
index e5508212fd..16fd5633c2 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-iso-code.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-iso-code.asciidoc
@@ -30,7 +30,7 @@ A machine learning job has detected data exfiltration to a particular geo-locati
 * Rule Type: Machine Learning
 * Tactic: Exfiltration
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,16 +67,8 @@ The Data Exfiltration Detection integration detects data exfiltration activity b
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
-- Under Settings, click Install Data Exfiltration Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Data Exfiltration Detection, you'll need to enable the corresponding Anomaly Detection jobs. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your network data. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `logs-network_traffic.*` if you used Network Packet Capture.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/ded/kibana/ml_module/ded-ml.json[this] configuration file, you will see a card for Data Exfiltration Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-region.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-region.asciidoc
index 850bec3f0f..f6015f77d1 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-region.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-data-exfiltration-activity-to-an-unusual-region.asciidoc
@@ -30,7 +30,7 @@ A machine learning job has detected data exfiltration to a particular geo-locati
 * Rule Type: Machine Learning
 * Tactic: Exfiltration
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,16 +67,8 @@ The Data Exfiltration Detection integration detects data exfiltration activity b
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
-- Under Settings, click Install Data Exfiltration Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Data Exfiltration Detection, you'll need to enable the corresponding Anomaly Detection jobs. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your network data. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `logs-network_traffic.*` if you used Network Packet Capture.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/ded/kibana/ml_module/ded-ml.json[this] configuration file, you will see a card for Data Exfiltration Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-dga-activity.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-dga-activity.asciidoc
index a82b558f4c..d2a44bcbec 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-dga-activity.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-dga-activity.asciidoc
@@ -30,7 +30,7 @@ A population analysis machine learning job detected potential DGA (domain genera
 * Rule Type: Machine Learning
 * Tactic: Command and Control
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -68,37 +68,8 @@ The DGA Detection integration consists of an ML-based framework to detect DGA ac
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Domain Generation Algorithm Detection and select the integration to see more details about it.
-- Under Settings, click Install Domain Generation Algorithm Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-Before you can enable this rule, you'll need to enrich DNS events with predictions from the Supervised DGA Detection model. This is done via the ingest pipeline named `<package_version>-ml_dga_ingest_pipeline` installed with the DGA Detection package.
-- If using an Elastic Beat such as Packetbeat, add the DGA ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `packetbeat.yml`.
-- If adding the DGA ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the DGA ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "ml_is_dga": {
-      "properties": {
-        "malicious_prediction": {
-          "type": "long"
-        },
-        "malicious_probability": {
-          "type": "float"
-        }
-      }
-    }
-  }
-}
-```
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Anomaly Detection Setup*
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-linux-backdoor-user-account-creation.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-linux-backdoor-user-account-creation.asciidoc
index 6f32d63d6e..66a3ed8a51 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-linux-backdoor-user-account-creation.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-linux-backdoor-user-account-creation.asciidoc
@@ -35,7 +35,7 @@ Identifies the attempt to create a new backdoor user by setting the user's UID t
 * Data Source: Elastic Defend
 * Data Source: Auditd Manager
 
-*Version*: 6
+*Version*: 7
 
 *Rule authors*: 
 
@@ -69,7 +69,7 @@ This rule identifies the usage of the `usermod` command to set a user's UID to 0
 *Possible investigation steps*
 
 - Investigate the user account that got assigned a uid of 0, and analyze its corresponding attributes.
-  - !{osquery{"label":"Osquery - Retrieve User Accounts with a UID of 0","query":"SELECT description, gid, gid_signed, shell, uid, uid_signed, username FROM users WHERE username != 'root' AND uid LIKE '0'"}}
+  - !{osquery{"label":"Osquery - Retrieve User Accounts with a UID of 0","query":"SELECT description, gid, gid_signed, shell, uid, uid_signed, username FROM users WHERE username != 'root' AND uid LIKE\n'0'\n"}}
 - Investigate the process execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-network-sweep-detected.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-network-sweep-detected.asciidoc
index d8388fe0dd..a69a74b322 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-network-sweep-detected.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-network-sweep-detected.asciidoc
@@ -1,7 +1,7 @@
 [[potential-network-sweep-detected]]
 === Potential Network Sweep Detected
 
-This rule identifies a potential network sweep.  A network sweep is a method used by attackers to scan a target network, identifying active hosts, open ports, and available services to gather information on vulnerabilities and weaknesses. This reconnaissance helps them plan subsequent attacks and exploit potential entry points for unauthorized access, data theft, or other malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination hosts on commonly used network services.
+This rule identifies a potential network sweep. A network sweep is a method used by attackers to scan a target network, identifying active hosts, open ports, and available services to gather information on vulnerabilities and weaknesses. This reconnaissance helps them plan subsequent attacks and exploit potential entry points for unauthorized access, data theft, or other malicious activities. This rule proposes threshold logic to check for connection attempts from one source host to 10 or more destination hosts on commonly used network services.
 
 *Rule type*: threshold
 
@@ -32,7 +32,7 @@ This rule identifies a potential network sweep.  A network sweep is a method use
 * Tactic: Reconnaissance
 * Use Case: Network Security Monitoring
 
-*Version*: 5
+*Version*: 6
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-non-standard-port-http-https-connection.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-non-standard-port-http-https-connection.asciidoc
index ef179542d9..e7321c921d 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-non-standard-port-http-https-connection.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-non-standard-port-http-https-connection.asciidoc
@@ -33,7 +33,7 @@ Identifies potentially malicious processes communicating via a port paring typic
 * Data Source: Elastic Defend
 * Data Source: Elastic Endgame
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -134,10 +134,6 @@ network where process.name : ("http", "https") and destination.port not in (80,
 ** ID: TA0011
 ** Reference URL: https://attack.mitre.org/tactics/TA0011/
 * Technique:
-** Name: Non-Standard Port
-** ID: T1571
-** Reference URL: https://attack.mitre.org/techniques/T1571/
-* Technique:
 ** Name: Application Layer Protocol
 ** ID: T1071
 ** Reference URL: https://attack.mitre.org/techniques/T1071/
@@ -146,6 +142,10 @@ network where process.name : ("http", "https") and destination.port not in (80,
 ** ID: T1071.001
 ** Reference URL: https://attack.mitre.org/techniques/T1071/001/
 * Technique:
+** Name: Non-Standard Port
+** ID: T1571
+** Reference URL: https://attack.mitre.org/techniques/T1571/
+* Technique:
 ** Name: Encrypted Channel
 ** ID: T1573
 ** Reference URL: https://attack.mitre.org/techniques/T1573/
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-init-d-detected.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-init-d-detected.asciidoc
index 7cd6752b03..66b954ba9e 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-init-d-detected.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-init-d-detected.asciidoc
@@ -36,7 +36,7 @@ Files that are placed in the /etc/init.d/ directory in Unix can be used to start
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 9
+*Version*: 10
 
 *Rule authors*: 
 
@@ -73,7 +73,7 @@ This rule looks for the creation of new files within the `/etc/init.d/` director
   - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
 - Investigate whether any other files in the `/etc/init.d/` or `/run/systemd/generator.late/` directories have been altered.
   - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (path LIKE '/etc/init.d/%' OR path LIKE '/run/systemd/generator.late/%')"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (path LIKE '/etc/init.d/%' OR path LIKE '/run/systemd/generator.late/%')\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE (path LIKE '/etc/init.d/%' OR path LIKE\n'/run/systemd/generator.late/%')\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate syslog through the `sudo cat /var/log/syslog | grep 'LSB'` command to find traces of the LSB header of the script (if present). If syslog is being ingested into Elasticsearch, the same can be accomplished through Kibana.
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-motd-file-creation-detected.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-motd-file-creation-detected.asciidoc
index 803126a3db..167a1ada3d 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-motd-file-creation-detected.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-motd-file-creation-detected.asciidoc
@@ -34,7 +34,7 @@ Message of the day (MOTD) is the message that is presented to the user when a us
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 9
+*Version*: 10
 
 *Rule authors*: 
 
@@ -72,7 +72,7 @@ This rule identifies the creation of new files within the `/etc/update-motd.d/`
   - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
 - Investigate whether any other files in the `/etc/update-motd.d/` or `/usr/lib/update-notifier/` directories have been altered.
   - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE '/usr/lib/update-notifier/%')"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE '/usr/lib/update-notifier/%')\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE\n'/usr/lib/update-notifier/%')\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-run-control-detected.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-run-control-detected.asciidoc
index c853f22dc6..496fbc2b5e 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-run-control-detected.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-persistence-through-run-control-detected.asciidoc
@@ -36,7 +36,7 @@ This rule monitors the creation/alteration of the rc.local file by a previously
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 110
+*Version*: 111
 
 *Rule authors*: 
 
@@ -76,7 +76,7 @@ Detection alerts from this rule indicate the creation of a new `/etc/rc.local` f
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate whether the `/lib/systemd/system/rc-local.service` and `/run/systemd/generator/multi-user.target.wants/rc-local.service` files were created through the `systemd-rc-local-generator` located at `/usr/lib/systemd/system-generators/systemd-rc-local-generator`.
-  - !{osquery{"label":"Osquery - Retrieve rc-local.service File Information","query":"SELECT * FROM file WHERE (path = '/run/systemd/generator/multi-user.target.wants/rc-local.service' OR path = '/run/systemd/generator/multi-user.target.wants/rc-local.service')"}}
+  - !{osquery{"label":"Osquery - Retrieve rc-local.service File Information","query":"SELECT * FROM file WHERE (path = '/run/systemd/generator/multi-user.target.wants/rc-local.service' OR path =\n'/run/systemd/generator/multi-user.target.wants/rc-local.service')\n"}}
   - In case the file is not present here, `sudo systemctl status rc-local` can be executed to find the location of the rc-local unit file.
   - If `rc-local.service` is found, manual investigation is required to check for the rc script execution. Systemd will generate syslogs in case of the execution of the rc-local service. `sudo cat /var/log/syslog | grep "rc-local.service|/etc/rc.local Compatibility"` can be executed to check for the execution of the service.
     - If logs are found, it's likely that the contents of the `rc.local` file have been executed. Analyze the logs. In case several syslog log files are available, use a wildcard to search through all of the available logs.
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-ransomware-behavior-high-count-of-readme-files-by-system.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-ransomware-behavior-high-count-of-readme-files-by-system.asciidoc
index 3bbbb295aa..89b38bbd6b 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-ransomware-behavior-high-count-of-readme-files-by-system.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-ransomware-behavior-high-count-of-readme-files-by-system.asciidoc
@@ -15,7 +15,7 @@ This rule identifies a high number (20) of file creation event by the System vir
 
 *Runs every*: 5m
 
-*Searches indices from*: now-1m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
 
 *Maximum alerts per execution*: 100
 
@@ -32,7 +32,7 @@ This rule identifies a high number (20) of file creation event by the System vir
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 1
+*Version*: 2
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-ransomware-note-file-dropped-via-smb.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-ransomware-note-file-dropped-via-smb.asciidoc
index 16bb06ed6d..81407b6198 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-ransomware-note-file-dropped-via-smb.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-ransomware-note-file-dropped-via-smb.asciidoc
@@ -30,7 +30,7 @@ Identifies an incoming SMB connection followed by the creation of a file with a
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 1
+*Version*: 2
 
 *Rule authors*: 
 
@@ -115,13 +115,13 @@ sequence by host.id with maxspan=1s
 ** ID: TA0040
 ** Reference URL: https://attack.mitre.org/tactics/TA0040/
 * Technique:
-** Name: Inhibit System Recovery
-** ID: T1490
-** Reference URL: https://attack.mitre.org/techniques/T1490/
-* Technique:
 ** Name: Data Destruction
 ** ID: T1485
 ** Reference URL: https://attack.mitre.org/techniques/T1485/
+* Technique:
+** Name: Inhibit System Recovery
+** ID: T1490
+** Reference URL: https://attack.mitre.org/techniques/T1490/
 * Tactic:
 ** Name: Lateral Movement
 ** ID: TA0008
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-remote-desktop-tunneling-detected.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-remote-desktop-tunneling-detected.asciidoc
index d6f1b8909f..81a17b8f49 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-remote-desktop-tunneling-detected.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-remote-desktop-tunneling-detected.asciidoc
@@ -12,6 +12,7 @@ Identifies potential use of an SSH utility to establish RDP over a reverse SSH T
 * logs-windows.*
 * endgame-*
 * logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: high
 
@@ -37,8 +38,9 @@ Identifies potential use of an SSH utility to establish RDP over a reverse SSH T
 * Resources: Investigation Guide
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
+* Data Source: SentinelOne
 
-*Version*: 110
+*Version*: 212
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-reverse-shell-via-child.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-reverse-shell-via-child.asciidoc
index 6af72f1eba..be5cd484ae 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-reverse-shell-via-child.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-reverse-shell-via-child.asciidoc
@@ -31,7 +31,7 @@ This detection rule identifies suspicious network traffic patterns associated wi
 * Tactic: Execution
 * Data Source: Elastic Defend
 
-*Version*: 2
+*Version*: 3
 
 *Rule authors*: 
 
@@ -85,12 +85,13 @@ For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/
 [source, js]
 ----------------------------------
 sequence by host.id, process.entity_id with maxspan=5s
-  [network where event.type == "start" and event.action in ("connection_attempted", "connection_accepted") and 
-   process.name : ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish", "socat") and destination.ip != null and 
-   not cidrmatch(destination.ip, "127.0.0.0/8", "169.254.0.0/16", "224.0.0.0/4", "::1")]
-  [process where event.type == "start" and event.action == "exec" and 
-   process.name in ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish") and (
-     (process.args : ("-i", "-l")) or (process.parent.name == "socat" and process.parent.args : "*exec*")
+  [network where event.type == "start" and host.os.type == "linux" and
+     event.action in ("connection_attempted", "connection_accepted") and
+     process.name : ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish", "socat") and destination.ip != null and
+     not cidrmatch(destination.ip, "127.0.0.0/8", "169.254.0.0/16", "224.0.0.0/4", "::1")]
+  [process where event.type == "start" and host.os.type == "linux" and event.action == "exec" and
+     process.name in ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish") and (
+       (process.args : ("-i", "-l")) or (process.parent.name == "socat" and process.parent.args : "*exec*")
    )]
 
 ----------------------------------
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-reverse-shell.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-reverse-shell.asciidoc
index 6a78e3dcb2..f23a3c5148 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-reverse-shell.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-reverse-shell.asciidoc
@@ -31,7 +31,7 @@ This detection rule identifies suspicious network traffic patterns associated wi
 * Tactic: Execution
 * Data Source: Elastic Defend
 
-*Version*: 8
+*Version*: 9
 
 *Rule authors*: 
 
@@ -83,12 +83,13 @@ For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/
 [source, js]
 ----------------------------------
 sequence by host.id with maxspan=5s
-  [network where event.type == "start" and event.action in ("connection_attempted", "connection_accepted") and 
-   process.name : ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish", "socat") and destination.ip != null and 
-   not cidrmatch(destination.ip, "127.0.0.0/8", "169.254.0.0/16", "224.0.0.0/4", "::1")] by process.entity_id
-  [process where event.type == "start" and event.action in ("exec", "fork") and 
-   process.name in ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish") and (
-     (process.args : ("-i", "-l")) or (process.parent.name == "socat" and process.parent.args : "*exec*")
+  [network where event.type == "start" and host.os.type == "linux" and
+     event.action in ("connection_attempted", "connection_accepted") and
+     process.name : ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish", "socat") and destination.ip != null and
+     not cidrmatch(destination.ip, "127.0.0.0/8", "169.254.0.0/16", "224.0.0.0/4", "::1")] by process.entity_id
+  [process where event.type == "start" and host.os.type == "linux" and event.action in ("exec", "fork") and
+     process.name in ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish") and (
+       (process.args : ("-i", "-l")) or (process.parent.name == "socat" and process.parent.args : "*exec*")
    )] by process.parent.entity_id
 
