CVE-2022-41907 : Vulnerability Insights and Analysis

A critical overflow vulnerability was discovered in TensorFlow, an open-source machine learning platform. The vulnerability affects the

tf.raw_ops.ResizeNearestNeighborGrad

function, leading to an overflow when given a large

size

input. This CVE has been assigned the identifier CVE-2022-41907 and was published on November 18, 2022.

Understanding CVE-2022-41907

This section delves into the details of the overflow vulnerability in

ResizeNearestNeighborGrad

in TensorFlow.

What is CVE-2022-41907?

The CVE-2022-41907 vulnerability arises due to an overflow in the

tf.raw_ops.ResizeNearestNeighborGrad

function within TensorFlow. Attackers could potentially exploit this flaw to execute malicious code or disrupt services.

The Impact of CVE-2022-41907

The impact of CVE-2022-41907 is rated as medium severity with a CVSS base score of 4.8. The vulnerability could allow attackers to impact service availability, posing a threat to systems running the affected TensorFlow versions.

Technical Details of CVE-2022-41907

This section covers the technical aspects of the CVE, including the vulnerability description, affected systems, and exploitation mechanism.

Vulnerability Description

The vulnerability involves an overflow in the

tf.raw_ops.ResizeNearestNeighborGrad

function, triggered by a large

size

input, potentially leading to a denial of service or code execution.

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. Users running these versions are urged to update to the patched versions.

Exploitation Mechanism

Attackers can exploit this vulnerability by providing a large

size

input to the

tf.raw_ops.ResizeNearestNeighborGrad

function, triggering an overflow condition and potential service disruption.

Mitigation and Prevention

In this section, we discuss the steps to mitigate the risks posed by CVE-2022-41907 and prevent exploitation.

Immediate Steps to Take

Users should update TensorFlow to version 2.11 to mitigate the vulnerability and prevent potential overflow conditions.

Long-Term Security Practices

Regularly update TensorFlow to the latest patched versions to address known vulnerabilities and enhance overall system security.

Patching and Updates

TensorFlow has released patches for versions 2.10.1, 2.9.3, and 2.8.4 to address the overflow vulnerability. Users are advised to apply these patches promptly.