Potential Vulnerability in ACON Library: Improper Input Validation Leading to Malicious Code Execution
Get instant alerts when new vulnerabilities affect ACON - before attackers find them.
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.
Our own answer: ranges merged, affected separated from platform-only, with confidence and review flags.
No remediation guidance has been written for this CVE yet, and no fixed version or vendor advisory is recorded against it.
SSVC signals action urgency (what to patch first), separate from CVSS which measures severity.
Get alerted
Track the products you run and VulnTracker tells you when a new CVE affects them — with what is known about fixing it, and nothing about the rest.