AVID-2026-R1097

Description

CHECK fail in EmptyTensorList in TensorFlow (CVE-2022-35998)

Details

TensorFlow is an open source platform for machine learning. If EmptyTensorList receives an input element_shape with more than one dimension, it gives a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c8ba76d48567aed347508e0552a257641931024d. 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-2022-35998 describes a vulnerability in TensorFlow (an ML framework) causing a denial-of-service via a CHECK failure in EmptyTensorList when element_shape has multiple dimensions. This directly concerns AI/ML software and is a defect in a component used to build/train/deploy AI systems; it affects software supply chains (TensorFlow as a dependency in AI stacks) and is a CVE with patched commits. Therefore it satisfies AI relevance, supply-chain relevance, security vulnerability, and has sufficient evidence in the report.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qhw4-wwr7-gjc5
• https://github.com/tensorflow/tensorflow/commit/c8ba76d48567aed347508e0552a257641931024d

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