Improper Input Validation Affecting tensorflow-gpu package, versions [2.3.0, 2.3.1)


Severity

Recommended
0.0
medium
0
10

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

Threat Intelligence

EPSS
0.18% (57th percentile)

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  • Snyk IDSNYK-PYTHON-TENSORFLOWGPU-1013466
  • published28 Sept 2020
  • disclosed25 Sept 2020
  • creditAivul Team from Qihoo 360

Introduced: 25 Sep 2020

CVE-2020-15197  (opens in a new tab)
CWE-20  (opens in a new tab)

How to fix?

Upgrade tensorflow-gpu to version 2.3.1 or higher.

Overview

tensorflow-gpu is a machine learning framework.

Affected versions of this package are vulnerable to Improper Input Validation. The SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a CHECK assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor.

References

CVSS Scores

version 3.1