{"data":{"id":"81919161-7ef0-4c73-a128-4efc2944100c","title":"CVE-2024-49361: ACON is a widely-used library of tools for machine learning that focuses on adaptive correlation optimization. A potenti","summary":"CVE-2024-49361 is a vulnerability in ACON, a machine learning library that performs adaptive correlation optimization. The vulnerability exists in how ACON validates input data, which could allow an attacker to bypass these checks and execute arbitrary code (run commands they shouldn't be able to run) on systems using ACON. Machine learning applications that accept user-provided data are at the highest risk, especially those running on production servers (live systems serving real users).","solution":"N/A -- no mitigation discussed in source.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2024-49361","publishedAt":"2024-10-18T19:15:14.393Z","cveId":"CVE-2024-49361","cweIds":["CWE-20"],"cvssScore":null,"cvssSeverity":null,"severity":"high","attackType":["other"],"issueType":"vulnerability","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":["ACON"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":"unknown","epssScore":0.00514,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","availability"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.75,"researchCategory":null,"atlasIds":null}}