NULL Pointer Dereference Affecting tensorflow/tensorflow package, versions [2.3.0,2.3.4)[2.4.0,2.4.3)


Severity

Recommended
0.0
medium
0
10

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

Threat Intelligence

EPSS
0.04% (9th percentile)

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  • Snyk IDSNYK-UNMANAGED-TENSORFLOWTENSORFLOW-2333424
  • published12 Jan 2022
  • disclosed12 Aug 2021
  • creditUnknown

Introduced: 12 Aug 2021

CVE-2021-37647  (opens in a new tab)
CWE-476  (opens in a new tab)

How to fix?

Upgrade tensorflow/tensorflow to version 2.3.4, 2.4.3 or higher.

Overview

Affected versions of this package are vulnerable to NULL Pointer Dereference. TensorFlow is an end-to-end open source platform for machine learning. When a user does not supply arguments that determine a valid sparse tensor, tf.raw_ops.SparseTensorSliceDataset implementation can be made to dereference a null pointer. The implementation has some argument validation but fails to consider the case when either indices or values are provided for an empty sparse tensor when the other is not. If indices is empty, then code that performs validation (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If indices as provided by the user is empty, then indices in the C++ code above is backed by an empty std::vector, hence calling indices->dim_size(0) results in null pointer dereferencing (same as calling std::vector::at() on an empty vector). We have patched the issue in GitHub commit 02cc160e29d20631de3859c6653184e3f876b9d7. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

CVSS Base Scores

version 3.1