AVID-2026-R1086

Description

CHECK fail in LRNGrad in TensorFlow (CVE-2022-35985)

Details

TensorFlow is an open source platform for machine learning. If LRNGrad is given an output_image input tensor that is not 4-D, it results in a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. 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: The report describes a vulnerability in TensorFlow (LRNGrad) that can trigger a denial of service when given a malformed input. TensorFlow is a core AI framework widely used to build and run general-purpose AI systems, so this is a software supply-chain vulnerability affecting AI software stacks. It concerns AI/ML systems and their runtimes/frameworks, and the CVE includes fix details and affected versions, providing sufficient evidence.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9942-r22v-78cp
• https://github.com/tensorflow/tensorflow/commit/bd90b3efab4ec958b228cd7cfe9125be1c0cf255

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