Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Vimalk0703/shipworthy --skill threat-modelinggit clone --depth 1 https://github.com/Vimalk0703/shipworthyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vimalk0703/shipworthy/threat-modeling)<a href="https://agentmods.dev/skills/vimalk0703/shipworthy/threat-modeling"><img src="https://agentmods.dev/badge/skills/vimalk0703/shipworthy/threat-modeling/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vimalk0703/shipworthy/threat-modeling"><img src="https://agentmods.dev/badge/skills/vimalk0703/shipworthy/threat-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.03510 |
| Opus 5 | $0.00029 | $0.01755 |
| Sonnet 5 | $0.00012 | $0.00702 |
| Haiku 4.5 | $0.00006 | $0.00351 |
Grade A, and why
threat-modeling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeling with STRIDE
Core Principle
Threat modeling is a structured way to think about what can go wrong with a system's security before an attacker finds out. Do it during design, not after launch. The STRIDE framework gives you six categories of threats to systematically evaluate.
When to Threat Model
- Before building any new service or feature that handles user data.
- When adding a new external integration or API.
- When changing authentication or authorization logic.
- When introducing a new data store or data flow.
- During design document review (see the design-documents skill).
- At least annually for existing critical services.
The STRIDE Framework
S -- Spoofing (Pretending to Be Someone Else)
Question to ask: "Can an attacker pretend to be another user, service, or component?"
What to verify:
- All API endpoints require authentication (no accidental public endpoints).
- Authentication tokens are validated on every request, not just at login.
- Service-to-service calls use mutual TLS or signed tokens, not shared secrets.
- Email/SMS-based verification prevents account takeover.
- OAuth redirect URIs are strictly validated (no open redirects).
- API keys are scoped to specific permissions, not full access.
Common mitigations:
- Use strong authentication (OAuth 2.0 + PKCE, SAML, or WebAuthn).
- Implement multi-factor authentication for sensitive operations.
- Use short-lived tokens (15 min access tokens, longer refresh tokens).
- Validate the
aud(audience) claim in JWTs to prevent token reuse across services. - Rotate API keys and credentials on a schedule.
// Verify JWT on every request -- not just presence but validity
function authenticateRequest(req: Request): User {
const token = req.headers['authorization']?.replace('Bearer ', '');
if (!token) throw new AuthError('Missing authentication token');
const payload = jwt.verify(token, publicKey, {
algorithms: ['RS256'],
audience: 'api.myservice.com', // Prevent token reuse from other services
issuer: 'auth.mycompany.com', // Verify who issued the token
});
return { id: payload.sub, roles: payload.roles };
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 376 lines · 58 tokens per session scan A 9bacb868a2d2
threat-modeling is a skill published in the GitHub repository Vimalk0703/shipworthy (7 stars, last pushed 5mo ago), licensed MIT. It adds 58 tokens to every session and 3,510 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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