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.
git clone --depth 1 https://github.com/briiirussell/cybersecurity-skillsWrote 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/rules/briiirussell/cybersecurity-skills/threat-modeling)<a href="https://agentmods.dev/rules/briiirussell/cybersecurity-skills/threat-modeling"><img src="https://agentmods.dev/badge/rules/briiirussell/cybersecurity-skills/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/rules/briiirussell/cybersecurity-skills/threat-modeling"><img src="https://agentmods.dev/badge/rules/briiirussell/cybersecurity-skills/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 | $0.00102 | $0.02603 |
| Opus 5.5 | $0.00041 | $0.01041 |
| Sonnet 5.5 | $0.00020 | $0.00521 |
| Haiku 4.5 | $0.00010 | $0.00260 |
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 today.
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 — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeling — Pre-Implementation Security Design
Run a structured threat-modeling session against a proposed feature, system, or architecture. This is the design-time security skill — different from audit (which inspects code that exists). Use this when there's a design doc, a feature spec, an architecture diagram — but not yet code.
When to use:
- New feature touching auth, payments, multi-tenant data, or sensitive PII
- New external integration (third-party API, OAuth provider, webhook receiver)
- New service / microservice being added to the architecture
- Significant refactor of a security-sensitive component
- Before committing to a major architecture decision (event-driven vs request/response, monolith split, AI-feature introduction)
Cross-references: owasp-audit (code-level checklist that lines up with the threats this surfaces), api-audit (API-specific category mapping), iam-audit (identity decisions touch every threat model).
Authorization
Model systems the user owns, builds or is authorized to assess, from designs, diagrams and code they provide. Threat modeling is design analysis; it doesn't test anything. Don't build an attack tree of someone else's product without their authorization.
The four questions
Adam Shostack's framing — every threat model answers these four:
- What are we working on? (Scope and model)
- What can go wrong? (Threats)
- What are we going to do about it? (Mitigations)
- Did we do a good job? (Validation)
The rest of this skill walks through each in order.
Step 1 — What are we working on?
Produce a Data Flow Diagram (DFD) at one of three levels:
- Level 0 — Context diagram. One bubble for the system, lines to every external entity (users, third-party APIs, internal admin tools). Use this when the question is "what does this system even touch?"
- Level 1 — Major processes. Auth service, API gateway, primary data store, payment integration, etc. Use this for most feature-level threat models.
- Level 2 — Detailed component model. Specific endpoints, specific tables, specific queues. Use this for the trickiest parts only.
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.
- today Changed · +4 lines · -4 tokens per session 27f4a6b86969
- 1mo ago First seen · 210 lines · 106 tokens per session scan A 10c5d87cdecb
threat-modeling is a cursor rule published in the GitHub repository briiirussell/cybersecurity-skills (435 stars, last pushed today), licensed MIT. It adds 102 tokens to every session and 2,603 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-30.
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