AVID-2026-R0762

Description

Division by 0 in SparseMatMul (CVE-2021-29557)

Details

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service via a FPE runtime error in tf.raw_ops.SparseMatMul. The division by 0 occurs deep in Eigen code because the b tensor is empty. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Reason for inclusion in AVID: CVE-2021-29557 describes a software vulnerability in TensorFlow (an AI framework) where SparseMatMul can trigger a division-by-zero, causing a denial of service. This directly affects the AI software stack (model training/inference) and is triggered through the TensorFlow dependency. As TensorFlow is a core component used to build, train, deploy, and run general-purpose AI systems, this constitutes a software supply-chain vulnerability within AI pipelines. The issue is behavioral (DoS) and CVE-listed, with clear evidence of impact and affected artifacts (TensorFlow).

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:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
Base Score	2.5
Base Severity	🟢 Low
Attack Vector	LOCAL
Attack Complexity	🔴 High
Privileges Required	🟢 Low
User Interaction	NONE
Scope	UNCHANGED
Confidentiality Impact	NONE
Integrity Impact	NONE
Availability Impact	🟢 Low

CWE

ID	Description
CWE-369	CWE-369: Divide By Zero

Other information

Report Type: Advisory
Credits:
Date Reported: 2021-05-14
Version: 0.3.3
AVID Entry