CVE-2020-15266 Explained : Impact and Mitigation

In Tensorflow before version 2.4.0, a vulnerability exists that can lead to undefined behavior and a segmentation fault due to a specific argument in a function. This CVE has a CVSS base score of 3.7.

Understanding CVE-2020-15266

This CVE highlights a critical issue in Tensorflow versions prior to 2.4.0 that can result in a segmentation fault under certain conditions.

What is CVE-2020-15266?

The vulnerability in Tensorflow arises when a particular argument in the

tf.image.crop_and_resize

function is set to a very large value, causing the CPU kernel to interpret it as a

nan

floating point value. This misinterpretation leads to undefined behavior and ultimately triggers a segmentation fault.

The Impact of CVE-2020-15266

The impact of this vulnerability is rated as low severity, with a CVSS base score of 3.7. While the confidentiality and integrity of the system are not affected, the availability can be impacted due to the segmentation fault.

Technical Details of CVE-2020-15266

This section delves into the technical aspects of the CVE.

Vulnerability Description

The vulnerability stems from the mishandling of a specific argument in the

tf.image.crop_and_resize

function, leading to undefined behavior and a segmentation fault.

Affected Systems and Versions

Product: Tensorflow
Vendor: Tensorflow
Versions Affected: < 2.4.0

Exploitation Mechanism

The vulnerability can be exploited by providing a very large value to the

boxes

argument in the

tf.image.crop_and_resize

function, triggering the CPU kernel to misinterpret it as a

nan

floating point value.

Mitigation and Prevention

Protecting systems from CVE-2020-15266 requires immediate actions and long-term security practices.

Immediate Steps to Take

Update Tensorflow to version 2.4.0 or later to apply the patch that addresses this vulnerability.
Avoid passing excessively large values to the

boxes

argument in the

tf.image.crop_and_resize

function.

Long-Term Security Practices

Regularly monitor for security advisories and updates from Tensorflow.
Implement secure coding practices to prevent similar vulnerabilities in the future.

Patching and Updates

Ensure timely installation of patches and updates provided by Tensorflow to mitigate the risk of exploitation of this vulnerability.