Vulnerability · Published Feb 4, 2022 · Assigned by GitHub_M

CVE-2022-23589Null pointer dereference in Grappler's `IsConstant` in Tensorflow

Medium 6.5

In plain English

A medium-severity null pointer dereference in tensorflow from tensorflow. 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. Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a `SavedModel` file (fixing the first one would trigger the same dereference in the second place). First, during constant folding, the `GraphDef` might not have the required nodes for the binary operation. If a node is missing, the correposning `mul_*child` would be null, and the dereference in the subsequent line would be incorrect. We have a similar issue during `IsIdentityConsumingSwitch`. 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-9px9-73fg-3fqp
PyPItensorflow2.6.3GHSA-9px9-73fg-3fqp
PyPItensorflow2.7.1GHSA-9px9-73fg-3fqp
PyPItensorflow2.5.3, 2.6.3, 2.7.1PYSEC-2026-3154
PyPItensorflow-cpu2.6.3GHSA-9px9-73fg-3fqp
PyPItensorflow-cpu2.7.1GHSA-9px9-73fg-3fqp
PyPItensorflow-cpu2.5.3, 2.6.3PYSEC-2022-98
PyPItensorflow-cpu2.5.3GHSA-9px9-73fg-3fqp
PyPItensorflow-gpu2.7.1GHSA-9px9-73fg-3fqp
PyPItensorflow-gpu2.5.3, 2.6.3PYSEC-2022-153
PyPItensorflow-gpu2.5.3GHSA-9px9-73fg-3fqp
PyPItensorflow-gpu2.6.3GHSA-9px9-73fg-3fqp

Affected products (as reported)

VendorProductVersions
tensorflow tensorflow >= 2.7.0, < 2.7.1>= 2.6.0, < 2.6.3< 2.5.3

Weakness: CWE-476 · Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

References