CVE-2021-37675 : What You Need to Know

TensorFlow, a popular open-source platform for machine learning, is impacted by a vulnerability in most convolution operators leading to a denial of service due to a division by 0 issue. An attacker can exploit this flaw to cause a crash, affecting versions >= 2.3.4 and < 2.5.1. Learn more about the impact, technical details, and mitigation strategies below.

Understanding CVE-2021-37675

This section provides detailed insights into the TensorFlow vulnerability.

What is CVE-2021-37675?

TensorFlow's affected versions are vulnerable to a division by 0 issue in convolution operators, enabling attackers to trigger denial of service via a crash.

The Impact of CVE-2021-37675

The vulnerability poses a medium threat with a CVSS base score of 5.5, impacting availability given a low attack complexity and vector. It requires low privileges and no user interaction.

Technical Details of CVE-2021-37675

Explore the technical aspects of the TensorFlow vulnerability.

Vulnerability Description

The flaw arises from missing validations in shape inference implementations before division and modulo operations.

Affected Systems and Versions

Impacted versions of TensorFlow include >= 2.5.0 and < 2.5.1, >= 2.4.0 and < 2.4.3, and < 2.3.4.

Exploitation Mechanism

Attackers can exploit this vulnerability by triggering a crash through convolution operators operations.

Mitigation and Prevention

Discover strategies to mitigate and prevent exploits targeting CVE-2021-37675.

Immediate Steps to Take

Users are advised to update TensorFlow to version 2.6.0 to address the vulnerability. For versions 2.5.1, 2.4.3, and 2.3.4, apply the patch provided in commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4.

Long-Term Security Practices

Follow secure coding practices, conduct regular security audits, and stay informed about TensorFlow's security advisories.

Patching and Updates

Keep TensorFlow up to date with the latest patches and security fixes to protect against emerging threats.