Understand where your AI is exposed — before someone attacks it.
Classical threat modeling methods were built for deterministic software — Agentic AI demands more. We apply MAESTRO and OWASP Agentic Threats systematically to your architecture: layer by layer from foundation model to ecosystem, with real risk prioritisation.
AI Threat Modeling Maestro at a glance
Classical threat modeling does not understand what makes AI dangerous.
STRIDE was built for deterministic software. PASTA for classical risk analysis. Both are valuable — but they fall short as soon as you want to model an AI system that responds non-deterministically, autonomously selects tools and builds memory.
This creates a gap: controls get built on suspicion rather than on understood threats. MAESTRO closes that gap — as a 7-layer framework Cloud Security Alliance built specifically for Agentic AI. Combined with OWASP Agentic Threats and NIST AI RMF, it produces a threat model that fits what you are actually building.
What is MAESTRO threat modeling?
A structured threat analysis of your AI architecture — layered, architecture-specific and risk-based. Built specifically for Agentic AI systems that classical methods don't cover.
MAESTRO models your AI architecture across seven layers — from foundation models through data, frameworks, infrastructure to the agent ecosystem. Each layer has its own threats — and its own controls.
Threats don't only emerge inside a single layer — the most dangerous ones run across the system. Memory poisoning starts at data, acts in reasoning, manifests in tool use. MAESTRO makes those chains visible.
Not every theoretical threat is a relevant one. We rate impact and likelihood against your concrete architecture — and deliver a roadmap that fits your actual risks.
When a MAESTRO threat model makes sense
Four typical situations where a structured threat model makes the difference between a thought-through and a reactive security strategy.
How we work.
Four structured phases — from architecture analysis through layer mapping to a prioritised mitigation roadmap.
What you get.
Concrete, comprehensible deliverables — as living documents, not drawer paper.
Not every threat model answers the same question.
Classical threat modeling, LLM threat catalogs and MAESTRO complement each other — they don't replace each other.
- Spoofing, tampering, repudiation, info disclosure, DoS, elevation
- Built for deterministic software
- Answers the classical, not the AI-specific
- Prompt injection, insecure output, training data poisoning
- Focus on the language model as a component
- Answers the model, not the architecture
- 7 layers: foundation · data · frameworks · infrastructure · observability · security · ecosystem
- Cross-layer attacks and multi-agent threats made visible
- Answers the system — and what to protect
"A good threat model changes architecture decisions before they become expensive bad decisions. MAESTRO is the framework Agentic AI actually deserves."