AVID-2026-R1076

Description

CHECK fail in Conv2DBackpropInput in TensorFlow (CVE-2022-35969)

Details

TensorFlow is an open source platform for machine learning. The implementation of Conv2DBackpropInput requires input_sizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c. 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 CVE-2022-35969 entry describes a software vulnerability in TensorFlow (Conv2DBackpropInput) that can trigger a denial of service. TensorFlow is a core AI framework used to build/train/deploy general-purpose AI systems, making this a software supply chain issue in AI stacks. The report provides patch details, affected versions, and references, giving clear evidence of a security vulnerability in a software component commonly used in AI pipelines.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q2c3-jpmc-gfjx
• https://github.com/tensorflow/tensorflow/commit/50156d547b9a1da0144d7babe665cf690305b33c

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