Learn about CVE-2021-29596, a vulnerability in TensorFlow's `EmbeddingLookup` TFLite operator that allows a division by zero error. Find out the impacted versions and recommended mitigation steps.
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. 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. This vulnerability affects TensorFlow versions < 2.1.4, >= 2.2.0 and < 2.2.3, >= 2.3.0 and < 2.3.3, and >= 2.4.0 and < 2.4.2.
Understanding CVE-2021-29596
This CVE highlights a vulnerability in the
EmbeddingLookup
TFLite operator of TensorFlow that allows attackers to trigger a division by zero error.
What is CVE-2021-29596?
CVE-2021-29596 is a security vulnerability in TensorFlow's implementation of
EmbeddingLookup
TFLite operator that allows an attacker to exploit a division by zero error.
The Impact of CVE-2021-29596
The impact of this vulnerability is considered low, with an CVSS score of 2.5. However, it can be exploited by attackers with low privileges and locally.
Technical Details of CVE-2021-29596
This section provides detailed technical insights into the vulnerability.
Vulnerability Description
The vulnerability arises due to a division by zero error in the
EmbeddingLookup
TFLite operator of TensorFlow.
Affected Systems and Versions
TensorFlow versions affected by this vulnerability include < 2.1.4, >= 2.2.0 and < 2.2.3, >= 2.3.0 and < 2.3.3, and >= 2.4.0 and < 2.4.2.
Exploitation Mechanism
Attackers can exploit this vulnerability by crafting a model with the
value
input's first dimension set to 0.
Mitigation and Prevention
To address CVE-2021-29596, follow these mitigation and prevention strategies:
Immediate Steps to Take
Long-Term Security Practices
Patching and Updates