CVE-2021-29527 : Vulnerability Insights and Analysis

A vulnerability labeled as CVE-2021-29527 has been identified in TensorFlow, an open-source platform for machine learning. The issue allows an attacker to trigger a division by 0 in

tf.raw_ops.QuantizedConv2D

.

Understanding CVE-2021-29527

This section delves into the details of the vulnerability, its impact, technical aspects, and mitigation strategies.

What is CVE-2021-29527?

TensorFlow, a widely used machine learning platform, is affected by a vulnerability that enables an attacker to exploit a division by zero in a specific function, potentially leading to denial of service or other security compromises.

The Impact of CVE-2021-29527

The impact of this vulnerability is considered low, with a CVSS base score of 2.5. However, the attack complexity is high, and an attacker with local access can exploit it without requiring special privileges or user interaction. It affects various versions of TensorFlow up to 2.4.2.

Technical Details of CVE-2021-29527

Below are the key technical details related to the CVE-2021-29527 vulnerability.

Vulnerability Description

The vulnerability allows an attacker to perform a division by zero in the

tf.raw_ops.QuantizedConv2D

function within TensorFlow, potentially causing the application to crash or behave unexpectedly.

Affected Systems and Versions

The vulnerability impacts TensorFlow versions up to 2.4.2. Specifically, 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 are affected.

Exploitation Mechanism

An attacker can exploit this vulnerability by manipulating the function

QuantizedConv2D

to trigger a division by zero, leading to a potential denial of service or system crash.

Mitigation and Prevention

Understanding how to mitigate and prevent CVE-2021-29527 is crucial to maintaining system security.

Immediate Steps to Take

To address this vulnerability, users are advised to update their TensorFlow installations to version 2.5.0. Additionally, TensorFlow versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4 will receive patches to fix the issue.

Long-Term Security Practices

Regularly updating TensorFlow and other dependencies, following security best practices, and monitoring for security advisories are essential for long-term security.

Patching and Updates

Stay informed about security patches and updates released by TensorFlow to address vulnerabilities like CVE-2021-29527. Promptly applying these patches can help protect systems from exploitation.