Heap-based Buffer Overflow Affecting tensorflow-gpu package, versions [2.3.0, 2.3.1)


Severity

Recommended
0.0
medium
0
10

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

Threat Intelligence

EPSS
0.13% (49th percentile)

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  • Snyk IDSNYK-PYTHON-TENSORFLOWGPU-1013535
  • published28 Sept 2020
  • disclosed28 Sept 2020
  • creditUnknown

Introduced: 28 Sep 2020

CVE-2020-15201  (opens in a new tab)
CWE-20  (opens in a new tab)

How to fix?

Upgrade tensorflow-gpu to version 2.3.1 or higher.

Overview

tensorflow-gpu 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