PyPI: tensorflow-rocm
CVE-2021-37690
Safety vulnerability ID: SFTY-20210813-58261
Safety legacy ID: pyup.io-57793
Tensorflow-rocm 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
Overview
Use after free and segfault in shape inference functions
Advisory
Tensorflow-rocm 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
Also affects
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How to Fix
Mitigation and Workarounds
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Vulnerable Functions
Functions linked to known vulnerabilities.
References
- https://getsafety.com/vulnerabilities/SFTY-20210813-58261/CVE-2021-37690
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg
- https://nvd.nist.gov/vuln/detail/CVE-2021-37690
- https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-603.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-801.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-312.yaml
- https://github.com/advisories/GHSA-3hxh-8cp2-g4hg
Verified by Safety
Our Cybersecurity Intelligence Team reviewed this vulnerability. We combine public data with our own research to find issues not yet reported to public sources.
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