AVID-2026-R1081

Description

Segfault in QuantizedRelu and QuantizedRelu6 (CVE-2022-35979)

Details

TensorFlow is an open source platform for machine learning. If QuantizedRelu or QuantizedRelu6 are given nonscalar inputs for min_features or max_features, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Reason for inclusion in AVID: CVE-2022-35979 reports a segfault in TensorFlow’s QuantizedRelu/QuantizedRelu6 causing denial of service when given nonscalar inputs for min_features or max_features. This is a software vulnerability in a core AI framework used to build/train/deploy AI systems, i.e., a software supply chain component (TensorFlow). The issue is clearly tied to a vulnerability behavior (DoS via crash) and there is evidence of a patch and affected versions provided. Therefore it meets AI relevance, software supply-chain scope, security impact, and has sufficient evidence for AVID curation.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v7vw-577f-vp8x

Affected or Relevant Artifacts

• Developer: tensorflow
• Deployer: tensorflow
• Artifact Details:

Impact

AVID Taxonomy Categorization

• Risk domains: Security
• SEP subcategories: S0100: Software Vulnerability
• Lifecycle stages: L06: Deployment

CVSS

CWE

Other information

• Report Type: Advisory
• Credits:
• Date Reported: 2022-09-16
• Version: 0.3.3
• AVID Entry