CVE-2022-41901 Explained : Impact and Mitigation

A vulnerability has been discovered in TensorFlow that could allow an attacker to trigger a

CHECK

fail via input in

SparseMatrixNNZ

. This CVE has been identified as CVE-2022-41901 and has a CVSS base score of 4.8 (Medium).

Understanding CVE-2022-41901

This section provides detailed insights into the impact, technical details, and mitigation strategies related to CVE-2022-41901.

What is CVE-2022-41901?

TensorFlow, an open-source machine learning platform, is affected by this vulnerability. It occurs when an input

sparse_matrix

that is not a matrix with a shape of rank 0 triggers a

CHECK

fail in

tf.raw_ops.SparseMatrixNNZ

.

The Impact of CVE-2022-41901

The vulnerability can be exploited by an attacker to cause a denial of service (DoS) condition. However, as the required privileges are low, the impact is rated as medium with an availability impact of high.

Technical Details of CVE-2022-41901

This section provides specific technical details regarding the vulnerability.

Vulnerability Description

The issue arises due to improper input validation, specifically with the handling of input

sparse_matrix

that deviates from the expected rank 0 shape.

Affected Systems and Versions

The vulnerability affects TensorFlow versions 2.10.0 to 2.10.1, 2.9.0 to 2.9.3, and versions below 2.8.4.

Exploitation Mechanism

An attacker needs network access and user interaction to exploit this vulnerability, making it crucial for users to apply the necessary patches and updates.

Mitigation and Prevention

This section outlines the steps to mitigate the risks associated with CVE-2022-41901.

Immediate Steps to Take

Users are advised to update their TensorFlow installations to version 2.11 or apply the provided patch to address the vulnerability.

Long-Term Security Practices

It is recommended to follow secure coding practices and validate inputs properly to prevent similar vulnerabilities in the future.

Patching and Updates

The issue has been addressed in GitHub commit f856d02e5322821aad155dad9b3acab1e9f5d693 and will be included in TensorFlow 2.11. Additionally, the fix will be backported to versions 2.10.1, 2.9.3, and 2.8.4.