CVE-2021-37691 Explained : Impact and Mitigation

A detailed article about the Division by zero vulnerability in LSH in TensorFlow Lite, impacting versions >= 2.3.4 and < 2.5.1.

Understanding CVE-2021-37691

This CVE identifies a vulnerability in TensorFlow Lite that allows an attacker to trigger a division by zero error in the LSH implementation.

What is CVE-2021-37691?

TensorFlow Lite is an open-source machine learning platform, with the vulnerability found in versions >= 2.3.4 and < 2.5.1.

The Impact of CVE-2021-37691

The vulnerability allows an attacker to create a TFLite model that triggers the division by zero error in LSH, affecting the integrity and availability of the system.

Technical Details of CVE-2021-37691

The technical details include the vulnerability description, affected systems, and the exploitation mechanism.

Vulnerability Description

In affected versions, an attacker can exploit the LSH implementation to cause a division by zero error, potentially leading to system crashes or unauthorized access.

Affected Systems and Versions

Versions >= 2.3.4 and < 2.5.1 of TensorFlow Lite are impacted by this vulnerability.

Exploitation Mechanism

An attacker can craft a malicious TFLite model to exploit the flaw in the LSH implementation, causing the division by zero error.

Mitigation and Prevention

The mitigation strategies and preventive measures to safeguard systems against CVE-2021-37691.

Immediate Steps to Take

Users are advised to update TensorFlow to version 2.6.0 or apply the respective patches for versions 2.5.1, 2.4.3, and 2.3.4 to address the vulnerability.

Long-Term Security Practices

Implement secure coding practices, perform regular security audits, and stay informed about security updates for TensorFlow to prevent similar vulnerabilities.

Patching and Updates

Ensure timely installation of security patches and updates released by TensorFlow to mitigate the risk of exploitation.