CVE-2022-36014 : Exploit Details and Defense Strategies

This article provides detailed information about CVE-2022-36014, a vulnerability in TensorFlow that could lead to a null-dereference in

mlir::tfg::TFOp::nameAttr

.

Understanding CVE-2022-20657

CVE-2022-36014 is a vulnerability in TensorFlow affecting versions prior to 2.7.2, between 2.8.0 and 2.8.1, and between 2.9.0 and 2.9.1.

What is CVE-2022-20657?

TensorFlow, an open-source platform for machine learning, is impacted by a vulnerability where

mlir::tfg::TFOp::nameAttr

crashes when receiving null type list attributes.

The Impact of CVE-2022-20657

The CVSS base score for this vulnerability is 5.9, with a base severity of MEDIUM. The attack complexity is HIGH, with a network-based attack vector and high availability impact.

Technical Details of CVE-2022-20657

Vulnerability Description

The vulnerability arises when

mlir::tfg::TFOp::nameAttr

processes null type list attributes, resulting in a crash.

Affected Systems and Versions

Versions of TensorFlow prior to 2.7.2, between 2.8.0 and 2.8.1, and between 2.9.0 and 2.9.1 are affected by this vulnerability.

Exploitation Mechanism

Upon receiving null type list attributes, the vulnerable function

mlir::tfg::TFOp::nameAttr

crashes, potentially leading to denial of service.

Mitigation and Prevention

Immediate Steps to Take

To mitigate the risk, users are advised to update TensorFlow to the patched version 2.10.0. Alternatively, the fix is available in TensorFlow versions 2.9.1, 2.8.1, and 2.7.2.

Long-Term Security Practices

Practicing secure coding and regular software updates can help prevent similar vulnerabilities in the future.

Patching and Updates

Ensure timely application of patches and updates provided by TensorFlow to address this vulnerability.