CVE-2021-37664 : Exploit Details and Defense Strategies

A detailed overview of the CVE-2021-37664 vulnerability in TensorFlow, impacting versions >= 2.3.4 and < 2.5.1.

Understanding CVE-2021-37664

This section dives into the specifics of the vulnerability, its impact, technical details, and mitigation strategies.

What is CVE-2021-37664?

TensorFlow, a machine learning platform, is affected by a heap out-of-bounds vulnerability that allows attackers to read data outside of allocated bounds. The issue stems from inadequate validation of certain values.

The Impact of CVE-2021-37664

With a CVSS base score of 7.3, this high-severity vulnerability poses a risk of data confidentiality compromise and high availability impact. Attack complexity is low, with attackers requiring low privileges and no user interaction on a local vector.

Technical Details of CVE-2021-37664

This section delves into vulnerability description, affected systems, and the exploitation mechanism.

Vulnerability Description

The vulnerability allows attackers to read outside of heap allocated data by exploiting

BoostedTreesSparseCalculateBestFeatureSplit

function.

Affected Systems and Versions

Versions >= 2.3.4 and < 2.5.1 of TensorFlow are impacted, including versions 2.4.0, 2.4.3, and 2.5.0.

Exploitation Mechanism

By sending carefully crafted illegal arguments, attackers can exploit the vulnerability and read data beyond allocated bounds.

Mitigation and Prevention

Explore immediate steps and long-term security practices to mitigate the risks associated with CVE-2021-37664.

Immediate Steps to Take

Users are advised to apply patches promptly and validate input data to prevent unauthorized access to sensitive information.

Long-Term Security Practices

Implement robust input validation mechanisms and follow secure coding practices to avoid similar vulnerabilities in the future.

Patching and Updates

Keep TensorFlow up-to-date with the latest patches and releases. The issue has been addressed in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378 and will be included in TensorFlow 2.6.0, backported to versions 2.3.4, 2.4.3, and 2.5.1.