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threat-modelerlisted

Build a real threat model for a codebase, service, or feature — before the code review, before the pen test, before launch. Picks the right frame (STRIDE for systems, attack-tree for features, abuser-stories for product flows), works through assets / actors / entry points / trust boundaries via interview + code-read, and produces a structured THREAT_MODEL.md that downstream skills can use to scope a targeted scan. Use when the user says "threat model this", "what's the attack surface", "do a STRIDE analysis", "what could go wrong here", "model the threats", or before any launch touching auth, payments, PII, or multi-tenancy.
ak-ship/fullstack-agent-skills · ★ 0 · AI & Automation · score 72
Install: claude install-skill ak-ship/fullstack-agent-skills
# threat-modeler — figure out what to defend before you defend it ## When to use this skill Trigger when the user wants a *planned* security view, not a generic scan. Strong signals: - "threat model this", "do a STRIDE analysis", "what's the attack surface" - "what could an attacker do here" - Before any new feature touching auth, payments, file uploads, PII, multi-tenancy, or webhooks - Before a SOC 2 / ISO 27001 / pen-test engagement - A new service is being designed and there's no security context yet Do *not* trigger for: a static code review (use `security-sentinel`), incident response (you need a responder), or generic "make this secure" requests where no specific surface has been picked. Pin a scope first. ## The output contract A `THREAT_MODEL.md` file with two layers: 1. **A machine-readable section** (front matter or JSON block) — downstream skills (`security-sentinel`, `code-auditor`) can parse it to scope what they look for. Lists assets, actors, entry points, trust boundaries, and threats with severity scores. 2. **A human-readable section** — the actual narrative. A new engineer should be able to read it in 15 minutes and understand what's worth attacking, what's worth defending, and where the team has *deliberately* accepted a risk. Plus three concrete deliverables alongside the doc: - An **assumption log** — every claim the model rests on, so the next reviewer can verify or invalidate - An **open-questions list** — the things the interview couldn't re