Use of Uninitialized Resource Affecting tensorflow/tensorflow package, versions [2.2.0, 2.2.1)[2.3.0, 2.3.1)


Severity

Recommended
0.0
high
0
10

CVSS assessment by Snyk's Security Team. Learn more

Threat Intelligence

Exploit Maturity
Proof of Concept
EPSS
0.83% (54th percentile)

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  • Snyk IDSNYK-UNMANAGED-TENSORFLOWTENSORFLOW-2333434
  • published12 Jan 2022
  • disclosed25 Sept 2020
  • creditUnknown

Introduced: 25 Sep 2020

CVE-2020-15193  (opens in a new tab)
CWE-908  (opens in a new tab)

How to fix?

Upgrade tensorflow/tensorflow to version 2.2.1, 2.3.1 or higher.

Overview

Affected versions of this package are vulnerable to Use of Uninitialized Resource. In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of dlpack.to_dlpack can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a reinterpret_cast Since the PyObject is a Python object, not a TensorFlow Tensor, the cast to EagerTensor fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.

Note: Please refer to https://security.snyk.io/vuln/SNYK-PYTHON-TENSORFLOW-1013558

CVSS Base Scores

version 3.1