Improper input validation in Google Tensorflow

CVE-2022-29212

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, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. 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 (24.0th 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-2022-29212?
CVE-2022-29212 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-2022-29212?
Medium severity. CVSS v3 base score is 5.5 out of 10.