Improper input validation in Google Tensorflow

CVE-2022-29211

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.

Vulnerability class: Drupalgeddon 2 (CVE-2018-7600)

EPSS: 0.003 (23.7th percentile) — read the EPSS interpretation.

CVSS v3 metric

CVSS v3 base score 5.5 (Medium). Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.

Affected products

Weakness classification (CWE)

References

Frequently asked questions

What is CVE-2022-29211?
CVE-2022-29211 is a medium-severity vulnerability in Google Tensorflow, classified under Improper Input Validation. CVSS score: 5.5/10. Published 2022-05-21.
How severe is CVE-2022-29211?
Medium severity. CVSS v3 base score is 5.5 out of 10.