 ----------------------------------
diff --git a/docs/detections/prebuilt-rules/rule-details/potential-suspicious-file-edit.asciidoc b/docs/detections/prebuilt-rules/rule-details/potential-suspicious-file-edit.asciidoc
index 0d8a2937d4..3763d139e9 100644
--- a/docs/detections/prebuilt-rules/rule-details/potential-suspicious-file-edit.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/potential-suspicious-file-edit.asciidoc
@@ -32,7 +32,7 @@ This rule monitors for the potential edit of a suspicious file. In Linux, when e
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -46,7 +46,7 @@ This rule monitors for the potential edit of a suspicious file. In Linux, when e
 
 [source, js]
 ----------------------------------
-file where event.action in ("creation", "file_create_event") and file.extension == "swp" and 
+file where host.os.type == "linux" and event.action in ("creation", "file_create_event") and file.extension == "swp" and
 file.path : (
   /* common interesting files and locations */
   "/etc/.shadow.swp", "/etc/.shadow-.swp", "/etc/.shadow~.swp", "/etc/.gshadow.swp", "/etc/.gshadow-.swp",
@@ -83,14 +83,6 @@ file.path : (
 ** ID: T1037.004
 ** Reference URL: https://attack.mitre.org/techniques/T1037/004/
 * Technique:
-** Name: Hijack Execution Flow
-** ID: T1574
-** Reference URL: https://attack.mitre.org/techniques/T1574/
-* Sub-technique:
-** Name: Dynamic Linker Hijacking
-** ID: T1574.006
-** Reference URL: https://attack.mitre.org/techniques/T1574/006/
-* Technique:
 ** Name: Create or Modify System Process
 ** ID: T1543
 ** Reference URL: https://attack.mitre.org/techniques/T1543/
@@ -98,6 +90,14 @@ file.path : (
 ** Name: Systemd Service
 ** ID: T1543.002
 ** Reference URL: https://attack.mitre.org/techniques/T1543/002/
+* Technique:
+** Name: Hijack Execution Flow
+** ID: T1574
+** Reference URL: https://attack.mitre.org/techniques/T1574/
+* Sub-technique:
+** Name: Dynamic Linker Hijacking
+** ID: T1574.006
+** Reference URL: https://attack.mitre.org/techniques/T1574/006/
 * Tactic:
 ** Name: Privilege Escalation
 ** ID: TA0004
diff --git a/docs/detections/prebuilt-rules/rule-details/powershell-script-block-logging-disabled.asciidoc b/docs/detections/prebuilt-rules/rule-details/powershell-script-block-logging-disabled.asciidoc
index a7b919fc59..62cbbd3494 100644
--- a/docs/detections/prebuilt-rules/rule-details/powershell-script-block-logging-disabled.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/powershell-script-block-logging-disabled.asciidoc
@@ -37,7 +37,7 @@ Identifies attempts to disable PowerShell Script Block Logging via registry modi
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 109
+*Version*: 110
 
 *Rule authors*: 
 
@@ -122,6 +122,10 @@ registry where host.os.type == "windows" and event.type == "change" and
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
 ** Name: Impair Defenses
 ** ID: T1562
 ** Reference URL: https://attack.mitre.org/techniques/T1562/
@@ -129,7 +133,3 @@ registry where host.os.type == "windows" and event.type == "change" and
 ** Name: Disable Windows Event Logging
 ** ID: T1562.002
 ** Reference URL: https://attack.mitre.org/techniques/T1562/002/
-* Technique:
-** Name: Modify Registry
-** ID: T1112
-** Reference URL: https://attack.mitre.org/techniques/T1112/
diff --git a/docs/detections/prebuilt-rules/rule-details/prompt-for-credentials-with-osascript.asciidoc b/docs/detections/prebuilt-rules/rule-details/prompt-for-credentials-with-osascript.asciidoc
index 7c3086138a..4f88e134f7 100644
--- a/docs/detections/prebuilt-rules/rule-details/prompt-for-credentials-with-osascript.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/prompt-for-credentials-with-osascript.asciidoc
@@ -32,7 +32,7 @@ Identifies the use of osascript to execute scripts via standard input that may p
 * Tactic: Credential Access
 * Data Source: Elastic Defend
 
-*Version*: 207
+*Version*: 208
 
 *Rule authors*: 
 
@@ -83,7 +83,7 @@ For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/
 
 [source, js]
 ----------------------------------
-process where event.action == "exec" and
+process where event.action == "exec" and host.os.type == "macos" and
  process.name : "osascript" and process.args : "-e" and process.command_line : ("*osascript*display*dialog*password*", "*osascript*display*dialog*passphrase*") and
  not (process.parent.executable : "/usr/bin/sudo" and process.command_line : "*Encryption Key Escrow*") and
  not (process.command_line : "*-e with timeout of 3600 seconds*" and user.id == "0" and process.parent.executable : "/bin/bash") and
diff --git a/docs/detections/prebuilt-rules/rule-details/quarantine-attrib-removed-by-unsigned-or-untrusted-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/quarantine-attrib-removed-by-unsigned-or-untrusted-process.asciidoc
index 4663d1f26a..c00024af0c 100644
--- a/docs/detections/prebuilt-rules/rule-details/quarantine-attrib-removed-by-unsigned-or-untrusted-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/quarantine-attrib-removed-by-unsigned-or-untrusted-process.asciidoc
@@ -32,7 +32,7 @@ Detects deletion of the quarantine attribute by an unusual process (xattr). In m
 * Tactic: Defense Evasion
 * Data Source: Elastic Defend
 
-*Version*: 108
+*Version*: 109
 
 *Rule authors*: 
 
@@ -83,7 +83,7 @@ For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/
 
 [source, js]
 ----------------------------------
-file where event.action == "extended_attributes_delete" and process.executable != null and
+file where event.action == "extended_attributes_delete" and host.os.type == "macos" and process.executable != null and
 (process.code_signature.trusted == false or process.code_signature.exists == false) and not
 process.executable : ("/usr/bin/xattr", 
                       "/System/*", 
diff --git a/docs/detections/prebuilt-rules/rule-details/registry-persistence-via-appcert-dll.asciidoc b/docs/detections/prebuilt-rules/rule-details/registry-persistence-via-appcert-dll.asciidoc
index b1b68ca898..a6d5690994 100644
--- a/docs/detections/prebuilt-rules/rule-details/registry-persistence-via-appcert-dll.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/registry-persistence-via-appcert-dll.asciidoc
@@ -11,6 +11,7 @@ Detects attempts to maintain persistence by creating registry keys using AppCert
 * logs-endpoint.events.registry-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -34,8 +35,9 @@ Detects attempts to maintain persistence by creating registry keys using AppCert
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 108
+*Version*: 210
 
 *Rule authors*: 
 
@@ -67,7 +69,8 @@ registry where host.os.type == "windows" and
 /* uncomment once stable length(bytes_written_string) > 0 and */
   registry.path : (
     "HKLM\\SYSTEM\\*ControlSet*\\Control\\Session Manager\\AppCertDLLs\\*",
-    "\\REGISTRY\\MACHINE\\SYSTEM\\*ControlSet*\\Control\\Session Manager\\AppCertDLLs\\*"
+    "\\REGISTRY\\MACHINE\\SYSTEM\\*ControlSet*\\Control\\Session Manager\\AppCertDLLs\\*",
+    "MACHINE\\SYSTEM\\*ControlSet*\\Control\\Session Manager\\AppCertDLLs\\*"
   )
 
 ----------------------------------
diff --git a/docs/detections/prebuilt-rules/rule-details/route53-resolver-query-log-configuration-deleted.asciidoc b/docs/detections/prebuilt-rules/rule-details/route53-resolver-query-log-configuration-deleted.asciidoc
index ed54a15ac8..1ca31fc556 100644
--- a/docs/detections/prebuilt-rules/rule-details/route53-resolver-query-log-configuration-deleted.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/route53-resolver-query-log-configuration-deleted.asciidoc
@@ -34,7 +34,7 @@ Identifies when a Route53 Resolver Query Log Configuration is deleted. When a Ro
 * Resources: Investigation Guide
 * Tactic: Defense Evasion
 
-*Version*: 1
+*Version*: 2
 
 *Rule authors*: 
 
@@ -47,7 +47,6 @@ Identifies when a Route53 Resolver Query Log Configuration is deleted. When a Ro
 
 
 
-
 *Triage and Analysis*
 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/service-control-spawned-via-script-interpreter.asciidoc b/docs/detections/prebuilt-rules/rule-details/service-control-spawned-via-script-interpreter.asciidoc
index 03d1e25e2c..b41de7c3cb 100644
--- a/docs/detections/prebuilt-rules/rule-details/service-control-spawned-via-script-interpreter.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/service-control-spawned-via-script-interpreter.asciidoc
@@ -37,7 +37,7 @@ Identifies Service Control (sc.exe) spawning from script interpreter processes t
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 108
+*Version*: 109
 
 *Rule authors*: 
 
@@ -135,6 +135,10 @@ process where host.os.type == "windows" and event.type == "start" and
 ** ID: TA0002
 ** Reference URL: https://attack.mitre.org/tactics/TA0002/
 * Technique:
+** Name: Windows Management Instrumentation
+** ID: T1047
+** Reference URL: https://attack.mitre.org/techniques/T1047/
+* Technique:
 ** Name: Command and Scripting Interpreter
 ** ID: T1059
 ** Reference URL: https://attack.mitre.org/techniques/T1059/
@@ -150,10 +154,6 @@ process where host.os.type == "windows" and event.type == "start" and
 ** Name: Visual Basic
 ** ID: T1059.005
 ** Reference URL: https://attack.mitre.org/techniques/T1059/005/
-* Technique:
-** Name: Windows Management Instrumentation
-** ID: T1047
-** Reference URL: https://attack.mitre.org/techniques/T1047/
 * Tactic:
 ** Name: Defense Evasion
 ** ID: TA0005
diff --git a/docs/detections/prebuilt-rules/rule-details/shared-object-created-or-changed-by-previously-unknown-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/shared-object-created-or-changed-by-previously-unknown-process.asciidoc
index 1addbb7581..298fbd8e39 100644
--- a/docs/detections/prebuilt-rules/rule-details/shared-object-created-or-changed-by-previously-unknown-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/shared-object-created-or-changed-by-previously-unknown-process.asciidoc
@@ -33,7 +33,7 @@ This rule monitors the creation of shared object files by previously unknown pro
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 7
+*Version*: 8
 
 *Rule authors*: 
 
@@ -69,7 +69,7 @@ This rule monitors the creation of shared object files by previously unknown pro
 
 - Investigate the shared object that was created or modified through OSQuery.
   - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE path = {{file.path}}\n"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE path = {{file.path}}\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE path = {{file.path}}\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
diff --git a/docs/detections/prebuilt-rules/rule-details/solarwinds-process-disabling-services-via-registry.asciidoc b/docs/detections/prebuilt-rules/rule-details/solarwinds-process-disabling-services-via-registry.asciidoc
index 5ae40204cc..bea607514e 100644
--- a/docs/detections/prebuilt-rules/rule-details/solarwinds-process-disabling-services-via-registry.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/solarwinds-process-disabling-services-via-registry.asciidoc
@@ -37,7 +37,7 @@ Identifies a SolarWinds binary modifying the start type of a service to be disab
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 109
+*Version*: 110
 
 *Rule authors*: 
 
@@ -88,6 +88,10 @@ registry where host.os.type == "windows" and registry.path : (
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
 ** Name: Impair Defenses
 ** ID: T1562
 ** Reference URL: https://attack.mitre.org/techniques/T1562/
@@ -95,10 +99,6 @@ registry where host.os.type == "windows" and registry.path : (
 ** Name: Disable or Modify Tools
 ** ID: T1562.001
 ** Reference URL: https://attack.mitre.org/techniques/T1562/001/
-* Technique:
-** Name: Modify Registry
-** ID: T1112
-** Reference URL: https://attack.mitre.org/techniques/T1112/
 * Tactic:
 ** Name: Initial Access
 ** ID: TA0001
diff --git a/docs/detections/prebuilt-rules/rule-details/spike-in-bytes-sent-to-an-external-device-via-airdrop.asciidoc b/docs/detections/prebuilt-rules/rule-details/spike-in-bytes-sent-to-an-external-device-via-airdrop.asciidoc
index d79c85149c..adedcdb2a5 100644
--- a/docs/detections/prebuilt-rules/rule-details/spike-in-bytes-sent-to-an-external-device-via-airdrop.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/spike-in-bytes-sent-to-an-external-device-via-airdrop.asciidoc
@@ -30,7 +30,7 @@ A machine learning job has detected high bytes of data written to an external de
 * Rule Type: Machine Learning
 * Tactic: Exfiltration
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -66,16 +66,8 @@ The Data Exfiltration Detection integration detects data exfiltration activity b
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
-- Under Settings, click Install Data Exfiltration Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Data Exfiltration Detection, you'll need to enable the corresponding Anomaly Detection jobs. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your file events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/ded/kibana/ml_module/ded-ml.json[this] configuration file, you will see a card for Data Exfiltration Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/spike-in-bytes-sent-to-an-external-device.asciidoc b/docs/detections/prebuilt-rules/rule-details/spike-in-bytes-sent-to-an-external-device.asciidoc
index 1f3e4dd10b..80d093ebf0 100644
--- a/docs/detections/prebuilt-rules/rule-details/spike-in-bytes-sent-to-an-external-device.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/spike-in-bytes-sent-to-an-external-device.asciidoc
@@ -30,7 +30,7 @@ A machine learning job has detected high bytes of data written to an external de
 * Rule Type: Machine Learning
 * Tactic: Exfiltration
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -66,16 +66,8 @@ The Data Exfiltration Detection integration detects data exfiltration activity b
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
-- Under Settings, click Install Data Exfiltration Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Data Exfiltration Detection, you'll need to enable the corresponding Anomaly Detection jobs. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your file events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/ded/kibana/ml_module/ded-ml.json[this] configuration file, you will see a card for Data Exfiltration Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-connections-made-from-a-source-ip.asciidoc b/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-connections-made-from-a-source-ip.asciidoc
index 0551be606d..8d288a5a36 100644
--- a/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-connections-made-from-a-source-ip.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-connections-made-from-a-source-ip.asciidoc
@@ -31,7 +31,7 @@ A machine learning job has detected a high count of destination IPs establishing
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,17 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Before enabling the Anomaly Detection jobs, confirm that the Pivot Transform asset is installed and actively gathering data in the destination index `ml-rdp-lmd`.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your transformed RDP process data i.e.`ml-rdp-lmd`.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-connections-made-to-a-destination-ip.asciidoc b/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-connections-made-to-a-destination-ip.asciidoc
index b19128f359..c805ecb914 100644
--- a/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-connections-made-to-a-destination-ip.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-connections-made-to-a-destination-ip.asciidoc
@@ -31,7 +31,7 @@ A machine learning job has detected a high count of source IPs establishing an R
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,17 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Before enabling the Anomaly Detection jobs, confirm that the Pivot Transform asset is installed and actively gathering data in the destination index `ml-rdp-lmd`.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your transformed RDP process data i.e.`ml-rdp-lmd`.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-processes-in-an-rdp-session.asciidoc b/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-processes-in-an-rdp-session.asciidoc
index 70c5fcd663..43a77fdd42 100644
--- a/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-processes-in-an-rdp-session.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/spike-in-number-of-processes-in-an-rdp-session.asciidoc
@@ -31,7 +31,7 @@ A machine learning job has detected unusually high number of processes started i
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,17 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Before enabling the Anomaly Detection jobs, confirm that the Pivot Transform asset is installed and actively gathering data in the destination index `ml-rdp-lmd`.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your transformed RDP process data i.e.`ml-rdp-lmd`.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/spike-in-remote-file-transfers.asciidoc b/docs/detections/prebuilt-rules/rule-details/spike-in-remote-file-transfers.asciidoc
index a5e75dd495..1ff6f2941d 100644
--- a/docs/detections/prebuilt-rules/rule-details/spike-in-remote-file-transfers.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/spike-in-remote-file-transfers.asciidoc
@@ -31,7 +31,7 @@ A machine learning job has detected an abnormal volume of remote files shared on
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,16 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your file events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/ssh-authorized-keys-file-modification.asciidoc b/docs/detections/prebuilt-rules/rule-details/ssh-authorized-keys-file-modification.asciidoc
index 7fef6c953a..8900ae4fd5 100644
--- a/docs/detections/prebuilt-rules/rule-details/ssh-authorized-keys-file-modification.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/ssh-authorized-keys-file-modification.asciidoc
@@ -32,7 +32,7 @@ The Secure Shell (SSH) authorized_keys file specifies which users are allowed to
 * Tactic: Persistence
 * Data Source: Elastic Defend
 
