AVID-2026-R1070

Description

CHECK failures in FractionalAvgPoolGrad in TensorFlow (CVE-2022-35963)

Details

TensorFlow is an open source platform for machine learning. The implementation of FractionalAvgPoolGrad does not fully validate the input orig_input_tensor_shape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 03a659d7be9a1154fdf5eeac221e5950fec07dad. 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-2022-35963 describes a vulnerability in TensorFlow (FractionalAvgPoolGrad) where unchecked input shapes can trigger a CHECK failure, leading to a denial of service. TensorFlow is a core AI framework widely used to build/train/deploy AI systems, so this is a software component in the AI stack. The advisory provides patch details and affected versions, giving clear evidence of a security vulnerability impacting AI software supply chains.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-84jm-4cf3-9jfm
• https://github.com/tensorflow/tensorflow/commit/03a659d7be9a1154fdf5eeac221e5950fec07dad

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