Borrowing it
Nothing to install: this file belongs to mtarcure/claude-vibe-squad. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mtarcure/claude-vibe-squad/main/.agents/skills/security-threat-model/SKILL.mdgit clone --depth 1 https://github.com/mtarcure/claude-vibe-squadWrote 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/mtarcure/claude-vibe-squad/security-threat-model)<a href="https://agentmods.dev/skills/mtarcure/claude-vibe-squad/security-threat-model"><img src="https://agentmods.dev/badge/skills/mtarcure/claude-vibe-squad/security-threat-model/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/mtarcure/claude-vibe-squad/security-threat-model"><img src="https://agentmods.dev/badge/skills/mtarcure/claude-vibe-squad/security-threat-model.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00051 | $0.00472 |
| Opus 5 | $0.00026 | $0.00236 |
| Sonnet 5 | $0.00010 | $0.00094 |
| Haiku 4.5 | $0.00005 | $0.00047 |
Grade A, and why
security-threat-model 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 10d 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.
What it actually says
Security Threat Model
Build a threat model that is right-sized to the system and that terminates, rather than one that expands until every mechanism looks unsafe.
Steps
- State the asset: what is actually worth protecting here — data, funds, availability, integrity of a decision — and what its loss would cost.
- State the adversary: capability, position, and motivation. An unbounded adversary produces an unbounded model and no decisions.
- Draw the system as trust zones and the flows that cross them. Every trust-zone crossing is where the model does its work; flows inside a zone rarely are.
- For each crossing, enumerate threats systematically — spoofing, tampering, repudiation, disclosure, denial, elevation — and keep only those the stated adversary can reach.
- Record the existing control for each retained threat and whether it was observed working or merely assumed to exist. Assumed controls are gaps.
- Rank residual risk by asset loss × adversary reach, using
review-severity-ladder, and stop enumerating below the agreed floor. - Decide per residual: mitigate, bound the mechanism, remove the mechanism, or accept with a documented rationale and a revisit condition.
- When the model keeps producing unmitigable criticals on one mechanism, remove or bound that mechanism — chasing an airtight control is the wrong response.
- Write the assumptions down as first-class output; the assumptions are what will be wrong later, and they are what a reviewer should attack.
Acceptance
- Asset, adversary capability, and trust zones are stated before any threat is listed.
- Threats are enumerated per trust-zone crossing and filtered to the stated adversary.
- Every control is marked observed or assumed; assumed controls are treated as gaps.
- Residuals carry an explicit decision — mitigate, bound, remove, or accept with rationale and revisit condition.
- Assumptions are recorded as their own section, and the model terminates at a stated floor.
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.
- 10d ago First seen · 28 lines · 51 tokens per session scan A c196440bb0fc
security-threat-model is a skill published in the GitHub repository mtarcure/claude-vibe-squad (142 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 472 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 2026-08-30.
Other skills, from other repositories
gh-find-prs
Survey open Codewhale PRs and triage each for mergeability and disposition against the real landing branch.
contributor-onboarding
Help a new contributor get productive on this checkout - inspect sync state against main, build, run the repository's exact verification gate, and produce a local what's-new digest. Never fetches, pulls, or modifies a dirty tree on its own. Explicit-only.
codew-release-qa-sweep
Use before claiming Codewhale release work is done: run the full gate sweep and list the manual QA targets.
gh-file-issue
Use when filing a new Codewhale GitHub issue: turn a bug or idea into a well-formed, actionable issue with repro, acceptance criteria, labels, and milestone.
gh-treasure-hunt
Hunt the issue/PR queue for highest value-over-risk wins: clean focused community PRs, already-implemented issues to close, safe quick-fixes.
skill-installer
Install, update, trust, or inspect Codewhale skills from GitHub or local skill folders. Use when the user asks for available skills or wants a community skill installed.