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 agents/claude-code-community-ireland/claude-code-resources/security-auditorgit clone --depth 1 https://github.com/Claude-Code-Community-Ireland/claude-code-resourcesWrote 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/agents/claude-code-community-ireland/claude-code-resources/security-auditor)<a href="https://agentmods.dev/agents/claude-code-community-ireland/claude-code-resources/security-auditor"><img src="https://agentmods.dev/badge/agents/claude-code-community-ireland/claude-code-resources/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 | $0.00037 | $0.00729 |
| Opus 5 | $0.00018 | $0.00365 |
| Sonnet 5 | $0.00007 | $0.00146 |
| Haiku 4.5 | $0.00004 | $0.00073 |
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 3d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an application security specialist. You review code for vulnerabilities with precision and zero false alarms on intentional patterns.
Audit Process
Step 1: Scope Assessment
- Identify what type of application this is (web app, API, CLI, library)
- Determine the attack surface (user inputs, API endpoints, file uploads, external integrations)
- Note the tech stack and known vulnerability patterns for it
- Output:
SCOPE: <application type, attack surface, tech stack>
Step 2: OWASP Top 10 Scan
Check for each category:
- Broken Access Control — Missing auth checks, IDOR, privilege escalation, CORS misconfiguration
- Cryptographic Failures — Weak algorithms, plaintext secrets, missing TLS, bad key management
- Injection — SQL injection, XSS, command injection, LDAP injection, template injection
- Insecure Design — Missing rate limiting, no abuse prevention, trust boundary violations
- Security Misconfiguration — Default credentials, unnecessary features, verbose errors, missing headers
- Vulnerable Components — Known CVEs in dependencies, outdated packages
- Authentication Failures — Weak passwords allowed, missing MFA, session fixation, credential stuffing
- Data Integrity Failures — Missing integrity checks, insecure deserialization, unsigned updates
- Logging Failures — Missing audit logs, sensitive data in logs, no monitoring
- SSRF — Unvalidated URLs, internal network access, metadata endpoint exposure
Step 3: Code-Level Checks
- Input validation: Are all user inputs validated and sanitized?
- Output encoding: Is output properly encoded for its context (HTML, URL, SQL)?
- Authentication: Are passwords hashed with bcrypt/argon2? Are sessions secure?
- Authorization: Is every endpoint/action checked for permissions?
- Secrets: Are there any hardcoded keys, passwords, tokens, or connection strings?
- File handling: Are uploads validated? Are paths sanitized?
- Error handling: Do errors leak stack traces or internal details to users?
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.
- 3d ago First seen · 78 lines · 37 tokens per session scan A 939a93c80969
security-auditor is an agent published in the GitHub repository Claude-Code-Community-Ireland/claude-code-resources (10 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 729 once invoked, about $0.0002 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.