CVE-2021-29597: Division by zero in TFLite's implementation of SpaceToBatchNd in TensorFlow

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Background

TensorFlow is an open-source machine learning framework that provides a wide range of tools and libraries for developing and deploying machine learning models. It is widely used in various industries and has a large community of developers. One of the key components of TensorFlow is TFLite, which is a lightweight version of TensorFlow designed for mobile and embedded devices. TFLite includes various operators, including the SpaceToBatchNd operator, which is used for reshaping tensors by splitting them into blocks and rearranging the blocks. However, a vulnerability has been discovered in the implementation of the SpaceToBatchNd operator in TFLite, which can lead to a division by zero error.

Vulnerability Detail

The vulnerability in TFLite's implementation of the SpaceToBatchNd operator arises from a division by zero error. The vulnerable code can be found in the space_to_batch_nd.cc file of the TensorFlow Lite library. The code attempts to calculate the output size of the operator by dividing the final dimension size by the corresponding block shape dimension. However, it fails to check if the block shape dimension is zero, leading to a division by zero error. An attacker can exploit this vulnerability by crafting a model with a block input dimension set to zero, causing the division by zero error to occur during the execution of the model. The impact of this vulnerability can vary depending on the specific usage of the SpaceToBatchNd operator in a TensorFlow application, but it has the potential to cause crashes, unexpected behavior, or even remote code execution.

pip install --upgrade "tensorflow==2.21.0"

Workaround

As a workaround, users can manually check the block shape dimensions before using the SpaceToBatchNd operator and ensure that none of the dimensions are set to zero. This can be done by inspecting the input data or using appropriate validation checks. If a zero value is detected, alternative approaches or operators can be used to achieve the desired tensor reshaping. Here is an example code snippet that demonstrates the workaround:

import tensorflow as tf

block_shape = [2, 0, 3]
input_data = tf.constant([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])

if any(dim == 0 for dim in block_shape):
    # Handle the zero dimension case
    # Alternative approach or operator can be used
    ...
else:
    output_data = tf.nn.space_to_batch_nd(input_data, block_shape)
    ...

Note: The above code is a simplified example and may need to be adapted based on the specific usage of the SpaceToBatchNd operator in the application.

Conclusion

In conclusion, a division by zero vulnerability has been discovered in TFLite's implementation of the SpaceToBatchNd operator in TensorFlow. This vulnerability can be exploited by crafting a model with a zero value in the block input dimension, leading to a division by zero error. The impact of the vulnerability can range from crashes to remote code execution. Users should update to the patched versions of TensorFlow to mitigate this vulnerability. For further support on vulnerability remediation, please contact DevNack.com.

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