Improper Input Validation Affecting tensorflow-cpu 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-TENSORFLOWCPU-1013468
  • published 28 Sep 2020
  • disclosed 25 Sep 2020
  • credit Aivul Team from Qihoo 360

How to fix?

Upgrade tensorflow-cpu to version 2.3.1 or higher.

Overview

tensorflow-cpu 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
Expand this section

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