Borrowing it
Nothing to install: this file belongs to brovar/10x-pentest. 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/brovar/10x-pentest/main/.github/skills/pt-threat-model/SKILL.mdgit clone --depth 1 https://github.com/brovar/10x-pentestWrote 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/brovar/10x-pentest/pt-threat-model)<a href="https://agentmods.dev/skills/brovar/10x-pentest/pt-threat-model"><img src="https://agentmods.dev/badge/skills/brovar/10x-pentest/pt-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/brovar/10x-pentest/pt-threat-model"><img src="https://agentmods.dev/badge/skills/brovar/10x-pentest/pt-threat-model.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 | $0.00104 | $0.01626 |
| Opus 5 | $0.00052 | $0.00813 |
| Sonnet 5 | $0.00021 | $0.00325 |
| Haiku 4.5 | $0.00010 | $0.00163 |
Grade A, and why
pt-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.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/pt-threat-model — Threat Modeling (Stage 2)
Turn "what exists" into "what to test." Decompose the target with STRIDE per trust boundary, build
attacker-goal attack trees, map to MITRE ATT&CK, and derive a prioritized objective
register. Writes threat-model.md (the reasoning artifact) and test-objectives.md — the living
coverage ledger that drives both testing stages and is the single source of coverage truth
(test-objectives-schema.md).
When to use, when to skip
- Use after recon, to produce the test objectives that drive Stages 3–4.
- Skip never on the happy path (both testing stages depend on the register). On a re-run, only amend — see the resume rule; do not regenerate over a ledger the testing stages have written.
Initial Response
- With
<engagement-id>: proceed to Step 0. - Without: print
Usage: /pt-threat-model <engagement-id>.and STOP.
Inputs
target-profile.md+attack-surface.md— [blocking] (validated pertarget-profile-schema§7).scope.md— [blocking] (readiness ≠ blocked; threats stay in scope; supplies assetcriticality).foundation/threat-library.md,foundation/standards/— [optional] reference.
Process
Step 0: Validate inputs + resume
Validate scope + the recon pair (target_classes ⊆ vocab; every A-NNN mapped or gapped;
surface_confidence set). Failure ⇒ STOP. Resume (protects the living ledger): if
test-objectives.md exists, the ## Coverage ledger may already carry statuses written by the
testing stages — never reset it. Amend ## Objectives / ## Surface coverage and append new
TM-NNN (seed only the new rows at pending). A full ledger reset is a retest-only operation
(pt-new --from seeding), not this skill.
Step 1: Decompose & model → threat-model.md
From the trust boundaries (TB-NNN) and surface (S-NNN): apply STRIDE per element; build
attack trees for the goals that matter given asset criticality; map each threat to MITRE
ATT&CK (ATLAS for ai-llm). Run the mandatory abuse/authz lens — for any surface with auth,
input, secrets, or costly operations, include ≥1 of: broken authorization (IDOR / privesc),
injection / validation parity, secret/PII leakage, resource abuse.
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 · 115 lines · 0 tokens per session scan A 5232208ce769
pt-threat-model is a skill published in the GitHub repository brovar/10x-pentest (3 stars, last pushed 29d ago), licensed Apache-2.0. It adds 104 tokens to every session and 1,626 once invoked, about $0.0005 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 2026-08-31.
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