CVE-2022-36011 Explained : Impact and Mitigation

TensorFlow, an open-source platform for machine learning, is affected by a vulnerability known as Null dereference on MLIR on empty function attributes. This vulnerability arises when

mlir::tfg::ConvertGenericFunctionToFunctionDef

is provided with empty function attributes, resulting in a null dereference. The issue has been identified and patched in TensorFlow versions.

Understanding CVE-2022-36011

This section delves into the details of the CVE-2022-36011 vulnerability in TensorFlow.

What is CVE-2022-36011?

TensorFlow susceptible to a null dereference issue due to empty function attributes, which has been fixed in TensorFlow 2.10.0. Affected versions include TensorFlow < 2.7.2, >= 2.8.0 and < 2.8.1, and >= 2.9.0 and < 2.9.1.

The Impact of CVE-2022-36011

The vulnerability poses a medium severity threat with a base CVSS score of 5.9. It requires high attack complexity and has a significant impact on availability.

Technical Details of CVE-2022-36011

Explore the technical aspects of the CVE-2022-36011 vulnerability in TensorFlow.

Vulnerability Description

The issue results in a null dereference when empty function attributes are passed to

mlir::tfg::ConvertGenericFunctionToFunctionDef

in TensorFlow.

Affected Systems and Versions

TensorFlow versions impacted include < 2.7.2, >= 2.8.0 and < 2.8.1, and >= 2.9.0 and < 2.9.1.

Exploitation Mechanism

The vulnerability can be exploited remotely and does not require privileges or user interaction.

Mitigation and Prevention

Discover the steps to mitigate and prevent the CVE-2022-36011 vulnerability in TensorFlow.

Immediate Steps to Take

Update to TensorFlow 2.10.0 to eliminate the null dereference vulnerability. For versions 2.7.2, 2.8.1, and 2.9.1, apply the relevant patches.

Long-Term Security Practices

Adopt secure coding practices, implement code reviews, and stay informed about TensorFlow security updates.

Patching and Updates

Regularly check for security advisories from TensorFlow and apply patches promptly to keep your systems secure.