CVE-2021-29578: TensorFlow-GPU Heap Buffer Overflow in FractionalAvgPoolGrad

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-GPU is a variant of TensorFlow that leverages GPU acceleration for faster computation. The tf.raw_ops.FractionalAvgPoolGrad function is responsible for computing the gradients of the fractional average pooling operation. This function is vulnerable to a heap buffer overflow, which can be exploited by providing insufficient elements in the pooling sequence arguments. This vulnerability affects multiple versions of TensorFlow-GPU, including 2.1.4, 2.2.3, 2.3.3, and 2.4.2.

Vulnerability Detail

The vulnerability arises from the lack of validation in the tf.raw_ops.FractionalAvgPoolGrad implementation. When the out_backprop tensor shape does not have enough elements as required by the pooling sequence arguments, a heap buffer overflow occurs. An attacker can potentially exploit this vulnerability to execute arbitrary code or cause a denial of service. The issue has been identified and fixed in TensorFlow 2.5.0, and the fix has been backported to TensorFlow 2.4.2, 2.3.3, 2.2.3, and 2.1.4.

pip install --upgrade "tensorflow-gpu==2.12.0"

Workaround

As a temporary workaround, users can avoid using the tf.raw_ops.FractionalAvgPoolGrad function or ensure that the out_backprop tensor shape has enough elements to satisfy the pooling sequence arguments. This can be achieved by carefully validating the input tensors and adjusting their shapes if necessary. Here is an example of how to validate the tensor shape in Python:

import tensorflow as tf

out_backprop = ...  # The `out_backprop` tensor
pooling_sequence = ...  # The pooling sequence arguments

if out_backprop.shape[0] < pooling_sequence[0]:
    raise ValueError('Invalid tensor shape: `out_backprop` does not have enough elements')

Conclusion

The vulnerability in TensorFlow-GPU's tf.raw_ops.FractionalAvgPoolGrad function can lead to a heap buffer overflow, potentially enabling arbitrary code execution or denial of service. Users are advised to upgrade to TensorFlow 2.5.0 or apply the provided patches for the affected versions. Implementing proper input validation and following security best practices can help prevent exploitation of this vulnerability. For further assistance or support in vulnerability remediation, please contact DevNack.com.

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