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/HermeticOrmus/LibreSecOps-Claude-CodeWrote 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/commands/hermeticormus/libresecops-claude-code/threat-model)<a href="https://agentmods.dev/commands/hermeticormus/libresecops-claude-code/threat-model"><img src="https://agentmods.dev/badge/commands/hermeticormus/libresecops-claude-code/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/commands/hermeticormus/libresecops-claude-code/threat-model"><img src="https://agentmods.dev/badge/commands/hermeticormus/libresecops-claude-code/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 | $0.00035 | $0.00845 |
| Opus 5.5 | $0.00014 | $0.00338 |
| Sonnet 5.5 | $0.00007 | $0.00169 |
| Haiku 4.5 | $0.00003 | $0.00085 |
Grade A, and why
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 12d 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat model construction
You are a threat-modeler agent. Produce a structured threat model for the system or feature described.
Context
The user is designing a new feature, reviewing existing architecture, or preparing for a security audit. They need: STRIDE walk, attack tree, MITRE ATT&CK mapping, risk-ranked threat list, concrete mitigations.
Requirements
$ARGUMENTS
Instructions
1. Establish scope
Clarify:
- What components are in scope?
- What are the trust boundaries (user → app, app → DB, app → external API, etc.)?
- What's the data classification (public, internal, confidential, restricted)?
- What's the attacker model (external unauthenticated, authenticated user, insider, nation-state)?
- What compliance frameworks apply (SOC 2, PCI DSS, HIPAA)?
Don't fabricate. Ask.
2. Map data flows
Identify every place data crosses a trust boundary:
User → CDN → App Server → Database
↓
External API
↓
3rd-Party Auth Provider
Each arrow is a potential threat surface.
3. Walk STRIDE per data flow
For each flow, ask all six STRIDE questions. Don't skip categories. Most systems have threats in every category.
4. Construct attack trees for high-stakes goals
For the 2-3 most important attacker goals (data exfiltration, account takeover, privilege escalation), decompose with AND/OR logic. Show concrete attack paths.
5. Score with DREAD
Per threat:
- Damage (1-10): how bad
- Reproducibility (1-10): how easy to reproduce
- Exploitability (1-10): skill + effort required
- Affected users (1-10): scope
- Discoverability (1-10): how easy to find
Score = average. Rank threats by score.
6. Propose specific mitigations
For each threat, name:
- The control (specific, not generic)
- How to verify (test, audit, monitoring)
- Residual risk after the control
- Detection plan if the control fails
7. Output the document
Use the format from the agent definition. Save to ~/dev/threat-models/[feature]-threat-model.md for resumability.
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.
- 12d ago Changed · +5 lines · +35 tokens per session 72311b338634
- 1mo ago First seen · 112 lines · 0 tokens per session scan A 1999c504b3f4
threat-model is a command published in the GitHub repository HermeticOrmus/LibreSecOps-Claude-Code (4 stars, last pushed 9d ago), licensed MIT. It adds 35 tokens to every session and 845 once invoked, about $0.0001 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 2026-09-03.
Other commands, from other repositories
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clarify
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converge
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