Executive Summary

Informations
Name CVE-2024-49361 First vendor Publication 2024-10-18
Vendor Cve Last vendor Modification 2024-10-21

Security-Database Scoring CVSS v3

Cvss vector : N/A
Overall CVSS Score NA
Base Score NA Environmental Score NA
impact SubScore NA Temporal Score NA
Exploitabality Sub Score NA
 
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Security-Database Scoring CVSS v2

Cvss vector :
Cvss Base Score N/A Attack Range N/A
Cvss Impact Score N/A Attack Complexity N/A
Cvss Expoit Score N/A Authentication N/A
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Detail

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.

Original Source

Url : http://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2024-49361

CWE : Common Weakness Enumeration

% Id Name
100 % CWE-20 Improper Input Validation

Sources (Detail)

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

Alert History

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0
1
Date Informations
2024-10-21 21:27:32
  • Multiple Updates
2024-10-19 00:27:25
  • First insertion