AVID-2026-R1105

Description

Null dereference on MLIR on empty function attributes in TensorFlow (CVE-2022-36011)

Details

TensorFlow is an open source platform for machine learning. When mlir::tfg::ConvertGenericFunctionToFunctionDef is given empty function attributes, it gives a null dereference. We have patched the issue in GitHub commit 1cf45b831eeb0cab8655c9c7c5d06ec6f45fc41b. 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 describes a null pointer dereference in TensorFlow’s MLIR handling, causing a crash (availability impact). TensorFlow is a core AI framework, and the issue affects software components used to build, train, deploy, or run AI systems, i.e., the AI software supply chain. It is a security/vulnerability event with CVE reference and actionable patch information. Sufficient signals are present to warrant AVID curation.

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-476	CWE-476: NULL Pointer Dereference

Other information

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