Improper input validation in Google Tensorflow

CVE-2023-25661

TensorFlow is an Open Source Machine Learning Framework. In versions prior to 2.11.1 a malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack. A proof of concept can be constructed with the `Convolution3DTranspose` function. This Convolution3DTranspose layer is a very common API in modern neural networks. The ML models containing such vulnerable components could be deployed in ML applications or as cloud services. This failure could be potentially used to trigger a denial of service attack on ML cloud services. An attacker must have privilege to provide input to a `Convolution3DTranspose` call. This issue has been patched and users are advised to upgrade to version 2.11.1. There are no known workarounds for this vulnerability.

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

Published · last modified .

CVSS v3 metric

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

EPSS exploit prediction

EPSS: 0.004 (35.4th percentile), scored .

Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 35th percentile — 35.4% 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-2023-25661: held from 0.004 to 0.004.

EPSS over last 30 days · oldest: 0.004 · newest: 0.004 · change: +0.000

Affected products

Weakness classification (CWE)

Public proof-of-concept exploits

References

Frequently asked questions

What is CVE-2023-25661?
CVE-2023-25661 is a medium-severity vulnerability in Google Tensorflow, classified under Improper Input Validation. CVSS score: 6.5/10. Published 2023-03-27.
How severe is CVE-2023-25661?
Medium severity. CVSS v3 base score is 6.5 out of 10.
Is CVE-2023-25661 known to be exploited?
2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.