AI Security Framework | NIST AI RMF | OWASP LLM
Implement a structured AI security framework aligned with NIST AI RMF, OWASP LLM Top 10, ISO 42001, and EU AI Act — covering controls, risk management, and compliance.
AI Security Framework — Structured Security for AI Systems
Structured controls, risk management processes, and compliance mapping across NIST AI RMF, OWASP LLM Top 10, MITRE ATLAS, and ISO 42001 — giving your AI security programme a defensible, auditable foundation.
- OWASP LLM Top 10 technical controls across all in-scope LLM deployment layers
- NIST AI RMF implementation: GOVERN, MAP, MEASURE, MANAGE functions
- MITRE ATLAS adversary tactic coverage for AI-specific attack technique defence
- ISO 42001 AI management system control alignment and gap closure
- Ongoing risk identification, treatment, and monitoring process establishment
- Audit-ready compliance evidence: control test results, risk register, incident records
Why Ad-Hoc AI Security Creates Gaps
Individual teams implement AI security controls independently — creating inconsistent protection levels and compliance gaps at the boundaries between teams and AI system components.
Multiple Frameworks Must Be Harmonised
NIST AI RMF, OWASP LLM Top 10, ISO 42001, and EU AI Act overlap significantly — a unified implementation approach maps controls to all frameworks simultaneously, avoiding duplicate effort.
Frameworks Enable Systematic Maintenance
AI systems evolve continuously. A framework provides the structure for systematic updates to controls and risk assessments as models, data, and attack techniques change.