AVID-2026-R0942

Description

Out of bounds read in Tensorflow (CVE-2022-21726)

Details

Tensorflow is an Open Source Machine Learning Framework. The implementation of Dequantize does not fully validate the value of axis and can result in heap OOB accesses. The axis argument can be -1 (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. 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-2022-21726 describes an out-of-bounds read in TensorFlow’s Dequantize operation due to insufficient validation of the axis argument. TensorFlow is a core ML framework; a vulnerability here affects AI software stacks and dependencies used to build, train, deploy, and run general-purpose AI systems. This is a software supply chain issue because it impacts a widely used dependency in AI pipelines. The CVE is actionable with CVSS v3.1 base score high (C/H, I/N, A/H) and has publicly documented fixes. The report provides clear signal including affected component and remediation references.

References

Affected or Relevant Artifacts

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

Type	Name
System	n/a

Impact

AVID Taxonomy Categorization

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

CVSS

Version	3.1
Vector String	CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
Base Score	8.1
Base Severity	🔴 High
Attack Vector	NETWORK
Attack Complexity	🟢 Low
Privileges Required	🟢 Low
User Interaction	NONE
Scope	UNCHANGED
Confidentiality Impact	🔴 High
Integrity Impact	NONE
Availability Impact	🔴 High

Other information

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