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Vulnerability · Published Feb 3, 2022 · Assigned by GitHub_M

CVE-2022-21727Integer overflow in Tensorflow

High 7.6

In plain English

A high-severity integer overflow in the tensorflow package (PyPI). Proof-of-concept exploit code is public. The chance it is exploited in the next 30 days is estimated at 0.7% (higher than 52% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)7.6High
Exploit odds (30 days)0.7%top 48.0% of all CVEs
Exploited in the wildNo reportsCISA SSVC: poc
Attack toolingNoneno public tooling known

Official description

Tensorflow is an Open Source Machine Learning Framework. The implementation of shape inference for `Dequantize` is vulnerable to an integer overflow weakness. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked, and, since the code computes `axis + 1`, an attacker can trigger an integer overflow. 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-c6fh-56w7-fvjw
PyPItensorflow2.6.3GHSA-c6fh-56w7-fvjw
PyPItensorflow2.7.1GHSA-c6fh-56w7-fvjw
PyPItensorflow2.5.3, 2.6.3, 2.7.1PYSEC-2026-3159
PyPItensorflow-cpu2.6.3GHSA-c6fh-56w7-fvjw
PyPItensorflow-cpu2.7.1GHSA-c6fh-56w7-fvjw
PyPItensorflow-cpu2.5.3, 2.6.3PYSEC-2022-51
PyPItensorflow-cpu2.5.3GHSA-c6fh-56w7-fvjw
PyPItensorflow-gpu2.7.1GHSA-c6fh-56w7-fvjw
PyPItensorflow-gpu2.5.3, 2.6.3PYSEC-2022-106
PyPItensorflow-gpu2.5.3GHSA-c6fh-56w7-fvjw
PyPItensorflow-gpu2.6.3GHSA-c6fh-56w7-fvjw

Affected products (as reported)

VendorProductVersions
n/a n/a n/a

Weakness: CWE-190 · Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H

References