-*Version*: 205
+*Version*: 206
 
 *Rule authors*: 
 
@@ -86,14 +86,6 @@ event.category:file and event.type:(change or creation) and
 ** ID: TA0008
 ** Reference URL: https://attack.mitre.org/tactics/TA0008/
 * Technique:
-** Name: Remote Service Session Hijacking
-** ID: T1563
-** Reference URL: https://attack.mitre.org/techniques/T1563/
-* Sub-technique:
-** Name: SSH Hijacking
-** ID: T1563.001
-** Reference URL: https://attack.mitre.org/techniques/T1563/001/
-* Technique:
 ** Name: Remote Services
 ** ID: T1021
 ** Reference URL: https://attack.mitre.org/techniques/T1021/
@@ -101,3 +93,11 @@ event.category:file and event.type:(change or creation) and
 ** Name: SSH
 ** ID: T1021.004
 ** Reference URL: https://attack.mitre.org/techniques/T1021/004/
+* Technique:
+** Name: Remote Service Session Hijacking
+** ID: T1563
+** Reference URL: https://attack.mitre.org/techniques/T1563/
+* Sub-technique:
+** Name: SSH Hijacking
+** ID: T1563.001
+** Reference URL: https://attack.mitre.org/techniques/T1563/001/
diff --git a/docs/detections/prebuilt-rules/rule-details/ssh-authorized-keys-file-modified-inside-a-container.asciidoc b/docs/detections/prebuilt-rules/rule-details/ssh-authorized-keys-file-modified-inside-a-container.asciidoc
index c3aa161a67..1eb5bdc9ee 100644
--- a/docs/detections/prebuilt-rules/rule-details/ssh-authorized-keys-file-modified-inside-a-container.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/ssh-authorized-keys-file-modified-inside-a-container.asciidoc
@@ -30,7 +30,7 @@ This rule detects the creation or modification of an authorized_keys or sshd_con
 * Tactic: Persistence
 * Tactic: Lateral Movement
 
-*Version*: 2
+*Version*: 3
 
 *Rule authors*: 
 
@@ -68,14 +68,6 @@ file where container.id:"*" and
 ** ID: TA0008
 ** Reference URL: https://attack.mitre.org/tactics/TA0008/
 * Technique:
-** Name: Remote Service Session Hijacking
-** ID: T1563
-** Reference URL: https://attack.mitre.org/techniques/T1563/
-* Sub-technique:
-** Name: SSH Hijacking
-** ID: T1563.001
-** Reference URL: https://attack.mitre.org/techniques/T1563/001/
-* Technique:
 ** Name: Remote Services
 ** ID: T1021
 ** Reference URL: https://attack.mitre.org/techniques/T1021/
@@ -83,3 +75,11 @@ file where container.id:"*" and
 ** Name: SSH
 ** ID: T1021.004
 ** Reference URL: https://attack.mitre.org/techniques/T1021/004/
+* Technique:
+** Name: Remote Service Session Hijacking
+** ID: T1563
+** Reference URL: https://attack.mitre.org/techniques/T1563/
+* Sub-technique:
+** Name: SSH Hijacking
+** ID: T1563.001
+** Reference URL: https://attack.mitre.org/techniques/T1563/001/
diff --git a/docs/detections/prebuilt-rules/rule-details/ssm-session-started-to-ec2-instance.asciidoc b/docs/detections/prebuilt-rules/rule-details/ssm-session-started-to-ec2-instance.asciidoc
new file mode 100644
index 0000000000..10fb368a84
--- /dev/null
+++ b/docs/detections/prebuilt-rules/rule-details/ssm-session-started-to-ec2-instance.asciidoc
@@ -0,0 +1,123 @@
+[[ssm-session-started-to-ec2-instance]]
+=== SSM Session Started to EC2 Instance
+
+Identifies the first occurrence of an AWS resource establishing a session via SSM to an EC2 instance. Adversaries may use AWS Systems Manager to establish a session to an EC2 instance to execute commands on the instance. This can be used to gain access to the instance and perform actions such as privilege escalation. This rule helps detect the first occurrence of this activity for a given AWS resource.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* filebeat-*
+* logs-aws.cloudtrail-*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 10m
+
+*Searches indices from*: now-60m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://docs.aws.amazon.com/systems-manager/latest/APIReference/API_StartSession.html
+* https://hackingthe.cloud/aws/post_exploitation/intercept_ssm_communications/
+
+*Tags*: 
+
+* Domain: Cloud
+* Data Source: AWS
+* Data Source: Amazon Web Services
+* Data Source: AWS SSM
+* Use Case: Threat Detection
+* Tactic: Lateral Movement
+
+*Version*: 1
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and Analysis*
+
+
+
+*Investigating SSM Session Started to EC2 Instance*
+
+
+This rule detects the first instance of an AWS resource initiating an SSM session to an EC2 instance, which could be indicative of legitimate administrative activities or potential malicious actions like command execution or lateral movement.
+
+
+*Possible Investigation Steps*
+
+
+- **Examine the Session Start Event**: Review the AWS CloudTrail log for the event.
+    - Look for the `StartSession` action and verify details such as the `user_identity.arn`, `event.action`, and the target EC2 instance (`aws.cloudtrail.flattened.request_parameters`).
+- **Verify User Identity and Role**: Check the user’s ARN and access key ID (`aws.cloudtrail.user_identity.access_key_id`).
+    - Cross-reference this with IAM to verify if the user had the necessary permissions and if their role typically requires initiating SSM sessions.
+- **Assess Geographic and IP Context**: Analyze the source IP (`source.ip`) and geographic location (`source.geo`) from which the session was initiated.
+    - Determine if these are consistent with typical user locations or if they raise suspicions of compromise or misuse.
+- **Review Session Details**: Examine details like the session ID and stream URL (`aws.cloudtrail.flattened.response_elements`) to understand the scope and nature of the session.
+    - Check if any commands executed during the session were unauthorized or out of ordinary practices.
+- **Correlate with Other Security Events**: Look for other related security events around the time of the session start to identify any pattern or broader attack vector that may involve this user or EC2 instance.
+
+
+*False Positive Analysis*
+
+
+- **Legitimate Administrative Activities**: Confirm whether the SSM session was initiated for valid administrative purposes such as system maintenance, patching, or configuration updates. Verify with the respective teams or personnel.
+
+
+*Response and Remediation*
+
+
+- **Immediate Session Review**: If the session initiation seems suspicious, review all actions taken during the session.
+    - If possible, terminate the session to prevent any potential harm.
+- **Validate and Reinforce Security Policies**: Ensure that policies around SSM session initiation are strict and adhere to the principle of least privilege.
+    - Update IAM policies if necessary to tighten controls.
+- **Incident Response Activation**: If malicious intent or actions are confirmed, activate the incident response protocol.
+    - This includes containment of the threat, eradication of the adversary’s presence, recovery of affected systems, and a thorough investigation.
+- **Enhance Monitoring and Alerts**: Improve monitoring of SSM sessions, particularly focusing on sessions that involve sensitive or critical EC2 instances.
+    - Adjust alerting mechanisms to flag unusual session initiations promptly.
+
+
+*Additional Information*
+
+
+For more in-depth understanding of managing SSM sessions and security best practices, refer to the https://docs.aws.amazon.com/systems-manager/latest/APIReference/API_StartSession.html[AWS Systems Manager documentation]. Additionally, consider the security implications and best practices outlined in https://cloud.hacktricks.xyz/pentesting-cloud/aws-security/aws-privilege-escalation/aws-ssm-privesc[AWS SSM privilege escalation techniques].
+
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.dataset:"aws.cloudtrail" and event.provider:"ssm.amazonaws.com"
+    and event.action:"StartSession" and event.outcome:"success"
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Lateral Movement
+** ID: TA0008
+** Reference URL: https://attack.mitre.org/tactics/TA0008/
+* Technique:
+** Name: Remote Services
+** ID: T1021
+** Reference URL: https://attack.mitre.org/techniques/T1021/
+* Sub-technique:
+** Name: Cloud Services
+** ID: T1021.007
+** Reference URL: https://attack.mitre.org/techniques/T1021/007/
diff --git a/docs/detections/prebuilt-rules/rule-details/statistical-model-detected-c2-beaconing-activity-with-high-confidence.asciidoc b/docs/detections/prebuilt-rules/rule-details/statistical-model-detected-c2-beaconing-activity-with-high-confidence.asciidoc
index d362d9d70d..0ebbd2d37b 100644
--- a/docs/detections/prebuilt-rules/rule-details/statistical-model-detected-c2-beaconing-activity-with-high-confidence.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/statistical-model-detected-c2-beaconing-activity-with-high-confidence.asciidoc
@@ -31,7 +31,7 @@ A statistical model has identified command-and-control (C2) beaconing activity w
 * Use Case: C2 Beaconing Detection
 * Tactic: Command and Control
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -68,7 +68,7 @@ The Network Beaconing Identification integration consists of a statistical frame
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Network Beaconing Identification and select the integration to see more details about it.
-- Under Settings, click "Install Network Beaconing Identification assets" and follow the prompts to install the assets.
+- Follow the instructions under the **Installation** section.
 
 
 ==== Rule query
diff --git a/docs/detections/prebuilt-rules/rule-details/statistical-model-detected-c2-beaconing-activity.asciidoc b/docs/detections/prebuilt-rules/rule-details/statistical-model-detected-c2-beaconing-activity.asciidoc
index 9b67032125..fe4ff38e4e 100644
--- a/docs/detections/prebuilt-rules/rule-details/statistical-model-detected-c2-beaconing-activity.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/statistical-model-detected-c2-beaconing-activity.asciidoc
@@ -31,7 +31,7 @@ A statistical model has identified command-and-control (C2) beaconing activity.
 * Use Case: C2 Beaconing Detection
 * Tactic: Command and Control
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -68,7 +68,7 @@ The Network Beaconing Identification integration consists of a statistical frame
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Network Beaconing Identification and select the integration to see more details about it.
-- Under Settings, click "Install Network Beaconing Identification assets" and follow the prompts to install the assets.
+- Follow the instructions under the **Installation** section.
 
 
 ==== Rule query
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-antimalware-scan-interface-dll.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-antimalware-scan-interface-dll.asciidoc
index 98bfa9736c..576716319d 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-antimalware-scan-interface-dll.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-antimalware-scan-interface-dll.asciidoc
@@ -11,6 +11,7 @@ Identifies the creation of the Antimalware Scan Interface (AMSI) DLL in an unusu
 * logs-endpoint.events.file-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: high
 
@@ -36,8 +37,9 @@ Identifies the creation of the Antimalware Scan Interface (AMSI) DLL in an unusu
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 9
+*Version*: 111
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-endpoint-security-parent-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-endpoint-security-parent-process.asciidoc
index 4e48e658f3..9109ca9f8b 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-endpoint-security-parent-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-endpoint-security-parent-process.asciidoc
@@ -34,7 +34,7 @@ A suspicious Endpoint Security parent process was detected. This may indicate a
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -87,7 +87,6 @@ process where host.os.type == "windows" and event.type == "start" and
         "/enable"
     )
   )
-  
 
 ----------------------------------
 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-file-creation-in-etc-for-persistence.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-file-creation-in-etc-for-persistence.asciidoc
index 4e93a58f17..5827b6d30a 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-file-creation-in-etc-for-persistence.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-file-creation-in-etc-for-persistence.asciidoc
@@ -36,7 +36,7 @@ Detects the manual creation of files in specific etc directories, via user root,
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 113
+*Version*: 114
 
 *Rule authors*: 
 
@@ -72,8 +72,8 @@ This rule monitors for the creation of the most common system-wide configuration
 
 - Investigate the file that was created or modified.
 - Investigate whether any other files in any of the commonly abused directories have been altered through OSQuery.
-  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (\n  path LIKE '/etc/ld.so.conf.d/%' OR\n  path LIKE '/etc/cron.d/%' OR\n  path LIKE '/etc/sudoers.d/%' OR\n  path LIKE '/etc/rc%.d/%' OR\n  path LIKE '/etc/init.d/%' OR\n  path LIKE '/etc/systemd/system/%' OR\n  path LIKE '/usr/lib/systemd/system/%'\n)\n"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (\n  path LIKE '/etc/ld.so.conf.d/%' OR\n  path LIKE '/etc/cron.d/%' OR\n  path LIKE '/etc/sudoers.d/%' OR\n  path LIKE '/etc/rc%.d/%' OR\n  path LIKE '/etc/init.d/%' OR\n  path LIKE '/etc/systemd/system/%' OR\n  path LIKE '/usr/lib/systemd/system/%'\n)\n"}}
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE ( path LIKE '/etc/ld.so.conf.d/%' OR path LIKE '/etc/cron.d/%' OR path LIKE '/etc/sudoers.d/%'\nOR path LIKE '/etc/rc%.d/%' OR path LIKE '/etc/init.d/%' OR path LIKE '/etc/systemd/system/%' OR path LIKE\n'/usr/lib/systemd/system/%' )\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE ( path LIKE '/etc/ld.so.conf.d/%' OR path LIKE\n'/etc/cron.d/%' OR path LIKE '/etc/sudoers.d/%' OR path LIKE '/etc/rc%.d/%' OR path LIKE '/etc/init.d/%' OR path LIKE\n'/etc/systemd/system/%' OR path LIKE '/usr/lib/systemd/system/%' )\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
@@ -204,14 +204,6 @@ file.path : ("/etc/ld.so.conf.d/*", "/etc/cron.d/*", "/etc/sudoers.d/*", "/etc/r
 ** ID: T1037.004
 ** Reference URL: https://attack.mitre.org/techniques/T1037/004/
 * Technique:
-** Name: Hijack Execution Flow
-** ID: T1574
-** Reference URL: https://attack.mitre.org/techniques/T1574/
-* Sub-technique:
-** Name: Dynamic Linker Hijacking
-** ID: T1574.006
-** Reference URL: https://attack.mitre.org/techniques/T1574/006/
-* Technique:
 ** Name: Create or Modify System Process
 ** ID: T1543
 ** Reference URL: https://attack.mitre.org/techniques/T1543/
@@ -219,6 +211,14 @@ file.path : ("/etc/ld.so.conf.d/*", "/etc/cron.d/*", "/etc/sudoers.d/*", "/etc/r
 ** Name: Systemd Service
 ** ID: T1543.002
 ** Reference URL: https://attack.mitre.org/techniques/T1543/002/
+* Technique:
+** Name: Hijack Execution Flow
+** ID: T1574
+** Reference URL: https://attack.mitre.org/techniques/T1574/
+* Sub-technique:
+** Name: Dynamic Linker Hijacking
+** ID: T1574.006
+** Reference URL: https://attack.mitre.org/techniques/T1574/006/
 * Tactic:
 ** Name: Execution
 ** ID: TA0002
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-file-creation-via-kworker.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-file-creation-via-kworker.asciidoc
index 997877ed70..90817eb972 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-file-creation-via-kworker.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-file-creation-via-kworker.asciidoc
@@ -30,7 +30,7 @@ This rule monitors for a file creation event originating from a kworker parent p
 * Tactic: Defense Evasion
 * Data Source: Elastic Defend
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -66,7 +66,7 @@ This rule monitors for suspicious file creation events through the kworker proce
 
