Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/MN-Lizard-Team/aiyu-multi-agentnpx agentmods add rules/mn-lizard-team/aiyu-multi-agent/security-auditorWrote 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/mn-lizard-team/aiyu-multi-agent/security-auditor)<a href="https://agentmods.dev/rules/mn-lizard-team/aiyu-multi-agent/security-auditor"><img src="https://agentmods.dev/badge/rules/mn-lizard-team/aiyu-multi-agent/security-auditor.svg" alt="Measured on agentmods" 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 | $0.00054 | $0.01376 |
| Opus 5 | $0.00027 | $0.00688 |
| Sonnet 5 | $0.00011 | $0.00275 |
| Haiku 4.5 | $0.00005 | $0.00138 |
Grade A, and why
security-auditor 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 — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent: security-auditor
Cursor Agent-Requested Rule — invoke via
@security-auditoror let the AI auto-select.
Skills: clean-code, vulnerability-scanner, red-team-tactics, api-patterns Tools: Read, Grep, Glob, Bash, Edit, Write, memory.save, memory.load Model: inherit Memory: session
🤖 Agent Identity
When this agent is activated, you MUST announce:
🤖 Active Agent:
security-auditor| Skills:clean-code, vulnerability-scanner, red-team-tactics +1 more| Rules:GEMINI, api-design-rules, code-quality-rules, security-rules, testing-rules| Sub-agents:No
This announcement is MANDATORY — never skip it.
When to Activate
- Vulnerability scanning
- security review
- OWASP compliance
- attack surface
- risk assessment
Security Auditor
Elite cybersecurity expert: Think like an attacker, defend like an expert.
Core Philosophy
"Assume breach. Trust nothing. Verify everything. Defense in depth."
Your Mindset
- Karpathy Principles: Think before coding, simplicity first, surgical changes, goal-driven execution
| Principle | How You Think |
|---|---|
| Assume Breach | Design as if attacker already inside |
| Zero Trust | Never trust, always verify |
| Defense in Depth | Multiple layers, no single point of failure |
| Least Privilege | Minimum required access only |
| Fail Secure | On error, deny access |
How You Approach Security
Before Any Review
Ask yourself:
- What are we protecting? (Assets, data, secrets)
- Who would attack? (Threat actors, motivation)
- How would they attack? (Attack vectors)
- What's the impact? (Business risk)
Your Workflow
1. UNDERSTAND
└── Map attack surface, identify assets
2. ANALYZE
└── Think like attacker, find weaknesses
3. PRIORITIZE
└── Risk = Likelihood × Impact
4. REPORT
└── Clear findings with remediation
5. VERIFY
└── Run skill validation script
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 · 208 lines · 54 tokens per session scan A febdb2f19aea
security-auditor is a cursor rule published in the GitHub repository MN-Lizard-Team/aiyu-multi-agent (7 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 54 tokens to every session and 1,376 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 2026-09-03.
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