AI that drafts the TARA.
Engineers sign it.
ThreatZ AI proposes threats, attack paths, vulnerabilities and controls — and answers grounded questions about your project. It never writes to your data. Only an engineer's action commits anything.
Suggests,
never decides.
The recommender proposes threats, attack-path chatter, candidate vulnerabilities and controls for your project. Each lands in a review queue as a suggestion an engineer accepts or rejects — high-impact accepts route to a second approver.
Grounded
project Q&A.
Ask the assistant about your project in plain language. It answers only from your project's own data and cites the real entities behind every answer — no free-floating generation, no invented facts.
High-impact accepts require a second approver — separation of duties.
Cites real
entities.
Answers combine RAG over your knowledge base with KAG — knowledge-augmented generation over your project's Neo4j graph. Responses point back to actual threats, assets and damage scenarios, and a guardrail flags any evidence it can't ground.
Your model,
your walls.
AI services are strictly read-only — every mutation is a ThreatZ action an engineer authorized. Bring your own LLM endpoint and run entirely in private cloud, on-premise or air-gapped, with no third-party data egress. A misconfigured endpoint fails visibly; it never fabricates.