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


Severity

Recommended
0.0
medium
0
10

CVSS assessment made by Snyk's Security Team

    Threat Intelligence

    EPSS
    0.18% (57th percentile)

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  • Snyk ID SNYK-PYTHON-TENSORFLOW-1013467
  • published 28 Sep 2020
  • disclosed 25 Sep 2020
  • credit Aivul Team from Qihoo 360

How to fix?

Upgrade tensorflow to version 2.3.1 or higher.

Overview

tensorflow 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
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Snyk

Recommended
6.3 medium
  • Attack Vector (AV)
    Network
  • Attack Complexity (AC)
    High
  • Privileges Required (PR)
    Low
  • User Interaction (UI)
    None
  • Scope (S)
    Changed
  • Confidentiality (C)
    None
  • Integrity (I)
    None
  • Availability (A)
    High
Expand this section

NVD

6.3 medium