MoorAI maps its AI-coding-agent detections to the frameworks your auditors ask about — OWASP LLM Top 10, MITRE ATLAS, and STRIDE — and reports coverage against NIST AI RMF, ISO 42001, and SOC 2 / ISO 27001, all from redacted, content-free telemetry. So “how do you govern AI use?” has an evidenced answer.
Every threat in MoorAI's 40+ detection matrix carries three tags — the OWASP LLM Top 10 category, a MITRE ATLAS technique, and a STRIDE class — so the same finding is legible to the LLM-security, adversarial-ML, and threat-modeling teams with no re-mapping.
Because the mapping is built into the rule-base rather than bolted on, the console renders which OWASP LLM categories your policy covers and how — and exports it. And it's honest about what it is: a coverage and control-mapping view drawn from content-free telemetry, an input to an audit — not a certification.
Yes — each threat is tagged with an OWASP LLM category, a MITRE ATLAS technique, and a STRIDE class.
No. MoorAI generates control-mapping and coverage reports that feed an audit program; it is not itself a certification.
Yes — content-free, framework-enriched events in NDJSON or CEF.
More: on-device AI DLP · shadow-AI detection · MoorAI vs Prompt Security
OWASP LLM Top 10, MITRE ATLAS, STRIDE — mapped and exportable.