AVID-2026-R0953

Description

Null pointer dereference in TensorFlow (CVE-2022-21739)

Details

Tensorflow is an Open Source Machine Learning Framework. The implementation of QuantizedMaxPool has an undefined behavior where user controlled inputs can trigger a reference binding to null pointer. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Reason for inclusion in AVID: CVE-2022-21739 details a null pointer dereference in TensorFlow’s QuantizedMaxPool, a vulnerability in a widely-used AI framework. This directly concerns AI/ML systems and their software stack, potentially impacting availability. It affects software components used to build/train/deploy AI systems (TensorFlow), fitting the software supply chain category for general-purpose AI. The report provides sufficient evidence (CVE, description, fixes, references) to classify it as a security-related vulnerability in the AI software stack.

References

• NVD entry
• https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3mw4-6rj6-74g5
• https://github.com/tensorflow/tensorflow/commit/53b0dd6dc5957652f35964af16b892ec9af4a559
• https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/quantized_pooling_ops.cc#L114-L130

Affected or Relevant Artifacts

• Developer: n/a
• Deployer: n/a
• Artifact Details:

Impact

AVID Taxonomy Categorization

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

CVSS

Other information

• Report Type: Advisory
• Credits:
• Date Reported: 2022-02-03
• Version: 0.3.3
• AVID Entry