Vulnerability · Published May 20, 2022 · Assigned by GitHub_M

CVE-2022-29198Missing validation causes denial of service in TensorFlow via `SparseTensorToCSRSparseMatrix`

Medium 5.5

In plain English

A medium-severity improper input validation in tensorflow from tensorflow. Proof-of-concept exploit code is public. The chance it is exploited in the next 30 days is estimated at 0.3% (higher than 26% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)5.5Medium
Exploit odds (30 days)0.3%top 74.3% of all CVEs
Exploited in the wildNo reportsCISA SSVC: poc
Attack toolingNoneno public tooling known

Official description

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.SparseTensorToCSRSparseMatrix` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `dense_shape` is a vector and `indices` is a matrix (as part of requirements for sparse tensors) but there is no validation for this. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Affected packages & fixed versions

EcosystemPackageFixed inAdvisory
PyPItensorflow2.8.1GHSA-mg66-qvc5-rm93
PyPItensorflow2.7.2GHSA-mg66-qvc5-rm93
PyPItensorflow2.6.4GHSA-mg66-qvc5-rm93
PyPItensorflow2.6.4, 2.7.2, 2.8.1PYSEC-2026-3214
PyPItensorflow-cpu2.6.4, 2.7.2, 2.8.1PYSEC-2026-3350
PyPItensorflow-cpu2.6.4GHSA-mg66-qvc5-rm93
PyPItensorflow-cpu2.7.2GHSA-mg66-qvc5-rm93
PyPItensorflow-cpu2.8.1GHSA-mg66-qvc5-rm93
PyPItensorflow-gpu2.8.1GHSA-mg66-qvc5-rm93
PyPItensorflow-gpu2.6.4, 2.7.2, 2.8.1PYSEC-2026-1018
PyPItensorflow-gpu2.7.2GHSA-mg66-qvc5-rm93
PyPItensorflow-gpu2.6.4GHSA-mg66-qvc5-rm93

Affected products (as reported)

VendorProductVersions
tensorflow tensorflow < 2.6.4>= 2.7.0rc0, < 2.7.2>= 2.8.0rc0, < 2.8.1>= 2.9.0rc0, < 2.9.0

Weakness: CWE-20 · Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

References