Out-of-Bounds Affecting tensorflow-cpu package, versions [2.4.0,2.4.2) [2.3.0,2.3.3) [2.2.0,2.2.3) [,2.1.4)


Severity

Recommended
0.0
high
0
10

CVSS assessment made by Snyk's Security Team

    Threat Intelligence

    EPSS
    0.09% (41st percentile)

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  • Snyk ID SNYK-PYTHON-TENSORFLOWCPU-1315683
  • published 1 Jul 2021
  • disclosed 1 Jul 2021
  • credit Unknown

How to fix?

Upgrade tensorflow-cpu to version 2.4.2, 2.3.3, 2.2.3, 2.1.4 or higher.

Overview

tensorflow-cpu is a machine learning framework.

Affected versions of this package are vulnerable to Out-of-Bounds. Incomplete validation in SparseAdd results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of *_indices matches the size of corresponding *_shape. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.

CVSS Scores

version 3.1
Expand this section

Snyk

Recommended
7.8 high
  • Attack Vector (AV)
    Local
  • Attack Complexity (AC)
    Low
  • Privileges Required (PR)
    Low
  • User Interaction (UI)
    None
  • Scope (S)
    Unchanged
  • Confidentiality (C)
    High
  • Integrity (I)
    High
  • Availability (A)
    High
Expand this section

NVD

7.8 high