AVID-2026-R1099

Description

Null dereference on MLIR on empty function attributes in TensorFlow (CVE-2022-36000)

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 aed36912609fc07229b4d0a7b44f3f48efc00fd0. 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-2022-36000 issue is a software vulnerability in TensorFlow (an AI framework) related to MLIR null dereference, with patches and affected versions documented. It concerns components (TensorFlow) used to build/train/deploy AI systems, i.e., a software supply chain issue in general-purpose AI stacks. Evidence includes description of the bug, affected versions, and patch information.

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