CVE-2021-29601 Explained : Impact and Mitigation

A vulnerability has been identified in TensorFlow, a popular open-source platform for machine learning. The issue lies in the TFLite implementation of concatenation, leading to an integer overflow problem. This vulnerability has been assigned CVE-2021-29601 and has a CVSS base score of 6.3, categorizing it as a medium severity flaw.

Understanding CVE-2021-29601

This section will delve into the details of the vulnerability affecting TensorFlow.

What is CVE-2021-29601?

TensorFlow's TFLite implementation of concatenation is prone to an integer overflow issue where an attacker can manipulate model dimensions to trigger an overflow in

int

values.

The Impact of CVE-2021-29601

The vulnerability's impact is classified as having a high availability impact and high integrity impact, with a base severity rated as medium. It requires low privileges to exploit locally.

Technical Details of CVE-2021-29601

Let's explore the technical aspects related to the CVE-2021-29601 vulnerability.

Vulnerability Description

The vulnerability arises from the way TFLite handles tensor dimensions, using

int

instead of

int64

, potentially causing integer overflow during model conversion.

Affected Systems and Versions

TensorFlow versions prior to 2.1.4 and between 2.2.0 to 2.4.2 are affected by this vulnerability, with TensorFlow 2.5.0 including the fix.

Exploitation Mechanism

Attackers can craft malicious models to exploit the integer overflow vulnerability during the conversion process to TFLite format.

Mitigation and Prevention

Learn how to mitigate the risks associated with CVE-2021-29601.

Immediate Steps to Take

Users are advised to update to TensorFlow version 2.5.0 to address this vulnerability. Alternatively, applying patches provided for TensorFlow 2.4.2, 2.3.3, 2.2.3, and 2.1.4 can help mitigate the risk.

Long-Term Security Practices

Maintaining up-to-date software versions and following security best practices can enhance the overall security posture of TensorFlow deployments.

Patching and Updates

Regularly check for security updates and patches from the TensorFlow project to stay protected against potential threats.