CVE-2021-37660 : What You Need to Know

TensorFlow is an end-to-end open-source platform for machine learning. The vulnerability in affected versions allows an attacker to cause a floating-point exception by calling inplace operations with crafted arguments that result in a division by 0. The issue is due to a logic error in the implementation, which has been patched in GitHub commit e86605c0a336c088b638da02135ea6f9f6753618. Here's what you need to know about CVE-2021-37660:

Understanding CVE-2021-37660

In this section, we will delve into the details of the vulnerability in TensorFlow.

What is CVE-2021-37660?

The vulnerability in TensorFlow versions allows attackers to trigger a division by 0 when calling inplace operations with specific arguments.

The Impact of CVE-2021-37660

The impact of this vulnerability is rated as MEDIUM with a CVSS base score of 5.5. It can lead to a floating-point exception, potentially disrupting the affected system.

Technical Details of CVE-2021-37660

Let's explore the technical details of CVE-2021-37660.

Vulnerability Description

The vulnerability stems from a logic error in TensorFlow's implementation, enabling a division by 0 through crafted arguments.

Affected Systems and Versions

TensorFlow versions >= 2.3.4, < 2.5.1, and < 2.4.3 are impacted by this vulnerability.

Exploitation Mechanism

Attackers can exploit this vulnerability by invoking inplace operations with specific arguments that trigger a division by 0.

Mitigation and Prevention

To address CVE-2021-37660, take the following steps:

Immediate Steps to Take

Apply the patches provided by TensorFlow to fix the logic error.
Update TensorFlow to version 2.6.0 or apply the cherrypick commit on versions 2.5.1, 2.4.3, and 2.3.4.

Long-Term Security Practices

Regularly update TensorFlow and other dependencies to mitigate known vulnerabilities.

Patching and Updates

Stay informed about security advisories and apply relevant patches promptly to secure your systems.