 - Investigate the file that was created or modified through OSQuery.
   - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE path = {{file.path}}\n"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE path = {{file.path}}\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE path = {{file.path}}\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
@@ -165,10 +165,11 @@ For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/
 
 [source, js]
 ----------------------------------
-file where event.action in ("creation", "file_create_event") and process.name : "kworker*" and not (
-  (process.name : "kworker*kcryptd*") or 
-  (file.path : ("/var/log/*", "/var/crash/*", "/var/run/*", "/var/lib/systemd/coredump/*", "/var/spool/*"))
-)
+file where host.os.type == "linux" and event.action in ("creation", "file_create_event") and
+  process.name : "kworker*" and not (
+    (process.name : "kworker*kcryptd*") or
+    (file.path : ("/var/log/*", "/var/crash/*", "/var/run/*", "/var/lib/systemd/coredump/*", "/var/spool/*"))
+  )
 
 ----------------------------------
 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-file-renamed-via-smb.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-file-renamed-via-smb.asciidoc
index 1823af63b6..3044c815c1 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-file-renamed-via-smb.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-file-renamed-via-smb.asciidoc
@@ -32,7 +32,7 @@ Identifies an incoming SMB connection followed by a suspicious file rename opera
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 1
+*Version*: 2
 
 *Rule authors*: 
 
@@ -117,13 +117,13 @@ sequence by host.id with maxspan=1s
 ** ID: TA0040
 ** Reference URL: https://attack.mitre.org/tactics/TA0040/
 * Technique:
-** Name: Inhibit System Recovery
-** ID: T1490
-** Reference URL: https://attack.mitre.org/techniques/T1490/
-* Technique:
 ** Name: Data Destruction
 ** ID: T1485
 ** Reference URL: https://attack.mitre.org/techniques/T1485/
+* Technique:
+** Name: Inhibit System Recovery
+** ID: T1490
+** Reference URL: https://attack.mitre.org/techniques/T1490/
 * Tactic:
 ** Name: Lateral Movement
 ** ID: TA0008
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-macos-ms-office-child-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-macos-ms-office-child-process.asciidoc
index 1c72f39bb8..030d731d6e 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-macos-ms-office-child-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-macos-ms-office-child-process.asciidoc
@@ -31,7 +31,7 @@ Identifies suspicious child processes of frequently targeted Microsoft Office ap
 * Tactic: Initial Access
 * Data Source: Elastic Defend
 
-*Version*: 206
+*Version*: 207
 
 *Rule authors*: 
 
@@ -82,7 +82,7 @@ For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/
 
 [source, js]
 ----------------------------------
-process where event.action == "exec" and
+process where event.action == "exec" and host.os.type == "macos" and
     process.parent.name: (
       "Microsoft Word",
       "Microsoft Outlook",
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-microsoft-365-mail-access-by-clientappid.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-microsoft-365-mail-access-by-clientappid.asciidoc
index 6338c69f63..785d9a4912 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-microsoft-365-mail-access-by-clientappid.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-microsoft-365-mail-access-by-clientappid.asciidoc
@@ -31,7 +31,7 @@ Identifies when a Microsoft 365 Mailbox is accessed by a ClientAppId that was ob
 * Use Case: Configuration Audit
 * Tactic: Initial Access
 
-*Version*: 105
+*Version*: 106
 
 *Rule authors*: 
 
@@ -44,18 +44,87 @@ Identifies when a Microsoft 365 Mailbox is accessed by a ClientAppId that was ob
 
 
 
+*Triage and analysis*
+
+
+
+*Investigating Suspicious Microsoft 365 Mail Access by ClientAppId*
+
+
+- Verify the ClientAppId, source.ip and geolocation associated with Mail Access.
+- Verify the total number of used ClientAppId by that specific user.id.
+- Verify if the mailbox owner was on leave and just resumed working or not.
+- Verify if there are other alerts associated with the same user.id.
+- Verify the total number of connections from that ClientAppId, if it's accessing other mailboxes and with a high frequency there is a high chance it's a false positive.
+
+
+*False positive analysis*
+
+
+- Legit Microsoft or third party ClientAppId.
+- User changing of ClientAppId or new connection post an extended period of leave.
+- If the total number of accessed Mailboxes by ClientAppId is too high there is a high chance it's a false positive.
+
 
 ==== Setup
 
 
+
+*Setup*
+
+
 The Office 365 Logs Fleet integration, Filebeat module, or similarly structured data is required to be compatible with this rule.
 
+
 ==== Rule query
 
 
 [source, js]
 ----------------------------------
-event.dataset:o365.audit and event.provider:Exchange and event.category:web and event.action:MailItemsAccessed and event.outcome:success
+event.dataset:o365.audit and event.provider:Exchange and event.category:web and event.action:MailItemsAccessed and event.outcome:success and 
+not o365.audit.ClientAppId : ("13937bba-652e-4c46-b222-3003f4d1ff97" or "6326e366-9d6d-4c70-b22a-34c7ea72d73d" or 
+ "a3883eba-fbe9-48bd-9ed3-dca3e0e84250" or "d3590ed6-52b3-4102-aeff-aad2292ab01c" or "27922004-5251-4030-b22d-91ecd9a37ea4" or 
+ "1fec8e78-bce4-4aaf-ab1b-5451cc387264" or "26a7ee05-5602-4d76-a7ba-eae8b7b67941" or "00000002-0000-0000-c000-000000000000" or 
+ "00000002-0000-0ff1-ce00-000000000000" or "00000003-0000-0000-c000-000000000000" or "ffcb16e8-f789-467c-8ce9-f826a080d987" or 
+ "00000003-0000-0ff1-ce00-000000000000" or "00000004-0000-0ff1-ce00-000000000000" or "00000005-0000-0ff1-ce00-000000000000" or 
+ "00000006-0000-0ff1-ce00-000000000000" or "00000007-0000-0000-c000-000000000000" or "00000007-0000-0ff1-ce00-000000000000" or 
+ "00000009-0000-0000-c000-000000000000" or "0000000c-0000-0000-c000-000000000000" or "00000015-0000-0000-c000-000000000000" or 
+ "0000001a-0000-0000-c000-000000000000" or "00b41c95-dab0-4487-9791-b9d2c32c80f2" or "022907d3-0f1b-48f7-badc-1ba6abab6d66" or 
+ "04b07795-8ddb-461a-bbee-02f9e1bf7b46" or "08e18876-6177-487e-b8b5-cf950c1e598c" or "0cb7b9ec-5336-483b-bc31-b15b5788de71" or 
+ "0cd196ee-71bf-4fd6-a57c-b491ffd4fb1e" or "0f698dd4-f011-4d23-a33e-b36416dcb1e6" or "13937bba-652e-4c46-b222-3003f4d1ff97" or 
+ "14d82eec-204b-4c2f-b7e8-296a70dab67e" or "16aeb910-ce68-41d1-9ac3-9e1673ac9575" or "1786c5ed-9644-47b2-8aa0-7201292175b6" or 
+ "17d5e35f-655b-4fb0-8ae6-86356e9a49f5" or "18fbca16-2224-45f6-85b0-f7bf2b39b3f3" or "1950a258-227b-4e31-a9cf-717495945fc2" or 
+ "1b3c667f-cde3-4090-b60b-3d2abd0117f0" or "1fec8e78-bce4-4aaf-ab1b-5451cc387264" or "20a11fe0-faa8-4df5-baf2-f965f8f9972e" or 
+ "23523755-3a2b-41ca-9315-f81f3f566a95" or "243c63a3-247d-41c5-9d83-7788c43f1c43" or "268761a2-03f3-40df-8a8b-c3db24145b6b" or 
+ "26a7ee05-5602-4d76-a7ba-eae8b7b67941" or "26abc9a8-24f0-4b11-8234-e86ede698878" or "27922004-5251-4030-b22d-91ecd9a37ea4" or 
+ "28b567f6-162c-4f54-99a0-6887f387bbcc" or "29d9ed98-a469-4536-ade2-f981bc1d605e" or "2abdc806-e091-4495-9b10-b04d93c3f040" or 
+ "2d4d3d8e-2be3-4bef-9f87-7875a61c29de" or "2d7f3606-b07d-41d1-b9d2-0d0c9296a6e8" or "3090ab82-f1c1-4cdf-af2c-5d7a6f3e2cc7" or 
+ "35d54a08-36c9-4847-9018-93934c62740c" or "37182072-3c9c-4f6a-a4b3-b3f91cacffce" or "38049638-cc2c-4cde-abe4-4479d721ed44" or 
+ "3c896ded-22c5-450f-91f6-3d1ef0848f6e" or "4345a7b9-9a63-4910-a426-35363201d503" or "45a330b1-b1ec-4cc1-9161-9f03992aa49f" or 
+ "47629505-c2b6-4a80-adb1-9b3a3d233b7b" or "4765445b-32c6-49b0-83e6-1d93765276ca" or "497effe9-df71-4043-a8bb-14cf78c4b63b" or 
+ "4b233688-031c-404b-9a80-a4f3f2351f90" or "4d5c2d63-cf83-4365-853c-925fd1a64357" or "51be292c-a17e-4f17-9a7e-4b661fb16dd2" or 
+ "5572c4c0-d078-44ce-b81c-6cbf8d3ed39e" or "5e3ce6c0-2b1f-4285-8d4b-75ee78787346" or "60c8bde5-3167-4f92-8fdb-059f6176dc0f" or 
+ "61109738-7d2b-4a0b-9fe3-660b1ff83505" or "62256cef-54c0-4cb4-bcac-4c67989bdc40" or "6253bca8-faf2-4587-8f2f-b056d80998a7" or 
+ "65d91a3d-ab74-42e6-8a2f-0add61688c74" or "66a88757-258c-4c72-893c-3e8bed4d6899" or "67e3df25-268a-4324-a550-0de1c7f97287" or 
+ "69893ee3-dd10-4b1c-832d-4870354be3d8" or "74658136-14ec-4630-ad9b-26e160ff0fc6" or "74bcdadc-2fdc-4bb3-8459-76d06952a0e9" or 
+ "797f4846-ba00-4fd7-ba43-dac1f8f63013" or "7ab7862c-4c57-491e-8a45-d52a7e023983" or "7ae974c5-1af7-4923-af3a-fb1fd14dcb7e" or 
+ "7b7531ad-5926-4f2d-8a1d-38495ad33e17" or "80ccca67-54bd-44ab-8625-4b79c4dc7775" or "835b2a73-6e10-4aa5-a979-21dfda45231c" or 
+ "871c010f-5e61-4fb1-83ac-98610a7e9110" or "89bee1f7-5e6e-4d8a-9f3d-ecd601259da7" or "8edd93e1-2103-40b4-bd70-6e34e586362d" or 
+ "905fcf26-4eb7-48a0-9ff0-8dcc7194b5ba" or "91ca2ca5-3b3e-41dd-ab65-809fa3dffffa" or "93625bc8-bfe2-437a-97e0-3d0060024faa" or 
+ "93d53678-613d-4013-afc1-62e9e444a0a5" or "944f0bd1-117b-4b1c-af26-804ed95e767e" or "94c63fef-13a3-47bc-8074-75af8c65887a" or 
+ "95de633a-083e-42f5-b444-a4295d8e9314" or "97cb1f73-50df-47d1-8fb0-0271f2728514" or "98db8bd6-0cc0-4e67-9de5-f187f1cd1b41" or 
+ "99b904fd-a1fe-455c-b86c-2f9fb1da7687" or "9ea1ad79-fdb6-4f9a-8bc3-2b70f96e34c7" or "a3475900-ccec-4a69-98f5-a65cd5dc5306" or 
+ "a3b79187-70b2-4139-83f9-6016c58cd27b" or "a57aca87-cbc0-4f3c-8b9e-dc095fdc8978" or "a970bac6-63fe-4ec5-8884-8536862c42d4" or 
+ "a9b49b65-0a12-430b-9540-c80b3332c127" or "ab9b8c07-8f02-4f72-87fa-80105867a763" or "ae8e128e-080f-4086-b0e3-4c19301ada69" or 
+ "b23dd4db-9142-4734-867f-3577f640ad0c" or "b4bddae8-ab25-483e-8670-df09b9f1d0ea" or "b669c6ea-1adf-453f-b8bc-6d526592b419" or 
+ "b6e69c34-5f1f-4c34-8cdf-7fea120b8670" or "bb2a2e3a-c5e7-4f0a-88e0-8e01fd3fc1f4" or "bdd48c81-3a58-4ea9-849c-ebea7f6b6360" or 
+ "c1c74fed-04c9-4704-80dc-9f79a2e515cb" or "c35cb2ba-f88b-4d15-aa9d-37bd443522e1" or "c44b4083-3bb0-49c1-b47d-974e53cbdf3c" or 
+ "c9a559d2-7aab-4f13-a6ed-e7e9c52aec87" or "cc15fd57-2c6c-4117-a88c-83b1d56b4bbe" or "cf36b471-5b44-428c-9ce7-313bf84528de" or 
+ "cf53fce8-def6-4aeb-8d30-b158e7b1cf83" or "d176f6e7-38e5-40c9-8a78-3998aab820e7" or "d3590ed6-52b3-4102-aeff-aad2292ab01c" or 
+ "d73f4b35-55c9-48c7-8b10-651f6f2acb2e" or "d9b8ec3a-1e4e-4e08-b3c2-5baf00c0fcb0" or "de8bc8b5-d9f9-48b1-a8ad-b748da725064" or 
+ "dfe74da8-9279-44ec-8fb2-2aed9e1c73d0" or "e1ef36fd-b883-4dbf-97f0-9ece4b576fc6" or "e64aa8bc-8eb4-40e2-898b-cf261a25954f" or 
+ "e9f49c6b-5ce5-44c8-925d-015017e9f7ad" or "ee272b19-4411-433f-8f28-5c13cb6fd407" or "f5eaa862-7f08-448c-9c4e-f4047d4d4521" or 
+ "fb78d390-0c51-40cd-8e17-fdbfab77341b" or "fc0f3af4-6835-4174-b806-f7db311fd2f3" or "fdf9885b-dd37-42bf-82e5-c3129ef5a302")
 
 ----------------------------------
 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-ms-outlook-child-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-ms-outlook-child-process.asciidoc
index a3400b7a8b..c4dfc42f03 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-ms-outlook-child-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-ms-outlook-child-process.asciidoc
@@ -12,6 +12,7 @@ Identifies suspicious child processes of Microsoft Outlook. These child processe
 * logs-windows.*
 * endgame-*
 * logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: low
 
@@ -36,8 +37,9 @@ Identifies suspicious child processes of Microsoft Outlook. These child processe
 * Resources: Investigation Guide
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
+* Data Source: SentinelOne
 
-*Version*: 111
+*Version*: 213
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-network-activity-to-the-internet-by-previously-unknown-executable.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-network-activity-to-the-internet-by-previously-unknown-executable.asciidoc
index 698cb84d56..abb189e4f6 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-network-activity-to-the-internet-by-previously-unknown-executable.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-network-activity-to-the-internet-by-previously-unknown-executable.asciidoc
@@ -1,7 +1,7 @@
 [[suspicious-network-activity-to-the-internet-by-previously-unknown-executable]]
 === Suspicious Network Activity to the Internet by Previously Unknown Executable
 
-This rule monitors for network connectivity to the internet from a previously unknown executable located in a suspicious directory to a previously unknown destination ip. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to establish connections to unknown or suspicious destinations such as a command and control server. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise.
+This rule monitors for network connectivity to the internet from a previously unknown executable located in a suspicious directory. An alert from this rule can indicate the presence of potentially malicious activity, such as the execution of unauthorized or suspicious processes attempting to establish connections to unknown or suspicious destinations such as a command and control server. Detecting and investigating such behavior can help identify and mitigate potential security threats, protecting the system and its data from potential compromise.
 
