CVE-2021-37687 : Vulnerability Insights and Analysis

This CVE article provides detailed information about a vulnerability found in TensorFlow affecting versions >= 2.3.4 and < 2.5.1, allowing attackers to read arbitrary data from the heap.

Understanding CVE-2021-37687

This section explores the details of the vulnerability, its impact, affected systems, and the mitigation steps required.

What is CVE-2021-37687?

TensorFlow, an open-source machine learning platform, contains a vulnerability in TFLite's

GatherNd

and

Gather

implementations, enabling attackers to exploit negative indices for heap data reading.

The Impact of CVE-2021-37687

The vulnerability's CVSS score is 5.5, with a base severity of MEDIUM. Attackers with low privileges can exploit this issue to access confidential data from the heap.

Technical Details of CVE-2021-37687

This section delves into the specifics of the vulnerability, affected systems, and exploitation techniques.

Vulnerability Description

The flaw in TensorFlow's TFLite allows attackers to read arbitrary heap data through negative indices in crafted models, leading to out-of-bounds read (CWE-125) vulnerabilities.

Affected Systems and Versions

TensorFlow versions >= 2.3.4 and < 2.5.1, including 2.4.0 to 2.4.3, are impacted by this vulnerability in the TFLite's

GatherNd

and

Gather

implementations.

Exploitation Mechanism

By manipulating negative values in

indices

, threat actors can carefully design models to exploit the vulnerability and access sensitive data.

Mitigation and Prevention

This section outlines the immediate and long-term steps to mitigate the risks posed by CVE-2021-37687 in TensorFlow.

Immediate Steps to Take

Users are advised to update to TensorFlow version 2.6.0 or apply the provided patches in versions 2.5.1, 2.4.3, and 2.3.4 to prevent heap data leakage.

Long-Term Security Practices

Maintaining up-to-date software versions and monitoring security advisories can help organizations stay ahead of emerging threats and vulnerabilities.

Patching and Updates

Regularly applying security patches released by TensorFlow and validating configurations can enhance system security and prevent potential exploits.