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CVE-2024-49361 Detail

Description

ACON is a widely-used library of tools for machine learning that focuses on adaptive correlation optimization. A potential vulnerability has been identified in the input validation process, which could lead to arbitrary code execution if exploited. This issue could allow an attacker to submit malicious input data, bypassing input validation, resulting in remote code execution in certain machine learning applications using the ACON library. All users utilizing ACON’s input-handling functions are potentially at risk. Specifically, machine learning models or applications that ingest user-generated data without proper sanitization are the most vulnerable. Users running ACON on production servers are at heightened risk, as the vulnerability could be exploited remotely. As of time of publication, it is unclear whether a fix is available.


Metrics

NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 4.0 Severity and Vector Strings:

NIST CVSS score
NIST: NVD
N/A
NVD assessment not yet provided.

Nist CVSS score does not match with CNA score
CNA:  GitHub, Inc.
CVSS-BT 8.1 HIGH
Vector:  CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:U

References to Advisories, Solutions, and Tools

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Hyperlink Resource
https://github.com/torinriley/ACON/security/advisories/GHSA-345g-6rmp-3cv9

Weakness Enumeration

CWE-ID CWE Name Source
CWE-20 Improper Input Validation GitHub, Inc.  

Change History

1 change records found show changes

Quick Info

CVE Dictionary Entry:
CVE-2024-49361
NVD Published Date:
10/18/2024
NVD Last Modified:
10/21/2024
Source:
GitHub, Inc.