CVE-2021-37646 Explained : Impact and Mitigation

TensorFlow, an open-source platform for machine learning, was found to have a vulnerability in its implementation of

tf.raw_ops.StringNGrams

, leading to an integer overflow issue. The issue arises from converting a signed integer to an unsigned one, potentially resulting in memory allocation errors. This CVE has a CVSS base score of 5.5 (Medium severity) and affects versions >= 2.5.0, < 2.5.1; >= 2.4.0, < 2.4.3; and < 2.3.4. Immediate patching is recommended to mitigate the risk.

Understanding CVE-2021-37646

This section delves into the details of the vulnerability, its impact, technical aspects, and mitigation strategies.

What is CVE-2021-37646?

The vulnerability involves an incorrect conversion between numeric types in TensorFlow, affecting certain versions and potentially leading to an integer overflow due to memory allocation issues.

The Impact of CVE-2021-37646

The vulnerability in TensorFlow's

StringNGrams

implementation can have a significant impact, potentially allowing attackers to exploit the integer overflow issue and cause memory allocation errors.

Technical Details of CVE-2021-37646

Let's explore the technical aspects of the CVE to understand its implications on affected systems and the exploitation mechanism.

Vulnerability Description

The vulnerability arises from converting a signed integer to an unsigned one, leading to memory allocation based on incorrect values. The issue has been addressed in later versions of TensorFlow.

Affected Systems and Versions

TensorFlow versions >= 2.5.0, < 2.5.1; >= 2.4.0, < 2.4.3; and < 2.3.4 are affected by this vulnerability, requiring immediate attention to prevent potential exploitation.

Exploitation Mechanism

Attackers could potentially exploit this vulnerability by manipulating input values to trigger the integer overflow issue, leading to memory allocation errors.

Mitigation and Prevention

To safeguard systems from potential exploitation, it is vital to implement immediate preventive measures and follow long-term security practices.

Immediate Steps to Take

Users are advised to update TensorFlow to versions 2.6.0 or apply the necessary patches provided to address the integer overflow vulnerability.

Long-Term Security Practices

Implementing secure coding practices, regular security audits, and monitoring for vulnerabilities can help prevent similar issues in the future.

Patching and Updates

Ensure timely patching of the affected TensorFlow versions to mitigate the risks associated with the integer overflow vulnerability.