CVE-2021-29559 : Exploit Details and Defense Strategies

TensorFlow is an open-source platform for machine learning. This CVE addresses a vulnerability that allows an attacker to access data outside the bounds of a heap-allocated array in

tf.raw_ops.UnicodeEncode

due to incorrect assumptions. The issue affects TensorFlow 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. The fix is available in TensorFlow 2.5.0, with backports to versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4.

Understanding CVE-2021-29559

This section delves into the details of the TensorFlow vulnerability and its potential impact on affected systems.

What is CVE-2021-29559?

CVE-2021-29559 addresses a heap out-of-bounds access vulnerability in TensorFlow that could be exploited by an attacker to manipulate data beyond the boundaries of allocated memory.

The Impact of CVE-2021-29559

The vulnerability poses a low severity threat with high attack complexity. Although it requires low privileges to exploit and has low availability impact, the issue can still allow attackers to access sensitive information.

Technical Details of CVE-2021-29559

This section discusses the technical aspects of the vulnerability, affected systems, and the mechanism of exploitation.

Vulnerability Description

The vulnerability allows unauthorized data access outside the bounds of heap-allocated memory in the

tf.raw_ops.UnicodeEncode

function due to incorrect assumptions in TensorFlow's implementation.

Affected Systems and Versions

The vulnerability impacts TensorFlow 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.

Exploitation Mechanism

Attackers can exploit this vulnerability locally with high complexity, requiring low privileges. The exploit does not need user interaction and retains the scope of the attack unchanged.

Mitigation and Prevention

This section outlines the necessary steps to mitigate the risks associated with CVE-2021-29559 and prevent potential exploitation.

Immediate Steps to Take

Users are advised to update their TensorFlow installations to version 2.5.0 or apply the relevant patches provided for versions 2.4.2, 2.3.3, 2.2.3, and 2.1.4 to eliminate the vulnerability.

Long-Term Security Practices

To enhance overall security posture, users should regularly update TensorFlow and other software components, perform security assessments, and follow best practices in secure coding.

Patching and Updates

Stay informed about security updates and patches released by TensorFlow to address vulnerabilities promptly and ensure the ongoing protection of your systems.