Heap-based Buffer Overflow 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
    0.13% (49th percentile)

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  • Snyk ID SNYK-PYTHON-TENSORFLOWCPU-1013536
  • published 28 Sep 2020
  • disclosed 28 Sep 2020
  • credit Unknown

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 Heap-based Buffer Overflow. The RaggedCountSparseOutput implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the splits tensor generate a valid partitioning of the values tensor. Hence, the code is prone to heap buffer overflow.If split_values does not end with a value at least num_values then the while loop condition will trigger a read outside of the bounds of split_values once batch_idx grows too large.

CVSS Scores

version 3.1
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Snyk

Recommended
4.8 medium
  • Attack Vector (AV)
    Network
  • Attack Complexity (AC)
    High
  • Privileges Required (PR)
    None
  • User Interaction (UI)
    None
  • Scope (S)
    Unchanged
  • Confidentiality (C)
    Low
  • Integrity (I)
    Low
  • Availability (A)
    None
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NVD

4.8 medium