Improper Input Validation Affecting tensorflow/tensorflow package, versions [,2.3.1)


Severity

Recommended
0.0
medium
0
10

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

Threat Intelligence

Exploit Maturity
Proof of Concept
EPSS
0.14% (51st percentile)

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  • Snyk IDSNYK-UNMANAGED-TENSORFLOWTENSORFLOW-2333394
  • published12 Jan 2022
  • disclosed25 Sept 2020
  • creditUnknown

Introduced: 25 Sep 2020

CVE-2020-15197  (opens in a new tab)
CWE-20  (opens in a new tab)
CWE-617  (opens in a new tab)

How to fix?

Upgrade tensorflow/tensorflow to version 2.3.1 or higher.

Overview

Affected versions of this package are vulnerable to Improper Input Validation. In Tensorflow before version 2.3.1, 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. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

CVSS Scores

version 3.1