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.
CVE-2024-49361
This high-severity CVE scores 8.1 under NVD CVSS v3. EPSS exploit probability: 0.7%, top 51% of all CVEs by exploit prediction. GitHub Security Advisory data not yet ingested — confidence will rise once GHSA publishes (typical lag: hours to days for open-source ecosystem CVEs; never for infrastructure-only CVEs).
- High severity, but no confirmed exploitation yet
No vendor fix yet — apply a workaround or compensating control (WAF / firewall / segmentation) and watch for a patch.
- CVSS v3
- 8.1
- EG Score
- 8.1(medium)
- EG Risk
- 52(Track)EG Risk 52/100SSVC: Track
EG Risk is EchelonGraph's 0–100 priority score: it fuses intrinsic severity with real-world exploitation and automatability so you can rank equal-severity CVEs and fix the most dangerous first. Higher = act sooner. Distinct from the 0–10 EG Score (severity).
How it’s computedSeverity81% × 45%Exploitation1% × 40%Automatability100% × 15%Action: Routine — remediate on your standard cadence. - EPSS PROB
- 1%
- EPSS %ILE
- 52%
- KEV
- Not listed
Published
October 18, 2024
Last Modified
April 15, 2026
Advisory Details (1)
Auto-updated Sep 19, 2026Potential Vulnerability in ACON Library: Improper Input Validation Leading to Malicious Code Execution · Advisory · torinriley/ACON · GitHub
https://github.com/torinriley/ACON/security/advisories/GHSA-345g-6rmp-3cv9Weakness Classification(1)
MITRE Common Weakness Enumeration — the root-cause categories this CVE belongs to.
Data Freshness Timeline
(refreshed 7× in last 7d / 31× in last 30d)
Each row is a source pipeline that fetched or updated this CVE on that date, with what changed. For example, "NVD update" means NVD published or revised its analysis for this CVE; "MITRE cvelistV5" means we ingested or refreshed it from the CNA feed. Most recent first.
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