What is AI-Native Threat Modeling?
AI-native threat modeling describes tools and workflows that embed machine learning and large language models directly into the threat modeling lifecycle. Instead of manually drawing diagrams on whiteboards and listing threats in spreadsheets, security teams feed architecture diagrams, code, and context into AI copilots that generate and maintain threat models as systems evolve.
The shift is fundamental. Traditional threat modeling happened once, maybe during design. AI-native threat modeling runs continuously.
The Three Frameworks You Need to Know
STRIDE
The classic. Focuses on six threat categories: Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, and Elevation of Privilege.
PASTA
A seven-step, risk-centric methodology that connects technical threats to business impact.
MAESTRO
The new framework. Released in February 2025 by the Cloud Security Alliance, built specifically for agentic AI systems.
Top AI-Powered Threat Modeling Tools for 2026
STRIDE GPT (Open Source)
Uses GPT-class and other LLMs to generate STRIDE-based threat models and attack trees from application descriptions.
IriusRisk (SaaS)
Cloud-based threat modeling platform with customizable threat libraries.
