PyPI: tensorflow-gpu
CVE-2021-37678
Safety vulnerability ID: SFTY-20210812-30377
Safety legacy ID: pyup.io-56135
Tensorflow-gpu version 2.3.4, 2.4.3, 2.5.1, 2.6.0 and 2.7.0 include a fix for CVE-2021-37678: In affected versions, TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation(https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses "yaml.unsafe_load" which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, the Tensorflow team has removed it for now. The Tensorflow team has patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6jx-9g48-2r5r https://github.com/tensorflow/tensorflow/commit/23d6383eb6c14084a8fc3bdf164043b974818012
Overview
Arbitrary code execution due to YAML deserialization
Advisory
Tensorflow-gpu version 2.3.4, 2.4.3, 2.5.1, 2.6.0 and 2.7.0 include a fix for CVE-2021-37678: In affected versions, TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation(https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/python/keras/saving/model_config.py#L66-L104) uses "yaml.unsafe_load" which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, the Tensorflow team has removed it for now. The Tensorflow team has patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6jx-9g48-2r5r https://github.com/tensorflow/tensorflow/commit/23d6383eb6c14084a8fc3bdf164043b974818012
Affected Package
Also affects
---
How to Fix
Mitigation and Workarounds
---
Vulnerable Functions
Functions linked to known vulnerabilities.
References
- https://getsafety.com/vulnerabilities/SFTY-20210812-30377/CVE-2021-37678
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-r6jx-9g48-2r5r
- https://nvd.nist.gov/vuln/detail/CVE-2021-37678
- https://github.com/tensorflow/tensorflow/commit/23d6383eb6c14084a8fc3bdf164043b974818012
- https://github.com/tensorflow/tensorflow/commit/1df5a69e9f1a18a937e7907223066e606bf466b9
- https://github.com/tensorflow/tensorflow/commit/8e47a685785bef8f81bcb996048921dfde08a9ab
- https://github.com/tensorflow/tensorflow/commit/a09ab4e77afdcc6e1e045c9d41d5edab63aafc1a
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-591.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-789.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-300.yaml
- https://github.com/advisories/GHSA-r6jx-9g48-2r5r
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.
Learn more