AVID-2026-R1104

Description

CHECK fail in FakeQuantWithMinMaxVarsGradient in TensorFlow (CVE-2022-36005)

Details

TensorFlow is an open source platform for machine learning. When tf.quantization.fake_quant_with_min_max_vars_gradient receives input min or max that is nonscalar, it gives a CHECK fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. 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-2022-36005 affects TensorFlow, a core AI framework used in ML pipelines. It is a software vulnerability in a component used to build/train/deploy AI systems, with a DoS potential, and has published remediation. This fits AI-related, GP AI supply chain, and security vuln criteria with sufficient evidence.

References

Affected or Relevant Artifacts

Developer: tensorflow
Deployer: tensorflow
Artifact Details:

Type	Name
System	tensorflow

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:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Base Score	5.9
Base Severity	🟠 Medium
Attack Vector	NETWORK
Attack Complexity	🔴 High
Privileges Required	NONE
User Interaction	NONE
Scope	UNCHANGED
Confidentiality Impact	NONE
Integrity Impact	NONE
Availability Impact	🔴 High

CWE

ID	Description
CWE-617	CWE-617: Reachable Assertion

Other information

Report Type: Advisory
Credits:
Date Reported: 2022-09-16
Version: 0.3.3
AVID Entry