Numeric Truncation Error Affecting tensorflow package, versions [,1.15.4) [2.0.0, 2.0.3) [2.1.0, 2.1.2) [2.2.0, 2.2.1) [2.3.0, 2.3.1)


0.0
critical

Snyk CVSS

    Attack Complexity High
    Scope Changed
    Confidentiality High
    Integrity High
    Availability High

    Threat Intelligence

    EPSS 0.27% (68th percentile)
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NVD
9 critical

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  • Snyk ID SNYK-PYTHON-TENSORFLOW-1013547
  • published 28 Sep 2020
  • disclosed 28 Sep 2020
  • credit Aivul Team from Qihoo 360

How to fix?

Upgrade tensorflow to version 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or higher.

Overview

tensorflow is a machine learning framework.

Affected versions of this package are vulnerable to Numeric Truncation Error. The Shard API in TensorFlow expects the last argument to be a function taking two int64 (i.e., long long) arguments. However, there are several places in TensorFlow where a lambda taking int or int32 arguments is being used.In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption.