CVE-2021-37647 : Vulnerability Insights and Analysis

TensorFlow is an open-source platform for machine learning. A vulnerability in the

tf.raw_ops.SparseTensorSliceDataset

implementation could allow a null pointer dereference. The issue arises when a user does not provide valid arguments for a sparse tensor, leading to a potential null pointer dereference.

Understanding CVE-2021-37647

This vulnerability affects TensorFlow versions >= 2.5.0 and < 2.5.1, >= 2.4.0 and < 2.4.3, and < 2.3.4.

What is CVE-2021-37647?

The vulnerability allows for a null pointer dereference in the

SparseTensorSliceDataset

implementation in TensorFlow when certain arguments are not provided correctly, potentially resulting in a denial of service scenario.

The Impact of CVE-2021-37647

With a CVSS v3.1 base score of 7.7, this high severity vulnerability can lead to data integrity issues in affected systems without requiring user privileges.

Technical Details of CVE-2021-37647

The vulnerability stems from inadequate argument validation when handling sparse tensors in the TensorFlow implementation.

Vulnerability Description

When

indices

or

values

are provided for an empty sparse tensor without consideration for the opposite, a null pointer dereference can occur in the

tf.raw_ops.SparseTensorSliceDataset

implementation.

Affected Systems and Versions

TensorFlow versions >= 2.5.0, < 2.5.1, >= 2.4.0, < 2.4.3, and < 2.3.4 are susceptible to this vulnerability.

Exploitation Mechanism

Failure to validate

indices

or

values

correctly for empty sparse tensors can trigger a null pointer dereference, impacting the integrity of affected systems.

Mitigation and Prevention

Proactive measures are crucial to mitigate the risks associated with CVE-2021-37647.

Immediate Steps to Take

Users are advised to update to TensorFlow version 2.6.0 or apply the patch available in commit 02cc160e29d20631de3859c6653184e3f876b9d7. For versions 2.5.1, 2.4.3, and 2.3.4, the fix has been cherrypicked to address the vulnerability.

Long-Term Security Practices

Ensure proper input validation in TensorFlow code to prevent null pointer dereference vulnerabilities and adhere to secure coding practices.

Patching and Updates

Regularly update TensorFlow to the latest versions with security patches to mitigate the risk of known vulnerabilities.