Vulnerability · Published Oct 18, 2024 · Assigned by GitHub_M
CVE-2024-49361Potential Vulnerability in ACON Library: Improper Input Validation Leading to Malicious Code Execution
High 8.1
In plain English
A high-severity improper input validation in ACON from torinriley. There are no confirmed reports of exploitation so far. The chance it is exploited in the next 30 days is estimated at 0.7% (higher than 55% of all known vulnerabilities).
Official 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.
Affected products (as reported)
| Vendor | Product | Versions |
|---|---|---|
| torinriley | ACON | <= 1.1.0 |
Weakness: CWE-20 · 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
- https://github.com/torinriley/ACON/security/advisories/GHSA-345g-6rmp-3cv9 x_refsource_CONFIRM