 *Rule type*: new_terms
 
@@ -34,7 +34,7 @@ This rule monitors for network connectivity to the internet from a previously un
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 8
+*Version*: 9
 
 *Rule authors*: 
 
@@ -211,7 +211,8 @@ Packetbeat is a real-time network packet analyzer that you can use for applicati
 host.os.type:linux and event.category:network and event.action:(connection_attempted or ipv4_connection_attempt_event) and 
 process.executable:(
   (/etc/crontab or /etc/rc.local or ./* or /boot/* or /dev/shm/* or /etc/cron.*/* or /etc/init.d/* or /etc/rc*.d/* or 
-   /etc/update-motd.d/* or /home/*/.* or /run/* or /srv/* or /tmp/* or /usr/lib/update-notifier/* or /var/tmp/*
+   /etc/update-motd.d/* or /home/*/.* or /run/* or /srv/* or /tmp/* or /usr/lib/update-notifier/* or /var/tmp/* or
+   /var/log/*
   ) and not (/tmp/newroot/* or /tmp/snap.rootfs*)
  ) and 
 source.ip:(10.0.0.0/8 or 127.0.0.0/8 or 172.16.0.0/12 or 192.168.0.0/16) and 
@@ -224,8 +225,7 @@ not destination.ip:(
    192.0.0.10/32 or 192.0.0.170/32 or 192.0.0.171/32 or 192.0.0.8/32 or 192.0.0.9/32 or 192.0.2.0/24 or 
    192.168.0.0/16 or 192.175.48.0/24 or 192.31.196.0/24 or 192.52.193.0/24 or 192.88.99.0/24 or 198.18.0.0/15 or 
    198.51.100.0/24 or 203.0.113.0/24 or 224.0.0.0/4 or 240.0.0.0/4 or "::1" or "FE80::/10" or "FF00::/8" or 0.0.0.0
-) and
-not destination.port:(22 or 80 or 443)
+)
 
 ----------------------------------
 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-process-spawned-from-motd-detected.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-process-spawned-from-motd-detected.asciidoc
index b07d3e30e6..f776da3bae 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-process-spawned-from-motd-detected.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-process-spawned-from-motd-detected.asciidoc
@@ -34,7 +34,7 @@ Message of the day (MOTD) is the message that is presented to the user when a us
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 8
+*Version*: 9
 
 *Rule authors*: 
 
@@ -72,7 +72,7 @@ This rule identifies the execution of potentially malicious processes from a MOT
   - !{osquery{"label":"Osquery - Retrieve File Information","query":"SELECT * FROM file WHERE path = {{file.path}}"}}
 - Investigate whether any other files in the `/etc/update-motd.d/` or `/usr/lib/update-notifier/` directories have been altered.
   - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE '/usr/lib/update-notifier/%')"}}
-  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE '/usr/lib/update-notifier/%')\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT f.path, u.username AS file_owner, g.groupname AS group_owner, datetime(f.atime, 'unixepoch') AS\nfile_last_access_time, datetime(f.mtime, 'unixepoch') AS file_last_modified_time, datetime(f.ctime, 'unixepoch') AS\nfile_last_status_change_time, datetime(f.btime, 'unixepoch') AS file_created_time, f.size AS size_bytes FROM file f LEFT\nJOIN users u ON f.uid = u.uid LEFT JOIN groups g ON f.gid = g.gid WHERE (path LIKE '/etc/update-motd.d/%' OR path LIKE\n'/usr/lib/update-notifier/%')\n"}}
 - Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
   - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
 - Investigate other alerts associated with the user/host during the past 48 hours.
@@ -159,8 +159,8 @@ For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/
 
 [source, js]
 ----------------------------------
-process where event.type == "start" and event.action : ("exec", "exec_event") and
-process.parent.executable : ("/etc/update-motd.d/*", "/usr/lib/update-notifier/*") and (
+process where event.type == "start" and host.os.type == "linux" and event.action : ("exec", "exec_event") and
+  process.parent.executable : ("/etc/update-motd.d/*", "/usr/lib/update-notifier/*") and (
   (process.name in ("bash", "dash", "sh", "tcsh", "csh", "zsh", "ksh", "fish") and (
     (process.args : ("-i", "-l")) or (process.parent.name == "socat" and process.parent.args : "*exec*"))) or
   (process.name : ("nc", "ncat", "netcat", "nc.openbsd") and process.args_count >= 3 and 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-screenconnect-client-child-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-screenconnect-client-child-process.asciidoc
index 9672f8383f..dd2be69283 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-screenconnect-client-child-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-screenconnect-client-child-process.asciidoc
@@ -12,6 +12,7 @@ Identifies suspicious processes being spawned by the ScreenConnect client proces
 * logs-windows.sysmon_operational-*
 * logs-system.security*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -37,8 +38,9 @@ Identifies suspicious processes being spawned by the ScreenConnect client proces
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 1
+*Version*: 103
 
 *Rule authors*: 
 
@@ -68,7 +70,7 @@ process where host.os.type == "windows" and event.type == "start" and
    (process.name : "rundll32.exe" and not process.args : "url.dll,FileProtocolHandler") or
    (process.name : "msiexec.exe" and process.args : ("/i", "-i") and
     process.args : ("/q", "/quiet", "/qn", "-q", "-quiet", "-qn", "-Q+")) or
-   process.name : ("mshta.exe", "certutil.exe", "bistadmin.exe", "certreq.exe", "wscript.exe", "cscript.exe", "curl.exe", 
+   process.name : ("mshta.exe", "certutil.exe", "bistadmin.exe", "certreq.exe", "wscript.exe", "cscript.exe", "curl.exe",
                    "ssh.exe", "scp.exe", "wevtutil.exe", "wget.exe", "wmic.exe")
    )
 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-service-was-installed-in-the-system.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-service-was-installed-in-the-system.asciidoc
index 7d5ebfb03b..8e9c1fd2c5 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-service-was-installed-in-the-system.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-service-was-installed-in-the-system.asciidoc
@@ -31,7 +31,7 @@ Identifies the creation of a new Windows service with suspicious Service command
 * Tactic: Persistence
 * Resources: Investigation Guide
 
-*Version*: 8
+*Version*: 9
 
 *Rule authors*: 
 
@@ -67,8 +67,8 @@ This rule looks for suspicious services being created with suspicious traits com
     - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
     - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
     - !{osquery{"label":"Osquery - Retrieve Service Unsigned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
-    - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
-    - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+    - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+    - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
   - Retrieve the referenced files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
 - Identify the user account that performed the action and whether it should perform this kind of action.
 - Contact the account owner and confirm whether they are aware of this activity.
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-web-browser-sensitive-file-access.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-web-browser-sensitive-file-access.asciidoc
index ebd52984fa..8ed62a862b 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-web-browser-sensitive-file-access.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-web-browser-sensitive-file-access.asciidoc
@@ -7,7 +7,7 @@ Identifies the access or file open of web browser sensitive files by an untruste
 
 *Rule indices*: 
 
-* logs-endpoint.events.file.*
+* logs-endpoint.events.file-*
 
 *Severity*: high
 
@@ -31,7 +31,7 @@ Identifies the access or file open of web browser sensitive files by an untruste
 * Tactic: Credential Access
 * Data Source: Elastic Defend
 
-*Version*: 207
+*Version*: 208
 
 *Rule authors*: 
 
@@ -82,7 +82,7 @@ For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/
 
 [source, js]
 ----------------------------------
-file where event.action == "open" and process.executable != null and 
+file where event.action == "open" and host.os.type == "macos" and process.executable != null and
  file.name : ("cookies.sqlite", 
               "key?.db", 
               "logins.json", 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-werfault-child-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-werfault-child-process.asciidoc
index fab2e0ddc2..e620e10b09 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-werfault-child-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-werfault-child-process.asciidoc
@@ -11,6 +11,7 @@ A suspicious WerFault child process was detected, which may indicate an attempt
 * logs-endpoint.events.process-*
 * logs-windows.*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -39,8 +40,9 @@ A suspicious WerFault child process was detected, which may indicate an attempt
 * Tactic: Privilege Escalation
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
+* Data Source: SentinelOne
 
-*Version*: 112
+*Version*: 214
 
 *Rule authors*: 
 
@@ -70,11 +72,11 @@ For more details on adding a custom ingest pipeline refer - https://www.elastic.
 ----------------------------------
 process where host.os.type == "windows" and event.type == "start" and
 
-  process.parent.name : "WerFault.exe" and 
-  
+  process.parent.name : "WerFault.exe" and
+
   /* args -s and -t used to execute a process via SilentProcessExit mechanism */
-  (process.parent.args : "-s" and process.parent.args : "-t" and process.parent.args : "-c") and 
-  
+  (process.parent.args : "-s" and process.parent.args : "-t" and process.parent.args : "-c") and
+
   not process.executable : ("?:\\Windows\\SysWOW64\\Initcrypt.exe", "?:\\Program Files (x86)\\Heimdal\\Heimdal.Guard.exe")
 
 ----------------------------------
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-which-enumeration.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-which-enumeration.asciidoc
index ca489c1a49..3eb95becdd 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-which-enumeration.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-which-enumeration.asciidoc
@@ -31,7 +31,7 @@ This rule monitors for the usage of the which command with an unusual amount of
 * Data Source: Elastic Defend
 * Data Source: Elastic Endgame
 
-*Version*: 5
+*Version*: 6
 
 *Rule authors*: 
 
@@ -52,7 +52,7 @@ not process.args == "--tty-only"
 /* potential tuning if rule would turn out to be noisy
 and process.args in ("nmap", "nc", "ncat", "netcat", nc.traditional", "gcc", "g++", "socat") and 
 process.parent.name in ("bash", "dash", "ash", "sh", "tcsh", "csh", "zsh", "ksh", "fish")
-*/ 
+*/
 
 ----------------------------------
 
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-host.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-host.asciidoc
index 0db42c7da2..fd5d099d4d 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-host.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-host.asciidoc
@@ -30,7 +30,7 @@ A machine learning job combination has detected a set of one or more suspicious
 * Rule Type: Machine Learning
 * Tactic: Defense Evasion
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -67,49 +67,8 @@ The LotL Attack Detection integration detects living-off-the-land activity in Wi
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
-- Under Settings, click Install Living off the Land Attack Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-**Before you can enable this rule**, you'll need to enrich Windows process events with predictions from the Supervised LotL Attack Detection model. This is done via the ingest pipeline named `<package_version>-problem_child_ingest_pipeline` installed with the LotL Attack Detection package.
-- If using an Elastic Beat such as Winlogbeat, add the LotL ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `winlogbeat.yml`.
-- If adding the LotL ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor]. For example, you can check if your winlogbeat or Elastic Defend (the https://docs.elastic.co/en/integrations/endpoint#logs[default index pattern] being `logs-endpoint*`) already has an ingest pipeline by navigating to `Data > Index Management`, finding the index (sometimes you need to toggle "Include hidden indices"), and checking the index's settings for a default or final https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#set-default-pipeline[pipeline].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the LotL ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "problemchild": {
-      "properties": {
-        "prediction": {
-          "type": "long"
-        },
-        "prediction_probability": {
-          "type": "float"
-        }
-      }
-    },
-    "blocklist_label": {
-      "type": "long"
-    }
-  }
-}
-```
-
-
-*Anomaly Detection Setup*
-
-**Before you can enable this rule**, you'll need to enable the corresponding Anomaly Detection job. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your enriched Windows process events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `winlogbeat-*` if you used Winlogbeat.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/problemchild/kibana/ml_module/problemchild-ml.json[this] configuration file, you will see a card for "Living off the Land Attack Detection" under "Use preconfigured jobs". Warning: if the ingest pipeline hasn't run for some reason, such as no eligible data in winlogbeat has come in yet, _you won't be able to see this card yet_. If that is the case, try troubleshooting the ingest pipeline, and if any ProblemChild predictions have been populated yet.
-- Keep the default settings and click "Create jobs" to start the anomaly detection job and datafeed.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-parent-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-parent-process.asciidoc
index 13bbf33559..9c0512cbe3 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-parent-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-parent-process.asciidoc
@@ -32,7 +32,7 @@ A machine learning job combination has detected a set of one or more suspicious
 * Rule Type: Machine Learning
 * Tactic: Defense Evasion
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -69,49 +69,8 @@ The LotL Attack Detection integration detects living-off-the-land activity in Wi
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
-- Under Settings, click Install Living off the Land Attack Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-**Before you can enable this rule**, you'll need to enrich Windows process events with predictions from the Supervised LotL Attack Detection model. This is done via the ingest pipeline named `<package_version>-problem_child_ingest_pipeline` installed with the LotL Attack Detection package.
-- If using an Elastic Beat such as Winlogbeat, add the LotL ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `winlogbeat.yml`.
-- If adding the LotL ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor]. For example, you can check if your winlogbeat or Elastic Defend (the https://docs.elastic.co/en/integrations/endpoint#logs[default index pattern] being `logs-endpoint*`) already has an ingest pipeline by navigating to `Data > Index Management`, finding the index (sometimes you need to toggle "Include hidden indices"), and checking the index's settings for a default or final https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#set-default-pipeline[pipeline].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the LotL ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "problemchild": {
-      "properties": {
-        "prediction": {
-          "type": "long"
-        },
-        "prediction_probability": {
-          "type": "float"
-        }
-      }
-    },
-    "blocklist_label": {
-      "type": "long"
-    }
-  }
-}
-```
-
-
-*Anomaly Detection Setup*
-
-**Before you can enable this rule**, you'll need to enable the corresponding Anomaly Detection job. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your enriched Windows process events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `winlogbeat-*` if you used Winlogbeat.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/problemchild/kibana/ml_module/problemchild-ml.json[this] configuration file, you will see a card for "Living off the Land Attack Detection" under "Use preconfigured jobs". Warning: if the ingest pipeline hasn't run for some reason, such as no eligible data in winlogbeat has come in yet, _you won't be able to see this card yet_. If that is the case, try troubleshooting the ingest pipeline, and if any ProblemChild predictions have been populated yet.
-- Keep the default settings and click "Create jobs" to start the anomaly detection job and datafeed.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-user.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-user.asciidoc
index 1bf58264d6..0a304bea75 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-user.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-windows-process-cluster-spawned-by-a-user.asciidoc
@@ -32,7 +32,7 @@ A machine learning job combination has detected a set of one or more suspicious
 * Rule Type: Machine Learning
 * Tactic: Defense Evasion
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -69,49 +69,8 @@ The LotL Attack Detection integration detects living-off-the-land activity in Wi
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
-- Under Settings, click Install Living off the Land Attack Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-**Before you can enable this rule**, you'll need to enrich Windows process events with predictions from the Supervised LotL Attack Detection model. This is done via the ingest pipeline named `<package_version>-problem_child_ingest_pipeline` installed with the LotL Attack Detection package.
-- If using an Elastic Beat such as Winlogbeat, add the LotL ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `winlogbeat.yml`.
-- If adding the LotL ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor]. For example, you can check if your winlogbeat or Elastic Defend (the https://docs.elastic.co/en/integrations/endpoint#logs[default index pattern] being `logs-endpoint*`) already has an ingest pipeline by navigating to `Data > Index Management`, finding the index (sometimes you need to toggle "Include hidden indices"), and checking the index's settings for a default or final https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#set-default-pipeline[pipeline].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the LotL ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "problemchild": {
-      "properties": {
-        "prediction": {
-          "type": "long"
-        },
-        "prediction_probability": {
-          "type": "float"
-        }
-      }
-    },
-    "blocklist_label": {
-      "type": "long"
-    }
-  }
-}
-```
-
-
-*Anomaly Detection Setup*
-
-**Before you can enable this rule**, you'll need to enable the corresponding Anomaly Detection job. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your enriched Windows process events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `winlogbeat-*` if you used Winlogbeat.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/problemchild/kibana/ml_module/problemchild-ml.json[this] configuration file, you will see a card for "Living off the Land Attack Detection" under "Use preconfigured jobs". Warning: if the ingest pipeline hasn't run for some reason, such as no eligible data in winlogbeat has come in yet, _you won't be able to see this card yet_. If that is the case, try troubleshooting the ingest pipeline, and if any ProblemChild predictions have been populated yet.
-- Keep the default settings and click "Create jobs" to start the anomaly detection job and datafeed.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/suspicious-zoom-child-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/suspicious-zoom-child-process.asciidoc
index a845f6af75..925241da9a 100644
--- a/docs/detections/prebuilt-rules/rule-details/suspicious-zoom-child-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/suspicious-zoom-child-process.asciidoc
@@ -12,6 +12,7 @@ A suspicious Zoom child process was detected, which may indicate an attempt to r
 * logs-windows.*
 * endgame-*
 * logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -35,8 +36,9 @@ A suspicious Zoom child process was detected, which may indicate an attempt to r
 * Data Source: Elastic Endgame
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
+* Data Source: SentinelOne
 
