CVE-2021-29584: TensorFlow Integer Overflow Denial of Service

Background

TensorFlow is an end-to-end open source platform for machine learning. It provides a comprehensive ecosystem of tools, libraries, and resources for building and deploying machine learning models. TensorFlow is widely used in various domains, including research, industry, and academia. It supports both CPU and GPU computations, allowing for efficient training and inference on different hardware configurations.

Vulnerability Detail

The vulnerability identified as CVE-2021-29584 in TensorFlow is a denial of service (DoS) issue that can be triggered by an attacker. The vulnerability arises from an integer overflow in constructing a new tensor shape. The implementation of the TensorShape constructor fails to check for overflow when building a dense shape. This oversight can lead to a CHECK failure, resulting in a DoS condition. The vulnerable code can be found in the sparse_split_op.cc file of the TensorFlow source code. The issue affects multiple versions of TensorFlow, including 2.1.4, 2.2.3, 2.3.3, and 2.4.2.

pip install --upgrade "tensorflow-cpu==2.21.0"

Workaround

As a workaround, users can apply input validation and sanitization techniques to prevent malicious inputs from triggering the vulnerability. It is crucial to ensure that tensor shapes are constructed with valid dimensions and that overflow conditions are properly handled. Here is an example of input validation code that can be used as a workaround:

import tensorflow as tf

def construct_tensor_shape(shape):
    if all(dim > 0 for dim in shape):
        return tf.TensorShape(shape)
    else:
        raise ValueError('Invalid tensor shape')

Conclusion

The identified vulnerability in TensorFlow can lead to a denial of service condition when constructing tensor shapes. The TensorFlow development team has addressed the issue and will release patched versions of TensorFlow, including backports for earlier affected versions. Users are advised to update their installations to the latest patched version as soon as it becomes available. Applying input validation and sanitization techniques can serve as a temporary workaround. For further support on vulnerability remediation, please contact DevNack.com.

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