Use of Uninitialized Resource Affecting tensorflow/tensorflow package, versions [,2.1.4)[2.2.0,2.2.3)[2.3.0,2.3.3)[2.4.0,2.4.2)


Severity

Recommended
0.0
medium
0
10

CVSS assessment made by Snyk's Security Team. Learn more

Threat Intelligence

EPSS
0.04% (16th percentile)

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  • Snyk IDSNYK-UNMANAGED-TENSORFLOWTENSORFLOW-2333460
  • published12 Jan 2022
  • disclosed14 May 2021
  • creditUnknown

Introduced: 14 May 2021

CVE-2021-29580  (opens in a new tab)
CWE-908  (opens in a new tab)

How to fix?

Upgrade tensorflow/tensorflow to version 2.1.4, 2.2.3, 2.3.3, 2.4.2 or higher.

Overview

Affected versions of this package are vulnerable to Use of Uninitialized Resource. TensorFlow is an end-to-end open source platform for machine learning. The implementation of tf.raw_ops.FractionalMaxPoolGrad triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a CHECK condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

CVSS Scores

version 3.1