IQ:NS for Security Teams
The challenge
AI security risk spans multiple frameworks — OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, EU AI Act security provisions — each with different taxonomies and overlapping concepts.
What the ontologies provide
- Unified threat model — adversarial risk, prompt injection, data poisoning, model theft mapped across all relevant frameworks in one structured vocabulary
- Cross-framework coverage — see which controls each standard requires and where they overlap
- Integration-ready — SPARQL queries feed into SIEM, observability, and monitoring tools
- Vendor assessment structure — evaluate managed AI services (ChatGPT, Claude, Bedrock) against a consistent vocabulary
How it fits
The ontologies provide the semantic layer. Your existing SOC processes, SIEM tools, and incident response playbooks stay in place — they just get structured AI-specific context.