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 Haohao-end/openagent --skill security-threat-modelgit clone --depth 1 https://github.com/Haohao-end/openagentWrote 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/haohao-end/openagent/security-threat-model)<a href="https://agentmods.dev/skills/haohao-end/openagent/security-threat-model"><img src="https://agentmods.dev/badge/skills/haohao-end/openagent/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/haohao-end/openagent/security-threat-model"><img src="https://agentmods.dev/badge/skills/haohao-end/openagent/security-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 | $0.00082 | $0.01108 |
| Opus 5 | $0.00041 | $0.00554 |
| Sonnet 5 | $0.00016 | $0.00222 |
| Haiku 4.5 | $0.00008 | $0.00111 |
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 9d 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.
This is a copy
100% identical to security-threat-model — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Model Source Code Repo
Deliver an actionable AppSec-grade threat model that is specific to the repository or a project path, not a generic checklist. Anchor every architectural claim to evidence in the repo and keep assumptions explicit. Prioritizing realistic attacker goals and concrete impacts over generic checklists.
Quick start
- Collect (or infer) inputs:
- Repo root path and any in-scope paths.
- Intended usage, deployment model, internet exposure, and auth expectations (if known).
- Any existing repository summary or architecture spec.
- Use prompts in
references/prompt-template.mdto generate a repository summary. - Follow the required output contract in
references/prompt-template.md. Use it verbatim when possible.
Workflow
1) Scope and extract the system model
- Identify primary components, data stores, and external integrations from the repo summary.
- Identify how the system runs (server, CLI, library, worker) and its entrypoints.
- Separate runtime behavior from CI/build/dev tooling and from tests/examples.
- Map the in-scope locations to those components and exclude out-of-scope items explicitly.
- Do not claim components, flows, or controls without evidence.
2) Derive boundaries, assets, and entry points
- Enumerate trust boundaries as concrete edges between components, noting protocol, auth, encryption, validation, and rate limiting.
- List assets that drive risk (data, credentials, models, config, compute resources, audit logs).
- Identify entry points (endpoints, upload surfaces, parsers/decoders, job triggers, admin tooling, logging/error sinks).
3) Calibrate assets and attacker capabilities
- List the assets that drive risk (credentials, PII, integrity-critical state, availability-critical components, build artifacts).
- Describe realistic attacker capabilities based on exposure and intended usage.
- Explicitly note non-capabilities to avoid inflated severity.
4) Enumerate threats as abuse paths
- Prefer attacker goals that map to assets and boundaries (exfiltration, privilege escalation, integrity compromise, denial of service).
- Classify each threat and tie it to impacted assets.
- Keep the number of threats small but high quality.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 82 lines · 82 tokens per session scan A 1283c0dd62a8
security-threat-model is a skill published in the GitHub repository Haohao-end/openagent (805 stars, last pushed 1mo ago), licensed MIT. It adds 82 tokens to every session and 1,108 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to security-threat-model, differing in 0 lines, and is treated as a copy.
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