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Improper Input Validation

CVE-2022-29211

Medium
5.5/10

Summary

TensorFlow is an open source platform for machine learning. Versions prior to 2.6.4, 2.7.x prior to 2.7.2, 2.8.x prior to 2.8.1, and 2.9.x prior to 2.9.0rc2, 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 2.9.0rc2, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

  • LOW
  • LOCAL
  • NONE
  • UNCHANGED
  • NONE
  • LOW
  • NONE
  • HIGH

CWE-20 - Improper Input Validation

The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.

References

Advisory Timeline

  • Published