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. Learn more

Threat Intelligence

EPSS
0.3% (70th percentile)

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  • Snyk IDSNYK-PYTHON-TENSORFLOWCPU-1013617
  • published29 Sept 2020
  • disclosed25 Sept 2020
  • creditUnknown

Introduced: 25 Sep 2020

CVE-2020-15200  (opens in a new tab)
CWE-122  (opens in a new tab)
First added by Snyk

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. A BatchedMap is equivalent to a vector where each element is a hashmap. However, if the first element of splits_values is not 0, batch_idx will never be 1, hence there will be no hashmap at index 0 in per_batch_counts. Trying to access that in the user code results in a segmentation fault.

References

CVSS Scores

version 3.1