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/suyogpawar88/Threat-ModelWrote 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/suyogpawar88/threat-model/threat-modeling)<a href="https://agentmods.dev/rules/suyogpawar88/threat-model/threat-modeling"><img src="https://agentmods.dev/badge/rules/suyogpawar88/threat-model/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/suyogpawar88/threat-model/threat-modeling"><img src="https://agentmods.dev/badge/rules/suyogpawar88/threat-model/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 | $0.00055 | $0.00839 |
| Opus 5 | $0.00028 | $0.00419 |
| Sonnet 5 | $0.00011 | $0.00168 |
| Haiku 4.5 | $0.00006 | $0.00084 |
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 8d 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeling Rule
This project ships a full threat-modeling workflow originally packaged as a Claude Code / Cowork
plugin. It works the same way here: read skills/threat-modeling/SKILL.md in full before starting,
and follow it step by step. Do not skip straight to writing a threat list.
What this covers
- STRIDE threat enumeration with Likelihood x Impact business-risk scoring
(
skills/threat-modeling/references/stride-methodology.md) - Optional full 7-stage PASTA process for higher-rigor engagements
(
skills/threat-modeling/references/pasta-methodology.md) - AI/ML/LLM infrastructure threats -- prompt injection, training/RAG data poisoning, model
extraction, excessive agency, insecure output handling, unbounded consumption, etc.
(
skills/threat-modeling/references/ai-threat-taxonomy.md) - OWASP Top 10 (2021), OWASP API Security Top 10 (2023), and OWASP Top 10 for LLM Applications
(2025) mapping for every threat (
skills/threat-modeling/references/owasp-mappings.md) - MITRE ATT&CK (Enterprise) and MITRE ATLAS technique tagging for attack-chain steps
(
skills/threat-modeling/references/mitre-mappings.md) - Compensating-controls, mitigation-assurance, and compliance-gap analysis
(
skills/threat-modeling/references/compensating-controls-and-gaps.md) - Attack-chain / attack-scenario mapping (
skills/threat-modeling/references/attack-chain-mapping.md)
How to run it here
- The four connectors (Jira, Jenkins, ServiceNow, code repo) are registered as MCP servers in
.cursor/mcp.json-- enable them in Cursor's MCP settings and set the referenced environment variables (see.env.example/README.md). None are mandatory; the skill works with whatever subset is configured. - Trigger this rule whenever the user asks to threat model a service, run STRIDE/PASTA, map threats to OWASP or MITRE, or produce a DFD/Word report/Excel risk register for a system -- including AI/LLM/agent systems.
- Follow
skills/threat-modeling/SKILL.mdSteps 1-9 exactly, using the report-data schema atskills/threat-modeling/references/report-data-schema.jsonand the worked examples inskills/threat-modeling/references/examples/(sample_*for a conventional app,sample_ai_*for an AI/RAG/agent system). - Render outputs by running the bundled scripts directly:
python3 scripts/generate_drawio.py <spec.json> <output>.drawio [dfd|threat_model],python3 scripts/build_docx_report.py <report_data.json> <output>.docx,python3 scripts/build_xlsx_report.py <report_data.json> <output>.xlsx. - For large connector payloads, pipe through
python3 scripts/summarize.py --focus "..."first (requiresANTHROPIC_API_KEY) rather than reading raw payloads in full -- seescripts/requirements.txtfor Python dependencies (pip install -r scripts/requirements.txt).
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.
- 8d ago First seen · 54 lines · 55 tokens per session scan A 60f6868f2217
threat-modeling is a cursor rule published in the GitHub repository suyogpawar88/Threat-Model (6 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 839 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 2026-08-31.
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