CVE-2021-41217 : Vulnerability Insights and Analysis

TensorFlow is an open source platform for machine learning. In affected versions, a vulnerability leads to a null pointer exception due to assumptions made during the graph-building process.

Understanding CVE-2021-41217

This CVE highlights a vulnerability in TensorFlow that could result in a null pointer exception when certain nodes are not paired as expected.

What is CVE-2021-41217?

The vulnerability in TensorFlow arises during the construction of the control flow graph for a model when the first node in a pairing is missing, causing a crash when dereferencing a null pointer.

The Impact of CVE-2021-41217

The impact of this vulnerability is assessed with a CVSS base score of 5.5, categorizing it as of medium severity with a high availability impact in affected versions of TensorFlow.

Technical Details of CVE-2021-41217

This section delves into the technical aspects of the vulnerability found in TensorFlow.

Vulnerability Description

The vulnerability is due to incorrect assumptions in the node pairing process, leading to a null pointer exception that can cause a crash in affected versions.

Affected Systems and Versions

TensorFlow versions >= 2.6.0, < 2.6.1
TensorFlow versions >= 2.5.0, < 2.5.2
TensorFlow versions < 2.4.4

Exploitation Mechanism

The vulnerability can be exploited by causing specific nodes to be unpaired in the control flow graph construction process, triggering a null pointer exception.

Mitigation and Prevention

Steps to address and prevent the CVE-2021-41217 vulnerability.

Immediate Steps to Take

Update TensorFlow to version 2.7.0 or apply the fix included in TensorFlow 2.6.1, 2.5.2, and 2.4.4.

Long-Term Security Practices

Regularly update software to the latest versions to mitigate known vulnerabilities.
Implement secure coding practices when developing machine learning models.

Patching and Updates

Ensure timely application of security patches and updates provided by TensorFlow to address vulnerabilities.