CVE-2021-29568: TensorFlow - Null Pointer Dereference in tf.raw_ops.ParameterizedTruncatedNormal

Background

TensorFlow is an end-to-end open source platform for machine learning. It provides a comprehensive ecosystem of tools, libraries, and resources for developing and deploying machine learning models. TensorFlow is widely used in various domains, including research, industry, and academia. It offers a range of functionalities for building and training neural networks, as well as tools for data preprocessing, visualization, and evaluation. However, a vulnerability has been discovered in TensorFlow that can lead to undefined behavior and potential security risks.

Vulnerability Detail

The vulnerability, identified as CVE-2021-29568, resides in the tf.raw_ops.ParameterizedTruncatedNormal function of TensorFlow. This function is responsible for generating random numbers from a parameterized truncated normal distribution. The vulnerability arises from a lack of input validation in the implementation of this function. Specifically, the code does not check the validity of the shape argument before accessing its first element. If the shape argument is empty, the code attempts to access an empty array, resulting in a null pointer dereference. An attacker can exploit this vulnerability by providing a crafted input that triggers the null pointer dereference, potentially leading to a denial of service (DoS) or arbitrary code execution.

Workaround

As a temporary workaround, users can manually validate the shape argument before calling the tf.raw_ops.ParameterizedTruncatedNormal function. By ensuring that the shape argument is not empty, the null pointer dereference can be avoided. Here is an example of how to perform this validation in Python:

import tensorflow as tf

def safe_parameterized_truncated_normal(shape, mean, stddev):
    if not shape:
        raise ValueError('Shape argument cannot be empty')
    return tf.raw_ops.ParameterizedTruncatedNormal(shape=shape, mean=mean, stddev=stddev)

Conclusion

The vulnerability in TensorFlow's tf.raw_ops.ParameterizedTruncatedNormal function can result in undefined behavior and potential security risks. It is crucial for users to update their TensorFlow installations to the latest patched version as soon as it becomes available. Regularly checking for updates and promptly applying them is essential to ensure the security and stability of TensorFlow deployments. For further support and assistance in vulnerability remediation, please contact DevNack.com.

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