CVE-2021-41227: Arbitrary Memory Read in TensorFlow

Background

TensorFlow is an open-source machine learning framework widely used for developing and deploying machine learning models. It provides a comprehensive ecosystem of tools, libraries, and resources for building and training various types of neural networks. TensorFlow supports multiple programming languages and platforms, making it a popular choice among researchers and developers. However, a vulnerability has been discovered in TensorFlow that allows for arbitrary memory read, potentially leading to unauthorized access to sensitive information.

Vulnerability Detail

The vulnerability, identified as CVE-2021-41227, affects the ImmutableConst operation in TensorFlow. By exploiting this vulnerability, an attacker can trick the operation into reading arbitrary memory contents. This can be achieved by providing a specially crafted input to the operation. The issue arises due to a lack of proper handling of memory mapped strings in the tstring TensorFlow string class. Although the class has support for memory mapped strings, the ImmutableConst operation does not provide any support for this data type. As a result, an attacker can abuse this inconsistency to read arbitrary memory, potentially exposing sensitive data.

pip install --upgrade "tensorflow==2.21.0"

Workaround

As a temporary workaround, users can avoid using the ImmutableConst operation with memory mapped strings. Instead, alternative data types or operations can be used to achieve the desired functionality. Here is an example of how to avoid the vulnerable operation:

import tensorflow as tf

with open('/tmp/test', 'wb') as f:
    f.write(b'\xe2' * 128)
    data = tf.constant(b'\xe2' * 128)

print(data)

In this example, the constant operation is used as a substitute for ImmutableConst to create a tensor with the desired data. This ensures that the vulnerability is not triggered.

Conclusion

The vulnerability in TensorFlow (CVE-2021-41227) allows for arbitrary memory read, potentially leading to unauthorized access to sensitive information. It is crucial to update to the latest patched version of TensorFlow (2.7.0 or the backported versions) to mitigate the vulnerability. In the meantime, users can follow the provided workaround to avoid using the vulnerable operation. For further support on vulnerability remediation, please contact DevNack.com.

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