Improper Validation of Integrity Check Value in TensorFlow

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Background

TensorFlow is an open-source machine learning framework developed by Google. 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. However, a vulnerability has been discovered in TensorFlow that could potentially lead to a denial of service attack or a heap out-of-bounds read.

Vulnerability Detail

The vulnerability in TensorFlow arises from the improper validation of the integrity check value in the implementation of tf.sparse.split. This function does not fully validate the input arguments, allowing a malicious user to trigger a denial of service attack or a heap out-of-bounds read. The vulnerability can be exploited by passing a non-scalar value for the axis parameter. This vulnerability is similar to a previously reported issue (TFSA-2021-190, CVE-2021-41206). The impact of this vulnerability can be severe, potentially leading to crashes, data corruption, or unauthorized access to sensitive information.

pip install --upgrade "tensorflow==2.21.0"

Workaround

As a temporary workaround, users can avoid passing non-scalar values for the axis parameter in the tf.sparse.split function. By ensuring that axis is always a scalar, the vulnerability can be mitigated. Here is an example of how to use the function with a scalar axis value:

import tensorflow as tf
data = tf.random.uniform([1, 32, 32], dtype=tf.float32)
axis = 1
x = tf.sparse.from_dense(data)
result = tf.sparse.split(x, 3, axis=axis)

By following this workaround, the risk of exploitation can be reduced until the TensorFlow installation is updated to a patched version.

Conclusion

The vulnerability in TensorFlow's tf.sparse.split function can lead to a denial of service attack or a heap out-of-bounds read. It is crucial to update your TensorFlow installation to the latest version or the respective patched versions to mitigate this vulnerability. Additionally, following the provided workaround can reduce the risk of exploitation. If you have any further questions or need assistance with vulnerability remediation, please contact DevNack.com.

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