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 agentmods add rules/ensingm2/ai-threat-modeling-rulesets/cursorrulesgit clone --depth 1 https://github.com/ensingm2/AI-threat-modeling-rulesetsWhat 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 | $0.00945 | $0.00945 |
| Opus 5 | $0.00473 | $0.00473 |
| Sonnet 5 | $0.00189 | $0.00189 |
| Haiku 4.5 | $0.00094 | $0.00094 |
Grade A, and why
cursorrules 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 2d 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Modeling Framework
Project: LLM Instruction Sets for Threat Modeling
Creator: Mike Ensing ([email protected])
⚠️ MANDATORY STARTUP SELECTIONS (BEFORE ANY WORK)
CRITICAL: You MUST ask BOTH questions before beginning Stage 1. This is absolute and non-negotiable.
Step 1: Ask BOTH Questions (USE THIS EXACT SCRIPT - MANDATORY)
Copy this prompt VERBATIM when starting a threat model:
Before we begin, I need two selections:
1. Operational Mode:
- Collaborative Mode: Active user engagement, clarifying questions, stage approvals
- Automatic Mode: Autonomous operation, reasonable assumptions, no user interaction
2. Critic Review Mode:
- With Critic Review: Each stage undergoes adversarial quality validation
- Without Critic Review (Recommended): Stages proceed directly without separate validation phases
Important Note: Critic Review mode will be especially valuable when multi-agent support is added, enabling a separate agent to perform independent validation. For single-agent runs, the benefit of self-critique is generally not worth the increase in runtime and API requests. Recommendation: Without Critic Review unless you have a specific need for it.
Please specify: [Collaborative/Automatic] and [With Critic/Without Critic]
Step 2: Load mode file and confirm
- Load
modes/collaborative-mode.mdORmodes/automatic-mode.md - Confirm BOTH selections before proceeding
Step 3: Begin Stage 1
PROHIBITED:
- ❌ Starting Stage 1 without asking about operational mode
- ❌ Starting Stage 1 without asking about critic review mode
- ❌ Assuming either preference without explicit user selection
- ❌ Asking about mode but forgetting to ask about critic review
- ❌ Using your own wording instead of the exact script above
- ❌ Asking the two questions in separate prompts (MUST be combined)
Quick Reference
- Read:
.ai-instructions/core/entry-point.md - Read:
.ai-instructions/skills/workflow-guide.md - ASK USER BOTH: Operational mode + Critic review mode (see above)
- Load:
.ai-instructions/modes/[selected-mode].md - Confirm selections
- Read ALL user-provided source files (enumerate directories, read every file - no exceptions)
- Begin Stage 1
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.
- 2d ago First seen · 95 lines · 945 tokens per session scan A 601c17e27483
cursorrules is a cursor rule published in the GitHub repository ensingm2/AI-threat-modeling-rulesets (12 stars, last pushed 6mo ago), licensed MIT. It adds 945 tokens to every session, about $0.0047 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.
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angular-20
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dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
cli-error-handling
CLI command error handling patterns.
prefer-direct-imports-over-module-mocks
Prefer extracting a testable core over vi.mock / vi.resetModules when unit tests need to reach production logic entangled with config, env, or singletons.
control-plane-descriptors
Control plane descriptor and instance implementation patterns.
family-instance-domain-actions
Family instance domain action implementation patterns.