AVID-2026-R0795

Description

Division by zero in TFLite’s implementation of EmbeddingLookup (CVE-2021-29596)

Details

TensorFlow is an end-to-end open source platform for machine learning. The implementation of the EmbeddingLookup TFLite operator is vulnerable to a division by zero error(https://github.com/tensorflow/tensorflow/blob/e4b29809543b250bc9b19678ec4776299dd569ba/tensorflow/lite/kernels/embedding_lookup.cc#L73-L74). An attacker can craft a model such that the first dimension of the value input is 0. 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-2021-29596 describes a division-by-zero vulnerability in TensorFlow Lite’s EmbeddingLookup. TensorFlow is a core AI framework, and EmbeddingLookup is a fundamental operator used in ML models and deployment pipelines. The vulnerability resides in the AI software stack and can affect the reliability/availability of AI systems that rely on TensorFlow/TFLite, representing a software supply-chain issue. The report includes affected versions, CVE references, and fix details, providing sufficient signal for 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: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