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Sony Neural Network Libraries reliance on untrusted inputs prior to v1.0.10

Critical severity GitHub Reviewed Published May 13, 2022 to the GitHub Advisory Database • Updated Jan 27, 2023

Package

pip nnabla (pip)

Affected versions

< 1.0.10

Patched versions

1.0.10

Description

nbla/logger.cpp in libnnabla.a in Sony Neural Network Libraries (aka nnabla) prior to v1.0.10 relies on the HOME environment variable, which might be untrusted.

References

Published by the National Vulnerability Database Apr 4, 2019
Published to the GitHub Advisory Database May 13, 2022
Reviewed Jul 28, 2022
Last updated Jan 27, 2023

Severity

Critical

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

EPSS score

0.186%
(57th percentile)

Weaknesses

CVE ID

CVE-2019-10844

GHSA ID

GHSA-4q2w-rw7m-xqw6

Source code

Credits

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