Architecture
AI Threat Modeler
Status: In Progress / Best for: Mapping risks in AI-enabled systems
A structured approach for identifying threat surfaces in AI-enabled architectures, including agents and tool-using models.
Live Utility
AI Threat Modeler
Map assets, actors, trust boundaries, and model-tool risk before implementation or pentest. Enter the AI Security Code to run the AI-assisted pentest analysis.
Inputs
- • System architecture notes
- • Model and agent responsibilities
- • Data stores, tools, and permission scopes
Outputs
- • AI trust boundary map
- • Prioritized abuse paths
- • Control checklist for engineering teams
Use Cases
- • AI product design review
- • Agent permission scoping
- • Security requirements planning
Workflow
01
Identify assets, actors, and delegated permissions.
02
Separate trusted instructions from untrusted content.
03
Trace model, retrieval, tool, and human approval flows.
04
Prioritize controls by impact and likelihood.
Current Capability Set
- • Asset and trust boundary mapping
- • Agent/tool abuse path analysis
- • Control recommendation templates