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


0.0
medium

Snyk CVSS

    Attack Complexity High
    Availability High

    Threat Intelligence

    EPSS 0.21% (58th percentile)
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NVD
5.9 medium

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  • Snyk ID SNYK-PYTHON-TENSORFLOW-1013616
  • published 29 Sep 2020
  • disclosed 25 Sep 2020
  • credit Unknown

How to fix?

Upgrade tensorflow to version 2.3.1 or higher.

Overview

tensorflow 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