Learn about CVE-2021-37636 impacting TensorFlow versions 2.3.4 - 2.5.1 due to a division by 0 error in `SparseDenseCwiseDiv`. Discover its impact, technical details, and mitigation steps.
TensorFlow, an open-source platform for machine learning, is impacted by CVE-2021-37636 due to a vulnerability in the implementation of
SparseDenseCwiseDiv
leading to a division by 0 error. The issue affects versions of TensorFlow greater than or equal to 2.3.4 but less than 2.5.1, 2.4.3, and 2.6.0. Learn more about the impact, technical details, and mitigation strategies below.
Understanding CVE-2021-37636
This section provides an overview of the vulnerability affecting TensorFlow.
What is CVE-2021-37636?
TensorFlow's vulnerability in
SparseDenseCwiseDiv
can result in a division by 0 error due to inadequate handling of this specific case within the binary operation class implementation.
The Impact of CVE-2021-37636
The vulnerability has a CVSS score of 5.5, indicating a medium severity issue. It has a low attack complexity but high availability impact, potentially leading to service disruption.
Technical Details of CVE-2021-37636
Explore the technical aspects of the vulnerability in TensorFlow.
Vulnerability Description
The vulnerable
SparseDenseCwiseDiv
functionality in TensorFlow allows a division by 0 error due to insufficient exception handling.
Affected Systems and Versions
TensorFlow versions >= 2.5.0 and < 2.5.1, >= 2.4.0 and < 2.4.3, as well as < 2.3.4 are impacted by this vulnerability.
Exploitation Mechanism
The vulnerability can be exploited locally with low privileges and no user interaction required, making it relatively accessible to attackers.
Mitigation and Prevention
Discover the steps to mitigate the impact of CVE-2021-37636.
Immediate Steps to Take
Users are advised to update TensorFlow to version 2.6.0 or apply the respective patches in TensorFlow 2.5.1, 2.4.3, and 2.3.4 to address the vulnerability.
Long-Term Security Practices
Incorporating secure coding practices and regular security updates can help mitigate future vulnerabilities in TensorFlow.
Patching and Updates
Stay vigilant for security advisories from TensorFlow and promptly apply recommended patches to enhance security.