AVID-2026-R1073

Description

Segfault in QuantizedAvgPool in TensorFlow (CVE-2022-35966)

Details

TensorFlow is an open source platform for machine learning. If QuantizedAvgPool is given min_input or max_input tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 7cdf9d4d2083b739ec81cfdace546b0c99f50622. 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-2022-35966 is a software vulnerability in TensorFlow (an AI framework) causing a segfault and potential denial-of-service. TensorFlow is a core component used in building/training/deploying AI systems, so this affects the AI software supply chain. The report provides explicit vulnerability details, patch information, and references, giving clear 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-20	CWE-20: Improper Input Validation

Other information

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