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Vulnerability · Published Feb 3, 2022 · Assigned by GitHub_M

CVE-2022-21732Memory exhaustion in Tensorflow

Medium 4.3

In plain English

A medium-severity security flaw in the tensorflow package (PyPI). There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.8% (higher than 56% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)4.3Medium
Exploit odds (30 days)0.8%top 44.4% of all CVEs
Exploited in the wildNo reportsCISA SSVC: none
Attack toolingNoneno public tooling known

Official 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 & fixed versions

EcosystemPackageFixed inAdvisory
PyPItensorflow2.5.3GHSA-c582-c96p-r5cq
PyPItensorflow2.6.3GHSA-c582-c96p-r5cq
PyPItensorflow2.7.1GHSA-c582-c96p-r5cq
PyPItensorflow2.5.3, 2.6.3, 2.7.1PYSEC-2026-3158
PyPItensorflow-cpu2.6.3GHSA-c582-c96p-r5cq
PyPItensorflow-cpu2.7.1GHSA-c582-c96p-r5cq
PyPItensorflow-cpu2.5.3, 2.6.3PYSEC-2022-56
PyPItensorflow-cpu2.5.3GHSA-c582-c96p-r5cq
PyPItensorflow-gpu2.7.1GHSA-c582-c96p-r5cq
PyPItensorflow-gpu2.5.3, 2.6.3PYSEC-2022-111
PyPItensorflow-gpu2.5.3GHSA-c582-c96p-r5cq
PyPItensorflow-gpu2.6.3GHSA-c582-c96p-r5cq

Affected products (as reported)

VendorProductVersions
n/a n/a n/a

References