Merge branch '8.14' into mergify/bp/8.14/pr-5360

docs/AI-for-security/ai-for-security.asciidoc

@@ -0,0 +1,24 @@
+[[ai-for-security]]
+= AI for security
+
+:frontmatter-description: Learn to use AI capabilities in {elastic-sec}.
+:frontmatter-tags-products: [security]
+:frontmatter-tags-content-type: [overview]
+:frontmatter-tags-user-goals: [get-started]
+
+You can use {elastic-sec}'s built-in AI tools to speed up your work and augment your team's capabilities. The pages in this section describe <<security-assistant, AI Assistant>>, which answers questions and enhances your workflows throughout {elastic-sec}, and <<attack-discovery, Attack discovery>>, which speeds up the triage process by finding patterns and identifying attacks spanning multiple alerts.
+
+include::security-assistant.asciidoc[leveloffset=+1]
+include::attack-discovery.asciidoc[leveloffset=+1]
+
+include::llm-connector-guides.asciidoc[leveloffset=+1]
+include::azure-openai-setup.asciidoc[leveloffset=+2]
+include::connect-to-bedrock.asciidoc[leveloffset=+2]
+include::connect-to-openai.asciidoc[leveloffset=+2]
+
+include::ai-use-cases.asciidoc[leveloffset=+1]
+include::ai-alert-triage.asciidoc[leveloffset=+2]
+include::use-attack-discovery-ai-assistant-incident-reporting.asciidoc[leveloffset=+2]
+include::ai-esql-queries.asciidoc[leveloffset=+2]
+
+include::llm-performance-matrix.asciidoc[leveloffset=+1]

docs/AI-for-security/ai-use-cases.asciidoc

@@ -0,0 +1,10 @@
+[[assistant-use-cases]]
+= Use cases
+
+The guides in this section describe use cases for AI Assistant and Attack discovery. Refer to them for examples of each tool's individual capabilities and of what they can do together.
+
+* <<assistant-triage>>
+* <<attack-discovery-ai-assistant-incident-reporting>>
+* <<esql-queries-assistant>>
+
+For general information, refer to <<security-assistant, AI Assistant>> or <<attack-discovery, Attack discovery>>.

docs/assistant/security-assistant.asciidoc → docs/AI-for-security/security-assistant.asciidoc

@@ -189,14 +189,3 @@ In addition to practical advice, AI Assistant can offer conceptual advice, tips,
 * “I need to monitor for unusual file creation patterns that could indicate ransomware activity. How would I construct this query using EQL?”
 
 
-include::assistant-use-cases.asciidoc[leveloffset=+1]
-include::ai-alert-triage.asciidoc[leveloffset=+2]
-include::use-attack-discovery-ai-assistant-incident-reporting.asciidoc[leveloffset=+2]
-include::ai-esql-queries.asciidoc[leveloffset=+2]
-
-include::llm-connector-guides.asciidoc[leveloffset=+1]
-include::azure-openai-setup.asciidoc[leveloffset=+2]
-include::connect-to-openai.asciidoc[leveloffset=+2]
-include::connect-to-bedrock.asciidoc[leveloffset=+2]
-
-include::llm-performance-matrix.asciidoc[leveloffset=+1]

docs/detections/prebuilt-rules/downloadable-packages/8-14-4/prebuilt-rule-8-14-4-agent-spoofing-multiple-hosts-using-same-agent.asciidoc

@@ -0,0 +1,58 @@
+[[prebuilt-rule-8-14-4-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.
+
+*Rule type*: threshold
+
+*Rule indices*: 
+
+* logs-*
+* metrics-*
+* traces-*
+
+*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*: 
+
+* Use Case: Threat Detection
+* Tactic: Defense Evasion
+
+*Version*: 102
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Rule query
+
+
+[source, js]
+----------------------------------
+event.agent_id_status:* and not tags:forwarded
+
+----------------------------------
+
+*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/

docs/detections/prebuilt-rules/downloadable-packages/8-14-4/prebuilt-rule-8-14-4-anomalous-linux-compiler-activity.asciidoc

@@ -0,0 +1,123 @@
+[[prebuilt-rule-8-14-4-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.
+
+*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*: None
+
+*Tags*: 
+
+* Domain: Endpoint
+* OS: Linux
+* Use Case: Threat Detection
+* Rule Type: ML
+* Rule Type: Machine Learning
+* Tactic: Resource Development
+
+*Version*: 104
+
+*Rule authors*: 
+
+* Elastic
+
+*Rule license*: Elastic License v2
+
+
+==== Setup
+
+
+
+*Setup*
+
+
+This rule requires the installation of associated Machine Learning jobs, as well as data coming in from one of the following integrations:
+- Elastic Defend
+- Auditd Manager
+
+
+*Anomaly Detection Setup*
+
+
+Once the rule is enabled, the associated Machine Learning job will start automatically. You can view the Machine Learning job linked under the "Definition" panel of the detection rule. If the job does not start due to an error, the issue must be resolved for the job to commence successfully. For more details on setting up anomaly detection jobs, refer to the https://www.elastic.co/guide/en/kibana/current/xpack-ml-anomalies.html[helper guide].
+
+
+*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 to your 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/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].
+
+
+*Auditd Manager Integration Setup*
+
+The Auditd Manager Integration receives audit events from the Linux Audit Framework which is a part of the Linux kernel.
+Auditd Manager provides a user-friendly interface and automation capabilities for configuring and monitoring system auditing through the auditd daemon. With `auditd_manager`, administrators can easily define audit rules, track system events, and generate comprehensive audit reports, improving overall security and compliance in the system.
+
+
+*The following steps should be executed in order to add the Elastic Agent System integration "auditd_manager" to your system:*
+
+- Go to the Kibana home page and click “Add integrations”.
+- In the query bar, search for “Auditd Manager” and select the integration to see more details about it.
+- Click “Add Auditd Manager”.
+- Configure the integration name and optionally add a description.
+- Review optional and advanced settings accordingly.
+- Add the newly installed “auditd manager” to an existing or a new agent policy, and deploy the agent on a Linux system from which auditd log files are desirable.
+- Click “Save and Continue”.
+- For more details on the integration refer to the https://docs.elastic.co/integrations/auditd_manager[helper guide].
+
+
+*Rule Specific Setup Note*
+
+Auditd Manager subscribes to the kernel and receives events as they occur without any additional configuration.
+However, if more advanced configuration is required to detect specific behavior, audit rules can be added to the integration in either the "audit rules" configuration box or the "auditd rule files" box by specifying a file to read the audit rules from.
+- For this detection rule no additional audit rules are required.
+
+
+*Framework*: MITRE ATT&CK^TM^
+
+* Tactic:
+** Name: Resource Development
+** ID: TA0042
+** Reference URL: https://attack.mitre.org/tactics/TA0042/
+* Technique:
+** Name: Obtain Capabilities
+** ID: T1588
+** Reference URL: https://attack.mitre.org/techniques/T1588/
+* Sub-technique:
+** Name: Malware
+** ID: T1588.001
+** Reference URL: https://attack.mitre.org/techniques/T1588/001/