-*Version*: 110
+*Version*: 212
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/system-binary-copied-and-or-moved-to-suspicious-directory.asciidoc b/docs/detections/prebuilt-rules/rule-details/system-binary-copied-and-or-moved-to-suspicious-directory.asciidoc
index ded457a309..0d4793bf74 100644
--- a/docs/detections/prebuilt-rules/rule-details/system-binary-copied-and-or-moved-to-suspicious-directory.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/system-binary-copied-and-or-moved-to-suspicious-directory.asciidoc
@@ -29,7 +29,7 @@ This rule monitors for the copying or moving of a system binary to a suspicious
 * Tactic: Defense Evasion
 * Data Source: Elastic Defend
 
-*Version*: 7
+*Version*: 8
 
 *Rule authors*: 
 
@@ -117,10 +117,6 @@ sequence by host.id, process.entity_id with maxspan=1s
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Hide Artifacts
-** ID: T1564
-** Reference URL: https://attack.mitre.org/techniques/T1564/
-* Technique:
 ** Name: Masquerading
 ** ID: T1036
 ** Reference URL: https://attack.mitre.org/techniques/T1036/
@@ -128,3 +124,7 @@ sequence by host.id, process.entity_id with maxspan=1s
 ** Name: Rename System Utilities
 ** ID: T1036.003
 ** Reference URL: https://attack.mitre.org/techniques/T1036/003/
+* Technique:
+** Name: Hide Artifacts
+** ID: T1564
+** Reference URL: https://attack.mitre.org/techniques/T1564/
diff --git a/docs/detections/prebuilt-rules/rule-details/system-shells-via-services.asciidoc b/docs/detections/prebuilt-rules/rule-details/system-shells-via-services.asciidoc
index 79f8947f3c..97e8597a9b 100644
--- a/docs/detections/prebuilt-rules/rule-details/system-shells-via-services.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/system-shells-via-services.asciidoc
@@ -12,6 +12,7 @@ Windows services typically run as SYSTEM and can be used as a privilege escalati
 * logs-windows.*
 * endgame-*
 * logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -35,8 +36,9 @@ Windows services typically run as SYSTEM and can be used as a privilege escalati
 * Resources: Investigation Guide
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
+* Data Source: SentinelOne
 
-*Version*: 110
+*Version*: 212
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/systemd-service-started-by-unusual-parent-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/systemd-service-started-by-unusual-parent-process.asciidoc
new file mode 100644
index 0000000000..57bd3856d1
--- /dev/null
+++ b/docs/detections/prebuilt-rules/rule-details/systemd-service-started-by-unusual-parent-process.asciidoc
@@ -0,0 +1,217 @@
+[[systemd-service-started-by-unusual-parent-process]]
+=== Systemd Service Started by Unusual Parent Process
+
+Systemctl is a process used in Linux systems to manage systemd processes through service configuration files. Malicious actors can leverage systemd services to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection.
+
+*Rule type*: new_terms
+
+*Rule indices*: 
+
+* logs-endpoint.events.*
+
+*Severity*: medium
+
+*Risk score*: 47
+
+*Runs every*: 5m
+
+*Searches indices from*: now-9m ({ref}/common-options.html#date-math[Date Math format], see also <<rule-schedule, `Additional look-back time`>>)
+
+*Maximum alerts per execution*: 100
+
+*References*: 
+
+* https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/springtail-kimsuky-backdoor-espionage
+* https://pberba.github.io/security/2022/01/30/linux-threat-hunting-for-persistence-systemd-timers-cron/
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Tactic: Persistence
+* Tactic: Privilege Escalation
+* Data Source: Elastic Defend
+
+*Version*: 1
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Investigation guide
+
+
+
+*Triage and analysis*
+
+
+
+*Investigating Systemd Service Started by Unusual Parent Process*
+
+
+Systemd service files are configuration files in Linux systems used to define and manage systemd services.
+
+Malicious actors can leverage systemd service files to achieve persistence by creating or modifying service files to execute malicious commands or payloads during system startup. This allows them to maintain unauthorized access, execute additional malicious activities, or evade detection.
+
+This rule monitors the execution of the systemctl binary to start, enable or reenable a systemd service, potentially indicating the creation of a persistence mechanism.
+
+> **Note**:
+> This investigation guide uses the https://www.elastic.co/guide/en/security/master/invest-guide-run-osquery.html[Osquery Markdown Plugin] introduced in Elastic Stack version 8.5.0. Older Elastic Stack versions will display unrendered Markdown in this guide.
+> This investigation guide uses https://www.elastic.co/guide/en/security/current/osquery-placeholder-fields.html[placeholder fields] to dynamically pass alert data into Osquery queries. Placeholder fields were introduced in Elastic Stack version 8.7.0. If you're using Elastic Stack version 8.6.0 or earlier, you'll need to manually adjust this investigation guide's queries to ensure they properly run.
+
+
+*Possible Investigation Steps*
+
+
+- Investigate the currently enabled systemd services through the following command `sudo systemctl list-unit-files`.
+- Investigate whether any other files in any of the available systemd directories have been altered through OSQuery.
+  - !{osquery{"label":"Osquery - Retrieve File Listing Information","query":"SELECT * FROM file WHERE (\npath LIKE '/etc/systemd/system/%' OR \npath LIKE '/usr/local/lib/systemd/system/%' OR \npath LIKE '/lib/systemd/system/%' OR\npath LIKE '/usr/lib/systemd/system/%' OR\npath LIKE '/home/user/.config/systemd/user/%'\n)\n"}}
+  - !{osquery{"label":"Osquery - Retrieve Additional File Listing Information","query":"SELECT\n  f.path,\n  u.username AS file_owner,\n  g.groupname AS group_owner,\n  datetime(f.atime, 'unixepoch') AS file_last_access_time,\n  datetime(f.mtime, 'unixepoch') AS file_last_modified_time,\n  datetime(f.ctime, 'unixepoch') AS file_last_status_change_time,\n  datetime(f.btime, 'unixepoch') AS file_created_time,\n  f.size AS size_bytes\nFROM\n  file f\n  LEFT JOIN users u ON f.uid = u.uid\n  LEFT JOIN groups g ON f.gid = g.gid\nWHERE (\npath LIKE '/etc/systemd/system/%' OR \npath LIKE '/usr/local/lib/systemd/system/%' OR \npath LIKE '/lib/systemd/system/%' OR\npath LIKE '/usr/lib/systemd/system/%' OR\npath LIKE '/home/{{user.name}}/.config/systemd/user/%'\n)\n"}}
+- Investigate the script execution chain (parent process tree) for unknown processes. Examine their executable files for prevalence and whether they are located in expected locations.
+  - !{osquery{"label":"Osquery - Retrieve Running Processes by User","query":"SELECT pid, username, name FROM processes p JOIN users u ON u.uid = p.uid ORDER BY username"}}
+- Investigate other alerts associated with the user/host during the past 48 hours.
+- Validate the activity is not related to planned patches, updates, network administrator activity, or legitimate software installations.
+- Investigate whether the altered scripts call other malicious scripts elsewhere on the file system. 
+  - If scripts or executables were dropped, retrieve the files and determine if they are malicious:
+    - Use a private sandboxed malware analysis system to perform analysis.
+      - Observe and collect information about the following activities:
+        - Attempts to contact external domains and addresses.
+          - Check if the domain is newly registered or unexpected.
+          - Check the reputation of the domain or IP address.
+        - File access, modification, and creation activities.
+        - Cron jobs, services and other persistence mechanisms.
+            - !{osquery{"label":"Osquery - Retrieve Crontab Information","query":"SELECT * FROM crontab"}}
+- Investigate abnormal behaviors by the subject process/user such as network connections, file modifications, and any other spawned child processes.
+  - Investigate listening ports and open sockets to look for potential command and control traffic or data exfiltration.
+    - !{osquery{"label":"Osquery - Retrieve Listening Ports","query":"SELECT pid, address, port, socket, protocol, path FROM listening_ports"}}
+    - !{osquery{"label":"Osquery - Retrieve Open Sockets","query":"SELECT pid, family, remote_address, remote_port, socket, state FROM process_open_sockets"}}
+  - Identify the user account that performed the action, analyze it, and check whether it should perform this kind of action.
+    - !{osquery{"label":"Osquery - Retrieve Information for a Specific User","query":"SELECT * FROM users WHERE username = {{user.name}}"}}
+- Investigate whether the user is currently logged in and active.
+    - !{osquery{"label":"Osquery - Investigate the Account Authentication Status","query":"SELECT * FROM logged_in_users WHERE user = {{user.name}}"}}
+
+
+*False Positive Analysis*
+
+
+- If this activity is related to new benign software installation activity, consider adding exceptions — preferably with a combination of user and command line conditions.
+- If this activity is related to a system administrator who uses systemd services for administrative purposes, consider adding exceptions for this specific administrator user account. 
+- Try to understand the context of the execution by thinking about the user, machine, or business purpose. A small number of endpoints, such as servers with unique software, might appear unusual but satisfy a specific business need.
+
+
+*Related Rules*
+
+
+- New Systemd Service Created by Previously Unknown Process - 17b0a495-4d9f-414c-8ad0-92f018b8e001
+- Potential Persistence Through Run Control Detected - 0f4d35e4-925e-4959-ab24-911be207ee6f
+- Potential Persistence Through init.d Detected - 474fd20e-14cc-49c5-8160-d9ab4ba16c8b
+- New Systemd Timer Created - 7fb500fa-8e24-4bd1-9480-2a819352602c
+
+
+*Response and remediation*
+
+
+- Initiate the incident response process based on the outcome of the triage.
+- Isolate the involved host to prevent further post-compromise behavior.
+- If the triage identified malware, search the environment for additional compromised hosts.
+  - Implement temporary network rules, procedures, and segmentation to contain the malware.
+  - Stop suspicious processes.
+  - Immediately block the identified indicators of compromise (IoCs).
+  - Inspect the affected systems for additional malware backdoors like reverse shells, reverse proxies, or droppers that attackers could use to reinfect the system.
+- Investigate credential exposure on systems compromised or used by the attacker to ensure all compromised accounts are identified. Reset passwords for these accounts and other potentially compromised credentials, such as email, business systems, and web services.
+- Delete the service/timer or restore its original configuration.
+- Run a full antimalware scan. This may reveal additional artifacts left in the system, persistence mechanisms, and malware components.
+- Determine the initial vector abused by the attacker and take action to prevent reinfection through the same vector.
+- Leverage the incident response data and logging to improve the mean time to detect (MTTD) and the mean time to respond (MTTR).
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires data coming in from Elastic Defend.
+
+
+*Elastic Defend Integration Setup*
+
+Elastic Defend is integrated into the Elastic Agent using Fleet. Upon configuration, the integration allows the Elastic Agent to monitor events on your host and send data to the Elastic Security app.
+
+
+*Prerequisite Requirements:*
+
+- Fleet is required for Elastic Defend.
+- To configure Fleet Server refer to the https://www.elastic.co/guide/en/fleet/current/fleet-server.html[documentation].
+
+
+*The following steps should be executed in order to add the Elastic Defend integration on a Linux System:*
+
+- Go to the Kibana home page and click "Add integrations".
+- In the query bar, search for "Elastic Defend" and select the integration to see more details about it.
+- Click "Add Elastic Defend".
+- Configure the integration name and optionally add a description.
+- Select the type of environment you want to protect, either "Traditional Endpoints" or "Cloud Workloads".
+- Select a configuration preset. Each preset comes with different default settings for Elastic Agent, you can further customize these later by configuring the Elastic Defend integration policy. https://www.elastic.co/guide/en/security/current/configure-endpoint-integration-policy.html[Helper guide].
+- We suggest selecting "Complete EDR (Endpoint Detection and Response)" as a configuration setting, that provides "All events; all preventions"
+- Enter a name for the agent policy in "New agent policy name". If other agent policies already exist, you can click the "Existing hosts" tab and select an existing policy instead.
+For more details on Elastic Agent configuration settings, refer to the https://www.elastic.co/guide/en/fleet/8.10/agent-policy.html[helper guide].
+- Click "Save and Continue".
+- To complete the integration, select "Add Elastic Agent to your hosts" and continue to the next section to install the Elastic Agent on your hosts.
+For more details on Elastic Defend refer to the https://www.elastic.co/guide/en/security/current/install-endpoint.html[helper guide].
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+host.os.type:linux and event.category:process and event.type:start and event.action:exec and
+process.executable:/usr/bin/systemctl and process.args:(enable or reenable or start) and 
+process.entry_leader.entry_meta.type:* and
+not (
+  process.entry_leader.entry_meta.type:(container or init or unknown) or
+  process.parent.pid:1 or
+  process.parent.executable:(
+    /bin/adduser or /bin/dnf or /bin/dnf-automatic or /bin/dockerd or /bin/dpkg or /bin/microdnf or /bin/pacman or
+    /bin/podman or /bin/rpm or /bin/snapd or /bin/sudo or /bin/useradd or /bin/yum or /usr/bin/dnf or
+    /usr/bin/dnf-automatic or /usr/bin/dockerd or /usr/bin/dpkg or /usr/bin/microdnf or /usr/bin/pacman or
+    /usr/bin/podman or /usr/bin/rpm or /usr/bin/snapd or /usr/bin/sudo or /usr/bin/yum or /usr/sbin/adduser or
+    /usr/sbin/invoke-rc.d or /usr/sbin/useradd or /var/lib/dpkg/*
+  ) or
+  process.args_count >= 5
+)
+
+----------------------------------
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Persistence
+** ID: TA0003
+** Reference URL: https://attack.mitre.org/tactics/TA0003/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Systemd Service
+** ID: T1543.002
+** Reference URL: https://attack.mitre.org/techniques/T1543/002/
+* Tactic:
+** Name: Privilege Escalation
+** ID: TA0004
+** Reference URL: https://attack.mitre.org/tactics/TA0004/
+* Technique:
+** Name: Create or Modify System Process
+** ID: T1543
+** Reference URL: https://attack.mitre.org/techniques/T1543/
+* Sub-technique:
+** Name: Systemd Service
+** ID: T1543.002
+** Reference URL: https://attack.mitre.org/techniques/T1543/002/
diff --git a/docs/detections/prebuilt-rules/rule-details/third-party-backup-files-deleted-via-unexpected-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/third-party-backup-files-deleted-via-unexpected-process.asciidoc
index 2c61e00cf4..7ea0f109ae 100644
--- a/docs/detections/prebuilt-rules/rule-details/third-party-backup-files-deleted-via-unexpected-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/third-party-backup-files-deleted-via-unexpected-process.asciidoc
@@ -34,7 +34,7 @@ Identifies the deletion of backup files, saved using third-party software, by a
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 112
+*Version*: 113
 
 *Rule authors*: 
 
@@ -155,10 +155,10 @@ file where host.os.type == "windows" and event.type == "deletion" and
 ** ID: TA0040
 ** Reference URL: https://attack.mitre.org/tactics/TA0040/
 * Technique:
-** Name: Inhibit System Recovery
-** ID: T1490
-** Reference URL: https://attack.mitre.org/techniques/T1490/
-* Technique:
 ** Name: Data Destruction
 ** ID: T1485
 ** Reference URL: https://attack.mitre.org/techniques/T1485/
+* Technique:
+** Name: Inhibit System Recovery
+** ID: T1490
+** Reference URL: https://attack.mitre.org/techniques/T1490/
diff --git a/docs/detections/prebuilt-rules/rule-details/uac-bypass-attempt-via-windows-directory-masquerading.asciidoc b/docs/detections/prebuilt-rules/rule-details/uac-bypass-attempt-via-windows-directory-masquerading.asciidoc
index 78e817415f..8cd0cf9567 100644
--- a/docs/detections/prebuilt-rules/rule-details/uac-bypass-attempt-via-windows-directory-masquerading.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/uac-bypass-attempt-via-windows-directory-masquerading.asciidoc
@@ -38,7 +38,7 @@ Identifies an attempt to bypass User Account Control (UAC) by masquerading as a
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 
-*Version*: 112
+*Version*: 113
 
 *Rule authors*: 
 
@@ -157,14 +157,6 @@ process where host.os.type == "windows" and event.type == "start" and
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Abuse Elevation Control Mechanism
-** ID: T1548
-** Reference URL: https://attack.mitre.org/techniques/T1548/
-* Sub-technique:
-** Name: Bypass User Account Control
-** ID: T1548.002
-** Reference URL: https://attack.mitre.org/techniques/T1548/002/
-* Technique:
 ** Name: Masquerading
 ** ID: T1036
 ** Reference URL: https://attack.mitre.org/techniques/T1036/
@@ -172,3 +164,11 @@ process where host.os.type == "windows" and event.type == "start" and
 ** Name: Match Legitimate Name or Location
 ** ID: T1036.005
 ** Reference URL: https://attack.mitre.org/techniques/T1036/005/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Bypass User Account Control
+** ID: T1548.002
+** Reference URL: https://attack.mitre.org/techniques/T1548/002/
diff --git a/docs/detections/prebuilt-rules/rule-details/uac-bypass-via-windows-firewall-snap-in-hijack.asciidoc b/docs/detections/prebuilt-rules/rule-details/uac-bypass-via-windows-firewall-snap-in-hijack.asciidoc
index eef22f61fd..439c6a6692 100644
--- a/docs/detections/prebuilt-rules/rule-details/uac-bypass-via-windows-firewall-snap-in-hijack.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/uac-bypass-via-windows-firewall-snap-in-hijack.asciidoc
@@ -38,7 +38,7 @@ Identifies attempts to bypass User Account Control (UAC) by hijacking the Micros
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -160,14 +160,6 @@ process where host.os.type == "windows" and event.type == "start" and
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: Abuse Elevation Control Mechanism
-** ID: T1548
-** Reference URL: https://attack.mitre.org/techniques/T1548/
-* Sub-technique:
-** Name: Bypass User Account Control
-** ID: T1548.002
-** Reference URL: https://attack.mitre.org/techniques/T1548/002/
-* Technique:
 ** Name: System Binary Proxy Execution
 ** ID: T1218
 ** Reference URL: https://attack.mitre.org/techniques/T1218/
@@ -175,3 +167,11 @@ process where host.os.type == "windows" and event.type == "start" and
 ** Name: MMC
 ** ID: T1218.014
 ** Reference URL: https://attack.mitre.org/techniques/T1218/014/
+* Technique:
+** Name: Abuse Elevation Control Mechanism
+** ID: T1548
+** Reference URL: https://attack.mitre.org/techniques/T1548/
+* Sub-technique:
+** Name: Bypass User Account Control
+** ID: T1548.002
+** Reference URL: https://attack.mitre.org/techniques/T1548/002/
diff --git a/docs/detections/prebuilt-rules/rule-details/uncommon-registry-persistence-change.asciidoc b/docs/detections/prebuilt-rules/rule-details/uncommon-registry-persistence-change.asciidoc
index 6591ffc040..ab362877ea 100644
--- a/docs/detections/prebuilt-rules/rule-details/uncommon-registry-persistence-change.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/uncommon-registry-persistence-change.asciidoc
@@ -33,7 +33,7 @@ Detects changes to registry persistence keys that are not commonly used or modif
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 107
+*Version*: 108
 
 *Rule authors*: 
 
@@ -117,14 +117,6 @@ registry where host.os.type == "windows" and event.type in ("creation", "change"
 ** ID: TA0003
 ** Reference URL: https://attack.mitre.org/tactics/TA0003/
 * Technique:
-** Name: Boot or Logon Autostart Execution
-** ID: T1547
-** Reference URL: https://attack.mitre.org/techniques/T1547/
-* Sub-technique:
-** Name: Registry Run Keys / Startup Folder
-** ID: T1547.001
-** Reference URL: https://attack.mitre.org/techniques/T1547/001/
-* Technique:
 ** Name: Event Triggered Execution
 ** ID: T1546
 ** Reference URL: https://attack.mitre.org/techniques/T1546/
@@ -132,6 +124,14 @@ registry where host.os.type == "windows" and event.type in ("creation", "change"
 ** Name: Screensaver
 ** ID: T1546.002
 ** Reference URL: https://attack.mitre.org/techniques/T1546/002/
+* Technique:
+** Name: Boot or Logon Autostart Execution
+** ID: T1547
+** Reference URL: https://attack.mitre.org/techniques/T1547/
+* Sub-technique:
+** Name: Registry Run Keys / Startup Folder
+** ID: T1547.001
+** Reference URL: https://attack.mitre.org/techniques/T1547/001/
 * Tactic:
 ** Name: Defense Evasion
 ** ID: TA0005
diff --git a/docs/detections/prebuilt-rules/rule-details/unsigned-bits-service-client-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/unsigned-bits-service-client-process.asciidoc
index d003a3224a..0e65d3f3c5 100644
--- a/docs/detections/prebuilt-rules/rule-details/unsigned-bits-service-client-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unsigned-bits-service-client-process.asciidoc
@@ -33,7 +33,7 @@ Identifies an unsigned Windows Background Intelligent Transfer Service (BITS) cl
 * Rule Type: BBR
 * Data Source: Elastic Defend
 
-*Version*: 2
+*Version*: 3
 
 *Rule authors*: 
 
@@ -60,10 +60,6 @@ not process.code_signature.status : ("errorExpired", "errorCode_endpoint*")
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
-** Name: BITS Jobs
-** ID: T1197
-** Reference URL: https://attack.mitre.org/techniques/T1197/
-* Technique:
 ** Name: Masquerading
 ** ID: T1036
 ** Reference URL: https://attack.mitre.org/techniques/T1036/
@@ -71,3 +67,7 @@ not process.code_signature.status : ("errorExpired", "errorCode_endpoint*")
 ** Name: Invalid Code Signature
 ** ID: T1036.001
 ** Reference URL: https://attack.mitre.org/techniques/T1036/001/
+* Technique:
+** Name: BITS Jobs
+** ID: T1197
+** Reference URL: https://attack.mitre.org/techniques/T1197/
diff --git a/docs/detections/prebuilt-rules/rule-details/untrusted-driver-loaded.asciidoc b/docs/detections/prebuilt-rules/rule-details/untrusted-driver-loaded.asciidoc
index 004c4a4e1d..96fce92607 100644
--- a/docs/detections/prebuilt-rules/rule-details/untrusted-driver-loaded.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/untrusted-driver-loaded.asciidoc
@@ -33,7 +33,7 @@ Identifies attempt to load an untrusted driver. Adversaries may modify code sign
 * Resources: Investigation Guide
 * Data Source: Elastic Defend
 
-*Version*: 8
+*Version*: 9
 
 *Rule authors*: 
 
@@ -76,8 +76,8 @@ This rule identifies an attempt to load an untrusted driver, which effectively m
 - Investigate other alerts associated with the user/host during the past 48 hours.
 - Assess whether this behavior is prevalent in the environment by looking for similar occurrences across hosts.
 - Use Osquery to investigate the drivers loaded into the system.
-  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
-  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image, issuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image = authenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Non-Microsoft Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE NOT (provider == \"Microsoft\" AND signed == \"1\")\n"}}
+  - !{osquery{"label":"Osquery - Retrieve All Unsigned Drivers with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, class, description, directory, image,\nissuer_name, manufacturer, service, signed, subject_name FROM drivers JOIN authenticode ON drivers.image =\nauthenticode.path JOIN hash ON drivers.image = hash.path WHERE signed == \"0\"\n"}}
 - Identify the driver's `Device Name` and `Service Name`.
 - Check for alerts from the rules specified in the `Related Rules` section.
 
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-network-activity-from-a-windows-system-binary.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-network-activity-from-a-windows-system-binary.asciidoc
index 8db3083bb2..8c92ad3b53 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-network-activity-from-a-windows-system-binary.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-network-activity-from-a-windows-system-binary.asciidoc
@@ -34,7 +34,7 @@ Identifies network activity from unexpected system applications. This may indica
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -183,6 +183,14 @@ sequence by process.entity_id with maxspan=5m
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
+** Name: Masquerading
+** ID: T1036
+** Reference URL: https://attack.mitre.org/techniques/T1036/
+* Sub-technique:
+** Name: Match Legitimate Name or Location
+** ID: T1036.005
+** Reference URL: https://attack.mitre.org/techniques/T1036/005/
+* Technique:
 ** Name: Trusted Developer Utilities Proxy Execution
 ** ID: T1127
 ** Reference URL: https://attack.mitre.org/techniques/T1127/
@@ -194,11 +202,3 @@ sequence by process.entity_id with maxspan=5m
 ** Name: Mshta
 ** ID: T1218.005
 ** Reference URL: https://attack.mitre.org/techniques/T1218/005/
-* Technique:
-** Name: Masquerading
-** ID: T1036
-** Reference URL: https://attack.mitre.org/techniques/T1036/
-* Sub-technique:
-** Name: Match Legitimate Name or Location
-** ID: T1036.005
-** Reference URL: https://attack.mitre.org/techniques/T1036/005/
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-parent-process-for-cmd-exe.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-parent-process-for-cmd-exe.asciidoc
index 5e236d32b9..14edbfbe16 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-parent-process-for-cmd-exe.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-parent-process-for-cmd-exe.asciidoc
@@ -11,6 +11,7 @@ Identifies a suspicious parent child process relationship with cmd.exe descendin
 * logs-endpoint.events.process-*
 * logs-windows.sysmon_operational-*
 * endgame-*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: medium
 
@@ -33,8 +34,9 @@ Identifies a suspicious parent child process relationship with cmd.exe descendin
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
 * Data Source: Sysmon
+* Data Source: SentinelOne
 
-*Version*: 110
+*Version*: 212
 
 *Rule authors*: 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-process-for-a-windows-host.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-process-for-a-windows-host.asciidoc
index 37b22f35ca..d7ca931b2d 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-process-for-a-windows-host.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-process-for-a-windows-host.asciidoc
@@ -31,7 +31,7 @@ Identifies rare processes that do not usually run on individual hosts, which can
 * Tactic: Persistence
 * Resources: Investigation Guide
 
-*Version*: 107
+*Version*: 108
 
 *Rule authors*: 
 
@@ -80,8 +80,8 @@ This rule uses a machine learning job to detect a Windows process that is rare a
     - Use the Elastic Defend registry events to examine registry keys accessed, modified, or created by the related processes in the process tree.
     - Examine the host services for suspicious or anomalous entries.
       - !{osquery{"label":"Osquery - Retrieve All Services","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services"}}
-      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE NOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR user_account == null)"}}
-      - !{osquery{"label":"Retrieve Service Unisgned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid, services.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path = authenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'"}}
+      - !{osquery{"label":"Osquery - Retrieve Services Running on User Accounts","query":"SELECT description, display_name, name, path, pid, service_type, start_type, status, user_account FROM services WHERE\nNOT (user_account LIKE '%LocalSystem' OR user_account LIKE '%LocalService' OR user_account LIKE '%NetworkService' OR\nuser_account == null)\n"}}
+      - !{osquery{"label":"Retrieve Service Unisgned Executables with Virustotal Link","query":"SELECT concat('https://www.virustotal.com/gui/file/', sha1) AS VtLink, name, description, start_type, status, pid,\nservices.path FROM services JOIN authenticode ON services.path = authenticode.path OR services.module_path =\nauthenticode.path JOIN hash ON services.path = hash.path WHERE authenticode.result != 'trusted'\n"}}
   - Retrieve the files' SHA-256 hash values using the PowerShell `Get-FileHash` cmdlet and search for the existence and reputation of the hashes in resources like VirusTotal, Hybrid-Analysis, CISCO Talos, Any.run, etc.
 
