PyPi: Tensorflow

CVE-2021-37690

Safety vulnerability ID: 41166

This vulnerability was reviewed by experts

The information on this page was manually curated by our Cybersecurity Intelligence Team.

Created at Aug 13, 2021 Updated at Oct 25, 2024
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Advisory

Tensorflow version 2.3.4, 2.4.3, 2.5.1 and 2.6.0 include a fix for CVE-2021-37690:
In affected versions when running shape functions, some functions (such as 'MutableHashTableShape') produce extra output information in the form of a 'ShapeAndType' struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. 'ShapeRefiner' is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but the Tensorflow team was not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. The Tensorflow team has patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1.
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg
https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1

Affected package

tensorflow

Latest version: 2.18.0

TensorFlow is an open source machine learning framework for everyone.

Affected versions

Fixed versions

Vulnerability changelog

TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. See CVE-2021-37690.


CONFIRM:https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg
MISC:https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1: https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1

Resources

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Severity Details

CVSS Base Score

MEDIUM 6.6

CVSS v3 Details

MEDIUM 6.6
Attack Vector (AV)
LOCAL
Attack Complexity (AC)
LOW
Privileges Required (PR)
LOW
User Interaction (UI)
NONE
Scope (S)
UNCHANGED
Confidentiality Impact (C)
LOW
Integrity Impact (I)
LOW
Availability Availability (A)
HIGH

CVSS v2 Details

MEDIUM 4.6
Access Vector (AV)
LOCAL
Access Complexity (AC)
LOW
Authentication (Au)
NONE
Confidentiality Impact (C)
PARTIAL
Integrity Impact (I)
PARTIAL
Availability Impact (A)
PARTIAL