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CVE-2022-29211: Improper Input Validation

May 21, 2022 (updated June 3, 2022)

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.histogram_fixed_width is vulnerable to a crash when the values array contain Not a Number (NaN) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If values contains NaN then the result of the division is still NaN and the cast to int32 would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

References

  • github.com/advisories/GHSA-xrp2-fhq4-4q3w
  • github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc
  • github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc
  • github.com/tensorflow/tensorflow/commit/e57fd691c7b0fd00ea3bfe43444f30c1969748b5
  • github.com/tensorflow/tensorflow/issues/45770
  • github.com/tensorflow/tensorflow/releases/tag/v2.6.4
  • github.com/tensorflow/tensorflow/releases/tag/v2.7.2
  • github.com/tensorflow/tensorflow/releases/tag/v2.8.1
  • github.com/tensorflow/tensorflow/releases/tag/v2.9.0
  • github.com/tensorflow/tensorflow/security/advisories/GHSA-xrp2-fhq4-4q3w
  • nvd.nist.gov/vuln/detail/CVE-2022-29211

Code Behaviors & Features

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Affected versions

All versions before 2.6.4, all versions starting from 2.7.0 before 2.7.2, all versions starting from 2.8.0 before 2.8.1

Fixed versions

  • 2.6.4
  • 2.7.2
  • 2.8.1

Solution

Upgrade to versions 2.6.4, 2.7.2, 2.8.1 or above.

Impact 5.5 MEDIUM

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Learn more about CVSS

Weakness

  • CWE-20: Improper Input Validation

Source file

pypi/tensorflow/CVE-2022-29211.yml

Spotted a mistake? Edit the file on GitLab.

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