 
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-host.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-host.asciidoc
index 9cf101a7bb..d578ddf15b 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-host.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-host.asciidoc
@@ -32,7 +32,7 @@ A machine learning job has detected a suspicious Windows process. This process h
 * Rule Type: Machine Learning
 * Tactic: Defense Evasion
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -69,49 +69,8 @@ The LotL Attack Detection integration detects living-off-the-land activity in Wi
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
-- Under Settings, click Install Living off the Land Attack Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-**Before you can enable this rule**, you'll need to enrich Windows process events with predictions from the Supervised LotL Attack Detection model. This is done via the ingest pipeline named `<package_version>-problem_child_ingest_pipeline` installed with the LotL Attack Detection package.
-- If using an Elastic Beat such as Winlogbeat, add the LotL ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `winlogbeat.yml`.
-- If adding the LotL ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor]. For example, you can check if your winlogbeat or Elastic Defend (the https://docs.elastic.co/en/integrations/endpoint#logs[default index pattern] being `logs-endpoint*`) already has an ingest pipeline by navigating to `Data > Index Management`, finding the index (sometimes you need to toggle "Include hidden indices"), and checking the index's settings for a default or final https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#set-default-pipeline[pipeline].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the LotL ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "problemchild": {
-      "properties": {
-        "prediction": {
-          "type": "long"
-        },
-        "prediction_probability": {
-          "type": "float"
-        }
-      }
-    },
-    "blocklist_label": {
-      "type": "long"
-    }
-  }
-}
-```
-
-
-*Anomaly Detection Setup*
-
-**Before you can enable this rule**, you'll need to enable the corresponding Anomaly Detection job. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your enriched Windows process events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `winlogbeat-*` if you used Winlogbeat.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/problemchild/kibana/ml_module/problemchild-ml.json[this] configuration file, you will see a card for "Living off the Land Attack Detection" under "Use preconfigured jobs". Warning: If the ingest pipeline hasn't run for some reason, such as no eligible data in winlogbeat has come in yet, _you won't be able to see this card yet_. If that is the case, try troubleshooting the ingest pipeline, and check whether any ProblemChild predictions have been generated.
-- Keep the default settings and click "Create jobs" to start the anomaly detection job and datafeed.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-parent-process.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-parent-process.asciidoc
index f1e30e1027..9ec9fd12f4 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-parent-process.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-parent-process.asciidoc
@@ -32,7 +32,7 @@ A machine learning job has detected a suspicious Windows process. This process h
 * Rule Type: Machine Learning
 * Tactic: Defense Evasion
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -69,49 +69,8 @@ The LotL Attack Detection integration detects living-off-the-land activity in Wi
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
-- Under Settings, click Install Living off the Land Attack Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-**Before you can enable this rule**, you'll need to enrich Windows process events with predictions from the Supervised LotL Attack Detection model. This is done via the ingest pipeline named `<package_version>-problem_child_ingest_pipeline` installed with the LotL Attack Detection package.
-- If using an Elastic Beat such as Winlogbeat, add the LotL ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `winlogbeat.yml`.
-- If adding the LotL ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor]. For example, you can check if your winlogbeat or Elastic Defend (the https://docs.elastic.co/en/integrations/endpoint#logs[default index pattern] being `logs-endpoint*`) already has an ingest pipeline by navigating to `Data > Index Management`, finding the index (sometimes you need to toggle "Include hidden indices"), and checking the index's settings for a default or final https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#set-default-pipeline[pipeline].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the LotL ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "problemchild": {
-      "properties": {
-        "prediction": {
-          "type": "long"
-        },
-        "prediction_probability": {
-          "type": "float"
-        }
-      }
-    },
-    "blocklist_label": {
-      "type": "long"
-    }
-  }
-}
-```
-
-
-*Anomaly Detection Setup*
-
-**Before you can enable this rule**, you'll need to enable the corresponding Anomaly Detection job. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your enriched Windows process events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `winlogbeat-*` if you used Winlogbeat.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/problemchild/kibana/ml_module/problemchild-ml.json[this] configuration file, you will see a card for "Living off the Land Attack Detection" under "Use preconfigured jobs". Warning: if the ingest pipeline hasn't run for some reason, such as no eligible data in winlogbeat has come in yet, _you won't be able to see this card yet_. If that is the case, try troubleshooting the ingest pipeline, and if any ProblemChild predictions have been populated yet.
-- Keep the default settings and click "Create jobs" to start the anomaly detection job and datafeed.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-user.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-user.asciidoc
index fceae7405f..5ee8c1297d 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-user.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-process-spawned-by-a-user.asciidoc
@@ -32,7 +32,7 @@ A machine learning job has detected a suspicious Windows process. This process h
 * Rule Type: Machine Learning
 * Tactic: Defense Evasion
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -69,49 +69,8 @@ The LotL Attack Detection integration detects living-off-the-land activity in Wi
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Living off the Land Attack Detection and select the integration to see more details about it.
-- Under Settings, click Install Living off the Land Attack Detection assets and follow the prompts to install the assets.
-
-
-*Ingest Pipeline Setup*
-
-**Before you can enable this rule**, you'll need to enrich Windows process events with predictions from the Supervised LotL Attack Detection model. This is done via the ingest pipeline named `<package_version>-problem_child_ingest_pipeline` installed with the LotL Attack Detection package.
-- If using an Elastic Beat such as Winlogbeat, add the LotL ingest pipeline to it by adding a simple configuration https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#pipelines-for-beats[setting] to `winlogbeat.yml`.
-- If adding the LotL ingest pipeline to an existing pipeline, use a https://www.elastic.co/guide/en/elasticsearch/reference/current/pipeline-processor.html[pipeline processor]. For example, you can check if your winlogbeat or Elastic Defend (the https://docs.elastic.co/en/integrations/endpoint#logs[default index pattern] being `logs-endpoint*`) already has an ingest pipeline by navigating to `Data > Index Management`, finding the index (sometimes you need to toggle "Include hidden indices"), and checking the index's settings for a default or final https://www.elastic.co/guide/en/elasticsearch/reference/current/ingest.html#set-default-pipeline[pipeline].
-
-
-*Adding Custom Mappings*
-
-- Go to the Kibana homepage. Under Management, click Stack Management.
-- Under Data click Index Management and navigate to the Component Templates tab.
-- Templates that can be edited to add custom components will be marked with a @custom suffix. Edit the @custom component template corresponding to the beat/integration you added the LotL ingest pipeline to, by pasting the following JSON blob in the "Load JSON" flyout:
-```
-{
-  "properties": {
-    "problemchild": {
-      "properties": {
-        "prediction": {
-          "type": "long"
-        },
-        "prediction_probability": {
-          "type": "float"
-        }
-      }
-    },
-    "blocklist_label": {
-      "type": "long"
-    }
-  }
-}
-```
-
-
-*Anomaly Detection Setup*
-
-**Before you can enable this rule**, you'll need to enable the corresponding Anomaly Detection job. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your enriched Windows process events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events, or `winlogbeat-*` if you used Winlogbeat.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/problemchild/kibana/ml_module/problemchild-ml.json[this] configuration file, you will see a card for "Living off the Land Attack Detection" under "Use preconfigured jobs". Warning: if the ingest pipeline hasn't run for some reason, such as no eligible data in winlogbeat has come in yet, _you won't be able to see this card yet_. If that is the case, try troubleshooting the ingest pipeline, and if any ProblemChild predictions have been populated yet.
-- Keep the default settings and click "Create jobs" to start the anomaly detection job and datafeed.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-process-writing-data-to-an-external-device.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-process-writing-data-to-an-external-device.asciidoc
index 41e6916ac9..3aba30b6f3 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-process-writing-data-to-an-external-device.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-process-writing-data-to-an-external-device.asciidoc
@@ -30,7 +30,7 @@ A machine learning job has detected a rare process writing data to an external d
 * Rule Type: Machine Learning
 * Tactic: Exfiltration
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -66,16 +66,8 @@ The Data Exfiltration Detection integration detects data exfiltration activity b
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Data Exfiltration Detection and select the integration to see more details about it.
-- Under Settings, click Install Data Exfiltration Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Data Exfiltration Detection, you'll need to enable the corresponding Anomaly Detection jobs. 
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your file events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/ded/kibana/ml_module/ded-ml.json[this] configuration file, you will see a card for Data Exfiltration Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-directory.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-directory.asciidoc
index a0b2eeb859..8dd0283f08 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-directory.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-directory.asciidoc
@@ -31,7 +31,7 @@ An anomaly detection job has detected a remote file transfer on an unusual direc
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,16 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your file events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-extension.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-extension.asciidoc
index 88a4466443..57234aaf91 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-extension.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-extension.asciidoc
@@ -31,7 +31,7 @@ An anomaly detection job has detected a remote file transfer with a rare extensi
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,16 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your file events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-size.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-size.asciidoc
index f60c100148..fc435ff920 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-size.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-remote-file-size.asciidoc
@@ -31,7 +31,7 @@ A machine learning job has detected an unusually high file size shared by a remo
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,16 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your file events. For example, this would be `logs-endpoint.events.*` if you used Elastic Defend to collect events.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/unusual-time-or-day-for-an-rdp-session.asciidoc b/docs/detections/prebuilt-rules/rule-details/unusual-time-or-day-for-an-rdp-session.asciidoc
index 18300933e4..651e1d61a7 100644
--- a/docs/detections/prebuilt-rules/rule-details/unusual-time-or-day-for-an-rdp-session.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/unusual-time-or-day-for-an-rdp-session.asciidoc
@@ -31,7 +31,7 @@ A machine learning job has detected an RDP session started at an usual time or w
 * Rule Type: Machine Learning
 * Tactic: Lateral Movement
 
-*Version*: 3
+*Version*: 4
 
 *Rule authors*: 
 
@@ -67,17 +67,8 @@ The Lateral Movement Detection integration detects lateral movement activity by
 
 - Go to the Kibana homepage. Under Management, click Integrations.
 - In the query bar, search for Lateral Movement Detection and select the integration to see more details about it.
-- Under Settings, click Install Lateral Movement Detection assets and follow the prompts to install the assets.
-
-
-*Anomaly Detection Setup*
-
-Before you can enable rules for Lateral Movement Detection, you'll need to enable the corresponding Anomaly Detection jobs.
-- Before enabling the Anomaly Detection jobs, confirm that the Pivot Transform asset is installed and actively gathering data in the destination index `ml-rdp-lmd`.
-- Go to the Kibana homepage. Under Analytics, click Machine Learning.
-- Under Anomaly Detection, click Jobs, and then click "Create job". Select the Data View containing your transformed RDP process data i.e.`ml-rdp-lmd`.
-- If the selected Data View contains events that match the query in https://github.com/elastic/integrations/blob/main/packages/lmd/kibana/ml_module/lmd-ml.json[this] configuration file, you will see a card for Lateral Movement Detection under "Use preconfigured jobs".
-- Keep the default settings and click "Create jobs" to start the anomaly detection jobs and datafeeds.
+- Follow the instructions under the **Installation** section.
+- For this rule to work, complete the instructions through **Add preconfigured anomaly detection jobs**.
 
 
 *Framework*: MITRE ATT&CK^TM^
diff --git a/docs/detections/prebuilt-rules/rule-details/web-shell-detection-script-process-child-of-common-web-processes.asciidoc b/docs/detections/prebuilt-rules/rule-details/web-shell-detection-script-process-child-of-common-web-processes.asciidoc
index d600c233e3..11b4679508 100644
--- a/docs/detections/prebuilt-rules/rule-details/web-shell-detection-script-process-child-of-common-web-processes.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/web-shell-detection-script-process-child-of-common-web-processes.asciidoc
@@ -12,6 +12,7 @@ Identifies suspicious commands executed via a web server, which may suggest a vu
 * logs-windows.*
 * endgame-*
 * logs-system.security*
+* logs-sentinel_one_cloud_funnel.*
 
 *Severity*: high
 
@@ -40,8 +41,9 @@ Identifies suspicious commands executed via a web server, which may suggest a vu
 * Resources: Investigation Guide
 * Data Source: Elastic Endgame
 * Data Source: Elastic Defend
+* Data Source: SentinelOne
 
-*Version*: 111
+*Version*: 213
 
 *Rule authors*: 
 
@@ -129,7 +131,7 @@ For more details on adding a custom ingest pipeline refer - https://www.elastic.
 process where host.os.type == "windows" and event.type == "start" and
   process.parent.name : ("w3wp.exe", "httpd.exe", "nginx.exe", "php.exe", "php-cgi.exe", "tomcat.exe") and
   process.name : ("cmd.exe", "cscript.exe", "powershell.exe", "pwsh.exe", "powershell_ise.exe", "wmic.exe", "wscript.exe") and
-  not 
+  not
   (
     process.parent.name : ("php.exe", "httpd.exe") and process.name : "cmd.exe" and
     process.command_line : (
diff --git a/docs/detections/prebuilt-rules/rule-details/windows-account-or-group-discovery.asciidoc b/docs/detections/prebuilt-rules/rule-details/windows-account-or-group-discovery.asciidoc
index 04b37e51c1..52238508c4 100644
--- a/docs/detections/prebuilt-rules/rule-details/windows-account-or-group-discovery.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/windows-account-or-group-discovery.asciidoc
@@ -30,7 +30,7 @@ This rule identifies the execution of commands that enumerates account or group
 * Rule Type: BBR
 * Data Source: Elastic Defend
 
-*Version*: 4
+*Version*: 5
 
 *Rule authors*: 
 
@@ -93,10 +93,6 @@ and not process.parent.name : "LTSVC.exe" and not user.id : "S-1-5-18"
 ** ID: T1069.002
 ** Reference URL: https://attack.mitre.org/techniques/T1069/002/
 * Technique:
-** Name: Password Policy Discovery
-** ID: T1201
-** Reference URL: https://attack.mitre.org/techniques/T1201/
-* Technique:
 ** Name: Account Discovery
 ** ID: T1087
 ** Reference URL: https://attack.mitre.org/techniques/T1087/
@@ -108,3 +104,7 @@ and not process.parent.name : "LTSVC.exe" and not user.id : "S-1-5-18"
 ** Name: Domain Account
 ** ID: T1087.002
 ** Reference URL: https://attack.mitre.org/techniques/T1087/002/
+* Technique:
+** Name: Password Policy Discovery
+** ID: T1201
+** Reference URL: https://attack.mitre.org/techniques/T1201/
diff --git a/docs/detections/prebuilt-rules/rule-details/windows-defender-disabled-via-registry-modification.asciidoc b/docs/detections/prebuilt-rules/rule-details/windows-defender-disabled-via-registry-modification.asciidoc
index 708a69a255..52fc820ac1 100644
--- a/docs/detections/prebuilt-rules/rule-details/windows-defender-disabled-via-registry-modification.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/windows-defender-disabled-via-registry-modification.asciidoc
@@ -36,7 +36,7 @@ Identifies modifications to the Windows Defender registry settings to disable th
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 111
+*Version*: 112
 
 *Rule authors*: 
 
@@ -153,6 +153,10 @@ registry where host.os.type == "windows" and event.type in ("creation", "change"
 ** ID: TA0005
 ** Reference URL: https://attack.mitre.org/tactics/TA0005/
 * Technique:
+** Name: Modify Registry
+** ID: T1112
+** Reference URL: https://attack.mitre.org/techniques/T1112/
+* Technique:
 ** Name: Impair Defenses
 ** ID: T1562
 ** Reference URL: https://attack.mitre.org/techniques/T1562/
@@ -164,7 +168,3 @@ registry where host.os.type == "windows" and event.type in ("creation", "change"
 ** Name: Indicator Blocking
 ** ID: T1562.006
 ** Reference URL: https://attack.mitre.org/techniques/T1562/006/
-* Technique:
-** Name: Modify Registry
-** ID: T1112
-** Reference URL: https://attack.mitre.org/techniques/T1112/
diff --git a/docs/detections/prebuilt-rules/rule-details/windows-script-interpreter-executing-process-via-wmi.asciidoc b/docs/detections/prebuilt-rules/rule-details/windows-script-interpreter-executing-process-via-wmi.asciidoc
index 75dcbd180f..86ed465ad8 100644
--- a/docs/detections/prebuilt-rules/rule-details/windows-script-interpreter-executing-process-via-wmi.asciidoc
+++ b/docs/detections/prebuilt-rules/rule-details/windows-script-interpreter-executing-process-via-wmi.asciidoc
@@ -36,7 +36,7 @@ Identifies use of the built-in Windows script interpreters (cscript.exe or wscri
 * Data Source: Elastic Defend
 * Data Source: Sysmon
 
-*Version*: 109
+*Version*: 110
 
 *Rule authors*: 
 
@@ -101,6 +101,10 @@ sequence by host.id with maxspan = 5s
 ** ID: TA0002
 ** Reference URL: https://attack.mitre.org/tactics/TA0002/
 * Technique:
+** Name: Windows Management Instrumentation
+** ID: T1047
+** Reference URL: https://attack.mitre.org/techniques/T1047/
+* Technique:
 ** Name: Command and Scripting Interpreter
 ** ID: T1059
 ** Reference URL: https://attack.mitre.org/techniques/T1059/
@@ -108,7 +112,3 @@ sequence by host.id with maxspan = 5s
 ** Name: Visual Basic
 ** ID: T1059.005
 ** Reference URL: https://attack.mitre.org/techniques/T1059/005/
-* Technique:
-** Name: Windows Management Instrumentation
-** ID: T1047
-** Reference URL: https://attack.mitre.org/techniques/T1047/
diff --git a/docs/index.asciidoc b/docs/index.asciidoc
index 4d30f4b4da..78c24e50be 100644
--- a/docs/index.asciidoc
+++ b/docs/index.asciidoc
@@ -117,3 +117,5 @@ include::detections/prebuilt-rules/downloadable-packages/8-11-14/prebuilt-rules-
 include::detections/prebuilt-rules/downloadable-packages/8-11-15/prebuilt-rules-8-11-15-appendix.asciidoc[]
 
 include::detections/prebuilt-rules/downloadable-packages/8-11-16/prebuilt-rules-8-11-16-appendix.asciidoc[]
+
+include::detections/prebuilt-rules/downloadable-packages/8-11-17/prebuilt-rules-8-11-17-appendix.asciidoc[]