Vulnerability · Published May 14, 2021 · Assigned by GitHub_M

CVE-2021-29557Division by 0 in `SparseMatMul`

Low 2.5

In plain English

A low-severity security flaw in tensorflow from tensorflow. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.2% (higher than 9% of all known vulnerabilities). Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)2.5Low
Exploit odds (30 days)0.2%top 91.4% of all CVEs
Exploited in the wildNo reportsnot in CISA KEV
Attack toolingNoneno public tooling known

Official description

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.SparseMatMul`. The division by 0 occurs deep in Eigen code because the `b` tensor is empty. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Affected packages & fixed versions

EcosystemPackageFixed inAdvisory
PyPItensorflow2.3.3GHSA-xw93-v57j-fcgh
PyPItensorflow2.4.2GHSA-xw93-v57j-fcgh
PyPItensorflow2.1.4GHSA-xw93-v57j-fcgh
PyPItensorflow2.1.4, 2.2.3, 2.3.3, 2.4.2PYSEC-2021-194
PyPItensorflow2.2.3GHSA-xw93-v57j-fcgh
PyPItensorflow-cpu2.4.2GHSA-xw93-v57j-fcgh
PyPItensorflow-cpu2.1.4GHSA-xw93-v57j-fcgh
PyPItensorflow-cpu2.2.3GHSA-xw93-v57j-fcgh
PyPItensorflow-cpu2.3.3GHSA-xw93-v57j-fcgh
PyPItensorflow-cpu2.1.4, 2.2.3, 2.3.3, 2.4.2PYSEC-2021-485
PyPItensorflow-gpu2.3.3GHSA-xw93-v57j-fcgh
PyPItensorflow-gpu2.4.2GHSA-xw93-v57j-fcgh
PyPItensorflow-gpu2.1.4GHSA-xw93-v57j-fcgh
PyPItensorflow-gpu2.1.4, 2.2.3, 2.3.3, 2.4.2PYSEC-2021-683
PyPItensorflow-gpu2.2.3GHSA-xw93-v57j-fcgh

Affected products (as reported)

VendorProductVersions
tensorflow tensorflow < 2.1.4>= 2.2.0, < 2.2.3>= 2.3.0, < 2.3.3>= 2.4.0, < 2.4.2

Weakness: CWE-369 · Vector: CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

References