threat-modeler
SkillSecurityPerforms proactive, pre-implementation threat modeling (STRIDE-style) for a feature or system before it's built. Use when designing something new that touches user data, auth, money, or external input, before writing code.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the threat-modeler skill
What this skill tells your AI
The instructions your AI receives, as published by codebygarv/ai-skills in skills/security/threat-modeler/SKILL.md and read by ahel’s review.
Purpose
Identify likely threats and attack surfaces for a feature or system before it's built, so mitigations are designed in from the start rather than patched on after a Security Auditor review finds them in finished code.
When to Use
- Designing a new feature that touches user data, authentication, payments, or external/untrusted input.
- Before finalizing an architecture that introduces a new trust boundary (a new service, a new external integration, a new user-facing input).
- The user asks for a "threat model" or "what could go wrong from a security angle" on something not yet built.
Differs from Security Auditor: that skill reviews existing code for concrete vulnerabilities; this skill reasons about a design before code exists, to catch classes of risk while they're still cheap to address.
What to Analyze / Do
- Identify assets — what's actually worth protecting here (user credentials, PII, payment data, business logic that could be abused).
- Identify trust boundaries — every place data crosses from one trust level to another (client → server, service → service, user input → database).
- Apply STRIDE per boundary — for each boundary, consider: Spoofing, Tampering, Repudiation, Information disclosure, Denial of service, Elevation of privilege. Not every category applies everywhere — skip what's clearly irrelevant rather than padding.
- Rank by realistic likelihood × impact — a theoretically possible but operationally implausible threat matters less than a highly likely one; say which is which.
- Propose concrete mitigations — tied to the specific threat, not generic "add security" advice.
Output Format
- Assets and trust boundaries identified, briefly.
- A table or list: Threat → STRIDE category → Likelihood/Impact → Mitigation.
- Flag the 2-3 highest-priority threats explicitly, separate from the full list, so they don't get lost among lower-priority ones.
Avoid
- Generating a threat for every STRIDE category at every boundary regardless of relevance — that produces noise, not signal.
- Vague mitigations ("validate input better") — name the specific validation/control.
- Threat-modeling code that already exists and can be concretely reviewed — that's Security Auditor's job.
Signals
- GitHub stars
- 25
- Forks
- 1
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
threat-modeler-codebygarv- Source
- github.com/codebygarv/ai-skills