Integer overflow in Google Tensorflow

CVE-2023-25667

TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, integer overflow occurs when `2^31 <= num_frames * height * width * channels < 2^32`, for example Full HD screencast of at least 346 frames. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.

Vulnerability class: Integer Overflow

Published · last modified .

CVSS v3 metric

CVSS v3 base score 6.5 (Medium). Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H.

EPSS exploit prediction

EPSS: 0.003 (21.2th percentile), scored .

Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 21st percentile — 21.2% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.

EPSS trend (30 days)EPSS over the last 30 days for CVE-2023-25667: held from 0.003 to 0.003.

EPSS over last 30 days · oldest: 0.003 · newest: 0.003 · change: +0.000

Affected products

Weakness classification (CWE)

Public proof-of-concept exploits

References

Frequently asked questions

What is CVE-2023-25667?
CVE-2023-25667 is a medium-severity vulnerability in Google Tensorflow, classified under Integer Overflow or Wraparound. CVSS score: 6.5/10. Published 2023-03-25.
How severe is CVE-2023-25667?
Medium severity. CVSS v3 base score is 6.5 out of 10.
Is CVE-2023-25667 known to be exploited?
1 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.