CVE-2021-29575 : What You Need to Know

TensorFlow is an end-to-end open source platform for machine learning. The implementation of

tf.raw_ops.ReverseSequence

allows for stack overflow and/or

CHECK

-fail based denial of service. Negative values for certain arguments can lead to these issues. The fix is included in TensorFlow 2.5.0 and also backported to earlier versions still within support.

Understanding CVE-2021-29575

This vulnerability in TensorFlow affects certain versions, potentially leading to denial of service attacks due to improper validation of arguments in a specific function.

What is CVE-2021-29575?

CVE-2021-29575 highlights a vulnerability in TensorFlow's

tf.raw_ops.ReverseSequence

function that can result in denial of service due to improper argument validation.

The Impact of CVE-2021-29575

The impact of this CVE is rated as LOW, with the attack complexity being HIGH and requiring low privileges. It can lead to a denial of service locally with low availability impact.

Technical Details of CVE-2021-29575

This section delves into the technical aspects of the vulnerability, including its description, affected systems, and the exploitation mechanism.

Vulnerability Description

The vulnerability stems from improper argument validation in the

tf.raw_ops.ReverseSequence

function, potentially causing denial of service.

Affected Systems and Versions

Versions of TensorFlow prior to 2.5.0, specifically < 2.1.4, >= 2.2.0, < 2.2.3, >= 2.3.0, < 2.3.3, and >= 2.4.0, < 2.4.2 are impacted by this vulnerability.

Exploitation Mechanism

Attackers can exploit this vulnerability by providing negative or invalid values for certain arguments, leading to denial of service.

Mitigation and Prevention

To address CVE-2021-29575, users should take immediate steps to secure their systems and implement long-term security practices.

Immediate Steps to Take

Update TensorFlow to version 2.5.0 or apply the necessary patches provided by TensorFlow to mitigate the vulnerability.

Long-Term Security Practices

Ensure regular software updates and security patches to prevent similar vulnerabilities in the future.

Patching and Updates

It is crucial to stay updated with security advisories from TensorFlow and promptly apply patches to secure your systems against potential threats.