CVE-2020-26267: TensorFlow - Uninitialized Memory Access and Crashes in tf.raw_ops.DataFormatVecPermute

Background

TensorFlow is an open-source machine learning framework widely used for developing and training deep learning models. It provides a comprehensive ecosystem of tools, libraries, and resources for building and deploying machine learning applications. The tf.raw_ops.DataFormatVecPermute API in TensorFlow is responsible for permuting data formats, specifically assuming a permutation of NHWC (Number of examples, Height, Width, Channels).

Vulnerability Detail

In affected versions of TensorFlow, the tf.raw_ops.DataFormatVecPermute API does not properly validate the src_format and dst_format attributes. The code assumes that these two arguments define a permutation of NHWC, which can lead to uninitialized memory accesses, reading outside of bounds, and even crashes. An attacker could potentially exploit this vulnerability to execute arbitrary code or cause denial of service. This vulnerability is tracked as CVE-2020-26267 and has been assigned the identifier GHSA-c9f3-9wfr-wgh7.

pip install --upgrade "tensorflow==2.21.0"

Workaround

As a workaround, if updating TensorFlow is not immediately feasible, developers can manually validate the src_format and dst_format attributes before using the tf.raw_ops.DataFormatVecPermute API. This can be done by ensuring that the provided formats are valid permutations of NHWC. Here's an example code snippet in Python:

import tensorflow as tf

def validate_formats(src_format, dst_format):
    valid_formats = ['NHWC', 'NCHW', 'HWCN', 'HWNC', ...]  # List of valid permutations
    if src_format not in valid_formats or dst_format not in valid_formats:
        raise ValueError('Invalid format permutation')

# Usage
src_format = 'NHWC'
dst_format = 'NCHW'
validate_formats(src_format, dst_format)

Conclusion

In conclusion, the tf.raw_ops.DataFormatVecPermute API in TensorFlow is vulnerable to uninitialized memory accesses, reading outside of bounds, and crashes. It is crucial to update TensorFlow to the fixed versions or manually validate the format attributes to mitigate this vulnerability. For further support on vulnerability remediation, you can reach out to DevNack.com.

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