CVE-2023-25661
TensorFlow Convolution3DTranspose Denial of Service Vulnerability
Description
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.
INFO
Published Date :
March 27, 2023, 8:15 p.m.
Last Modified :
April 3, 2023, 4:19 p.m.
Source :
[email protected]
Remotely Exploitable :
Yes !
Impact Score :
3.6
Exploitability Score :
2.8
Public PoC/Exploit Available at Github
CVE-2023-25661 has a 1 public PoC/Exploit
available at Github.
Go to the Public Exploits
tab to see the list.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2023-25661
.
URL | Resource |
---|---|
https://github.com/tensorflow/tensorflow/commit/948fe6369a5711d4b4568ea9bbf6015c6dfb77e2 | Patch |
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxgc-95xx-grvq | Exploit Patch Vendor Advisory |
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
None
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Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2023-25661
vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2023-25661
vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
-
CVE Modified by [email protected]
May. 14, 2024
Action Type Old Value New Value -
Initial Analysis by [email protected]
Apr. 03, 2023
Action Type Old Value New Value Added CVSS V3.1 NIST AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H Changed Reference Type https://github.com/tensorflow/tensorflow/commit/948fe6369a5711d4b4568ea9bbf6015c6dfb77e2 No Types Assigned https://github.com/tensorflow/tensorflow/commit/948fe6369a5711d4b4568ea9bbf6015c6dfb77e2 Patch Changed Reference Type https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxgc-95xx-grvq No Types Assigned https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxgc-95xx-grvq Exploit, Patch, Vendor Advisory Added CWE NIST NVD-CWE-noinfo Added CPE Configuration OR *cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* versions up to (excluding) 2.11.1
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2023-25661
is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2023-25661
weaknesses.
Exploit Prediction
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days.
0.08 }} 0.01%
score
0.35810
percentile