Executive Summary
Informations | |||
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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 | |||
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Overall CVSS Score | NA | ||
Base Score | NA | Environmental Score | NA |
impact SubScore | NA | Temporal Score | NA |
Exploitabality Sub Score | NA | ||
Calculate full CVSS 3.0 Vectors scores |
Security-Database Scoring CVSS v2
Cvss vector : | |||
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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 |
Calculate full CVSS 2.0 Vectors scores |
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 |
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100 % | CWE-20 | Improper Input Validation |
Sources (Detail)
Source | Url |
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Alert History
Date | Informations |
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2024-10-21 21:27:32 |
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2024-10-19 00:27:25 |
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