CVE-2021-41196 Explained : Impact and Mitigation

TensorFlow is an open-source platform for machine learning. In affected versions, the Keras pooling layers can trigger a segfault if the pool's size is 0 or if a dimension is negative due to TensorFlow's implementation of pooling operations.

Understanding CVE-2021-41196

In this CVE, a crash occurs in

max_pool3d

when the size argument is 0 or negative.

What is CVE-2021-41196?

TensorFlow's pooling layers can cause a crash if the pool size is 0 or if a dimension is negative, leading to a segfault. This is due to the pooling operation implementation in TensorFlow.

The Impact of CVE-2021-41196

The vulnerability has a CVSS base score of 5.5, with medium severity. It has low attack complexity and requires local access. The availability impact is high, while confidentiality and integrity impacts are none.

Technical Details of CVE-2021-41196

The following technical details are associated with CVE-2021-41196:

Vulnerability Description

The Keras pooling layers in TensorFlow can trigger a segfault in specific conditions.

Affected Systems and Versions

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

Exploitation Mechanism

Crash occurs within

max_pool3d

when the size argument is 0 or negative due to unchecked values in the sliding window.

Mitigation and Prevention

Here are the steps to address CVE-2021-41196:

Immediate Steps to Take

Update TensorFlow to version 2.7.0 once the fix is available.
Apply patches provided by TensorFlow for versions 2.6.1, 2.5.2, and 2.4.4.

Long-Term Security Practices

Regularly update TensorFlow to the latest version to prevent known vulnerabilities.
Monitor TensorFlow security advisories and apply fixes promptly.

Patching and Updates

Keep TensorFlow updated to mitigate potential security risks.