CVE-2021-29534 : Exploit Details and Defense Strategies

This article delves into the details of CVE-2021-29534, also known as the 'CHECK-fail in SparseConcat' vulnerability in TensorFlow.

Understanding CVE-2021-29534

In this section, we will explore what CVE-2021-29534 entails.

What is CVE-2021-29534?

CVE-2021-29534, also labeled as the 'CHECK-fail in SparseConcat,' is a vulnerability identified in TensorFlow. It allows an attacker to execute a denial of service attack through a

CHECK

-fail in

tf.raw_ops.SparseConcat

due to flawed implementation.

The Impact of CVE-2021-29534

The impact of this vulnerability is rated with a CVSS base score of 2.5 (Low). The attack complexity is high, leveraging a local attack vector with low availability impact.

Technical Details of CVE-2021-29534

Let's explore the technical aspects of CVE-2021-29534.

Vulnerability Description

The vulnerability arises from improper checks for exceptional conditions, specifically in the handling of dimensions for the output shape in TensorFlow operations.

Affected Systems and Versions

The affected versions include 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

An attacker can exploit this vulnerability to trigger a denial of service by exploiting the flawed

CHECK

operation in TensorFlow's

SparseConcat

implementation.

Mitigation and Prevention

Learn how to mitigate the risks posed by CVE-2021-29534.

Immediate Steps to Take

Users are advised to update their TensorFlow installations to versions beyond 2.4.2 to address this vulnerability.

Long-Term Security Practices

Implement robust coding practices and utilize recommended TensorFlow operations to prevent similar

CHECK

-failures.

Patching and Updates

Ensure timely application of patches and updates to stay protected from known vulnerabilities.