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CVE-2021-41209 : Exploit Details and Defense Strategies

Learn about CVE-2021-41209 involving a division by 0 vulnerability in TensorFlow versions 2.4.4 and above. Discover the impact, affected systems, and mitigation steps.

TensorFlow is an open-source platform for machine learning. In affected versions, the implementations for convolution operators trigger a division by 0 if passed empty filter tensor arguments. The fix will be included in TensorFlow 2.7.0. This CVE affects TensorFlow versions 2.6.0 to 2.6.1, 2.5.0 to 2.5.2, and versions below 2.4.4.

Understanding CVE-2021-41209

In this section, we will delve into the details of CVE-2021-41209.

What is CVE-2021-41209?

CVE-2021-41209 involves a division by 0 issue in TensorFlow's convolution operators when presented with empty filter tensor arguments.

The Impact of CVE-2021-41209

The impact of this vulnerability is assessed as MEDIUM with a base CVSS score of 5.5. The attack complexity is LOW, attack vector is LOCAL, and availability impact is HIGH. This vulnerability does not affect confidentiality or integrity.

Technical Details of CVE-2021-41209

Let's explore the technical aspects of CVE-2021-41209.

Vulnerability Description

The vulnerability triggers a division by 0 in TensorFlow's convolution operators when encountering empty filter tensors.

Affected Systems and Versions

        TensorFlow versions >= 2.6.0, < 2.6.1
        TensorFlow versions >= 2.5.0, < 2.5.2
        TensorFlow versions < 2.4.4

Exploitation Mechanism

The issue occurs when the convolution operators encounter empty filter tensors, leading to a division by 0.

Mitigation and Prevention

Let's discuss mitigation strategies for CVE-2021-41209.

Immediate Steps to Take

        Update TensorFlow to version 2.7.0 when available to eliminate the vulnerability.
        For versions 2.6.1, 2.5.2, and 2.4.4, apply the fix by cherrypicking the relevant commit.
        Avoid using empty filter tensor arguments in TensorFlow until the fix is applied.

Long-Term Security Practices

        Regularly update TensorFlow to the latest versions to ensure security patches are applied promptly.
        Monitor TensorFlow's security advisories and apply fixes proactively.

Patching and Updates

        Stay informed about security updates from TensorFlow and promptly apply patches to mitigate known vulnerabilities.

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