Skip to content
OpenAdvisories
Medium · 4.3 CVE-2022-21732 BIT-tensorflow-2022-21732EUVD-2022-0295GHSA-c582-c96p-r5cqPYSEC-2022-111PYSEC-2022-56PYSEC-2026-3158

Memory exhaustion in Tensorflow

Published Feb 3, 2022 · Updated Feb 12, 2025 · Assigned by GitHub_M

Description

Tensorflow is an Open Source Machine Learning Framework. The implementation of `ThreadPoolHandle` can be used to trigger a denial of service attack by allocating too much memory. This is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Affected packages

EcosystemPackageAffectedFixedRecord
PyPI tensorflow < 2.5.3 2.5.3 GHSA-c582-c96p-r5cq
PyPI tensorflow >= 2.6.0, < 2.6.3 2.6.3 GHSA-c582-c96p-r5cq
PyPI tensorflow >= 2.7.0, < 2.7.1 2.7.1 GHSA-c582-c96p-r5cq
PyPI tensorflow < 2.5.3 · >= 2.6.0, < 2.6.3 · >= 2.7.0, < 2.7.1 2.5.3, 2.6.3, 2.7.1 PYSEC-2026-3158
PyPI tensorflow-cpu < 2.5.3 2.5.3 GHSA-c582-c96p-r5cq
PyPI tensorflow-cpu >= 2.6.0, < 2.6.3 2.6.3 GHSA-c582-c96p-r5cq
PyPI tensorflow-cpu >= 2.7.0, < 2.7.1 2.7.1 GHSA-c582-c96p-r5cq
PyPI tensorflow-cpu < 2.5.3 · >= 2.6.0, < 2.6.3 2.5.3, 2.6.3 PYSEC-2022-56
PyPI tensorflow-gpu < 2.5.3 2.5.3 GHSA-c582-c96p-r5cq
PyPI tensorflow-gpu >= 2.6.0, < 2.6.3 2.6.3 GHSA-c582-c96p-r5cq
PyPI tensorflow-gpu >= 2.7.0, < 2.7.1 2.7.1 GHSA-c582-c96p-r5cq
PyPI tensorflow-gpu < 2.5.3 · >= 2.6.0, < 2.6.3 2.5.3, 2.6.3 PYSEC-2022-111

References