Threat Model Agent
AI-Native Threat Analysis
The Threat Model Agent maps your AI system's semantic attack surface—endpoints, fuzzy trust boundaries, and intent surfaces—then generates a concrete library of attack scenarios ready for red team execution. Built for how AI systems actually fail, not how traditional software does.
Why STRIDE Fails AI SystemsSee It In ActionCapabilities
How It Works
Describe or import your AI system architecture—LLM, RAG, agent, edge deployment
Agent enumerates every endpoint: user prompts, retrieved documents, tool outputs, memory, inter-agent messages
Semantic boundaries are mapped: where does trust change, and how can those changes be exploited?
For agentic systems, intent surfaces are analyzed: what goals can be redirected, what tools can be abused?
Concrete attack scenarios are generated for each identified exposure and risk-ranked by blast radius
Scenarios are packaged as a red team playbook, ready for adversarial execution
Use Cases
Pre-Deployment Validation
Before shipping an LLM feature or agentic system, understand the semantic attack surface and get a playbook for your red team.
Agentic System Security
For agents with tool access, map what the agent can be made to do—not just what it can be made to say.
RAG Pipeline Analysis
Identify indirect injection vectors, knowledge base poisoning risks, and retrieval manipulation attacks.
Compliance Documentation
Generate threat model artifacts for SOC 2, ISO 27001, and AI-specific frameworks with evidence of adversarial analysis.
Ready to Deploy Threat Model Agent?
See how Threat Model Agent works with the rest of the ZIVIS platform to provide comprehensive security coverage.
Don't Wait for an AI Security Incident to Act
Tell us about your AI program and we'll show you where the gaps are.
