CVE-2021-29546 Explained : Impact and Mitigation

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero in

tf.raw_ops.QuantizedBiasAdd

, leading to undefined behavior. The issue stems from a division operation without checking for a zero result. The affected versions include TensorFlow < 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. The fix will be part of TensorFlow 2.5.0 with backports to earlier versions.

Understanding CVE-2021-29546

This section delves into the details of the CVE-2021-29546 vulnerability, its impact, technical aspects, and mitigation strategies.

What is CVE-2021-29546?

CVE-2021-29546 relates to an integer division by zero vulnerability in TensorFlow's

QuantizedBiasAdd

module. Attackers can exploit this issue to cause undefined behavior due to a missing check for a zero result in the division operation.

The Impact of CVE-2021-29546

The vulnerability, with a CVSS base score of 2.5 (low severity), can be exploited locally with low privileges. Although it has a low availability impact, the potential for triggering undefined behavior poses a threat to the integrity of affected systems.

Technical Details of CVE-2021-29546

The following section outlines the vulnerability description, affected systems, versions, and the exploitation mechanism.

Vulnerability Description

The vulnerability arises from a division operation in

QuantizedBiasAdd

that does not verify a non-zero result, leading to potential integer division by zero scenarios.

Affected Systems and Versions

The vulnerability impacts TensorFlow versions including < 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 to trigger an integer division by zero operation by manipulating inputs to the

QuantizedBiasAdd

module.

Mitigation and Prevention

In this section, we cover immediate steps to take, long-term security practices, and the importance of patching and updates.

Immediate Steps to Take

Users are advised to update affected TensorFlow installations to versions where the fix for CVE-2021-29546 is available. Additionally, input validation and sanitization can help prevent potential exploitation.

Long-Term Security Practices

Implementing secure coding practices, regular security audits, and staying informed about TensorFlow security advisories can enhance long-term security posture against such vulnerabilities.

Patching and Updates

Ensure timely installation of patches and updates provided by TensorFlow to address CVE-2021-29546 and other known security issues.