CVE-2021-37683 : Security Advisory and Response

TensorFlow is an end-to-end open source platform for machine learning. In affected versions, the implementation of division in TFLite is vulnerable to a division by 0 error. There is no check that the divisor tensor does not contain zero elements. The issue has been patched in GitHub commit 1e206baedf8bef0334cca3eb92bab134ef525a28. The fix will be included in TensorFlow 2.6.0, and also cherrypicked on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4. The CVSS v3.1 base score for this vulnerability is 5.5 (Medium Severity).

Understanding CVE-2021-37683

This section provides insights into the impact, technical details, and mitigation strategies related to CVE-2021-37683.

What is CVE-2021-37683?

CVE-2021-37683 concerns a vulnerability in TensorFlow Lite where the division operation is susceptible to a division by 0 error due to the absence of a check for zero elements in the divisor tensor.

The Impact of CVE-2021-37683

The vulnerability's impact is rated as Medium severity according to CVSS v3.1 metrics. The affected versions of TensorFlow in the specified range are at risk of this division by zero error.

Technical Details of CVE-2021-37683

In this section, we delve into the vulnerability description, affected systems, versions, and exploitation mechanism.

Vulnerability Description

The flaw in TensorFlow Lite's division operation allows a potential attacker to trigger a division by zero error, impacting the reliability and integrity of machine learning processes.

Affected Systems and Versions

TensorFlow versions >= 2.3.4 and < 2.5.1, >= 2.4.0 and < 2.4.3, and >= 2.5.0 and < 2.5.1 are confirmed to be affected by this vulnerability.

Exploitation Mechanism

An attacker could exploit this vulnerability by crafting input data to trigger a division by zero error in TensorFlow Lite, leading to denial of service or potential system instability.

Mitigation and Prevention

This section outlines immediate steps to take and long-term security practices to mitigate the risks associated with CVE-2021-37683.

Immediate Steps to Take

Users are advised to update TensorFlow to versions 2.6.0 or apply the specific patches on TensorFlow 2.5.1, 2.4.3, and 2.3.4. Additionally, input validation for divisor tensors is recommended to prevent exploitation.

Long-Term Security Practices

To enhance overall security posture, organizations should prioritize regular software updates, implement secure coding practices, and conduct thorough security assessments to identify and remediate vulnerabilities proactively.

Patching and Updates

It is crucial to stay informed about security advisories from TensorFlow and promptly apply patches and updates to ensure the integrity and security of machine learning workflows.