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Vulnerability · Published Feb 3, 2022 · Assigned by GitHub_M

CVE-2022-23567Integer overflows in Tensorflow

Medium 6.5

In plain English

A medium-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 1.1% (higher than 66% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)6.5Medium
Exploit odds (30 days)1.1%top 34.0% 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 implementations of `Sparse*Cwise*` ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service). We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. 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-rrx2-r989-2c43
PyPItensorflow2.6.3GHSA-rrx2-r989-2c43
PyPItensorflow2.7.1GHSA-rrx2-r989-2c43
PyPItensorflow2.5.3, 2.6.3, 2.7.1PYSEC-2026-3240
PyPItensorflow-cpu2.6.3GHSA-rrx2-r989-2c43
PyPItensorflow-cpu2.7.1GHSA-rrx2-r989-2c43
PyPItensorflow-cpu2.5.3, 2.6.3PYSEC-2022-76
PyPItensorflow-cpu2.5.3GHSA-rrx2-r989-2c43
PyPItensorflow-gpu2.7.1GHSA-rrx2-r989-2c43
PyPItensorflow-gpu2.5.3, 2.6.3PYSEC-2022-131
PyPItensorflow-gpu2.5.3GHSA-rrx2-r989-2c43
PyPItensorflow-gpu2.6.3GHSA-rrx2-r989-2c43

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:N/I:N/A:H

References