CVE-2021-29532 : Vulnerability Insights and Analysis

A deep dive into the CVE-2021-29532, a vulnerability in TensorFlow that allows attackers to perform a heap out-of-bounds read via

RaggedCross

.

Understanding CVE-2021-29532

This section will cover the details of the vulnerability, its impact, technical description, affected systems, and mitigation steps.

What is CVE-2021-29532?

TensorFlow, a machine learning platform, is prone to an out-of-bounds read vulnerability due to inadequate validation in the

RaggedCross

function.

The Impact of CVE-2021-29532

The vulnerability allows an attacker to read beyond the bounds of allocated arrays, potentially leading to unauthorized access to sensitive information.

Technical Details of CVE-2021-29532

Let's explore the specifics of the vulnerability in terms of description, affected systems, and the exploitation mechanism.

Vulnerability Description

By passing invalid tensor values to

tf.raw_ops.RaggedCross

, an attacker can trigger heap out-of-bounds reads in TensorFlow versions < 2.1.4 and >= 2.2.0, < 2.4.2.

Affected Systems and Versions

The vulnerability impacts TensorFlow versions < 2.1.4 and >= 2.2.0, < 2.4.2, where the

next_*

index is manipulated without proper array bounds validation.

Exploitation Mechanism

The issue arises from the lack of range validation for

next_*

values, allowing attackers to force OOB heap reads by manipulating array elements.

Mitigation and Prevention

Discover the immediate steps to secure your systems, best security practices, and the importance of patching and updates.

Immediate Steps to Take

Users are advised to update TensorFlow to version 2.5.0 or apply the specific patches in versions 2.1.4, 2.2.3, 2.3.3, and 2.4.2 to mitigate the heap out-of-bounds read vulnerability.

Long-Term Security Practices

Implement secure coding practices and regularly update TensorFlow to ensure protection against similar vulnerabilities in the future.

Patching and Updates

Stay informed about security advisories and commit updates from the TensorFlow team to address known vulnerabilities and enhance system security.