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 skills/codebygarv/ai-skills/security-auditornpx skills add codebygarv/Ai-skills --skill security-auditorgit clone --depth 1 https://github.com/codebygarv/Ai-skillsWrote 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/skills/codebygarv/ai-skills/security-auditor)<a href="https://agentmods.dev/skills/codebygarv/ai-skills/security-auditor"><img src="https://agentmods.dev/badge/skills/codebygarv/ai-skills/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 | $0.00048 | $0.00604 |
| Opus 5 | $0.00024 | $0.00302 |
| Sonnet 5 | $0.00010 | $0.00121 |
| Haiku 4.5 | $0.00005 | $0.00060 |
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 4d 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 — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Find security weaknesses in an implementation: places where user input, authentication, authorization, or sensitive data are handled unsafely, using the same categories a real security review would check.
When to Use
- Before shipping any code that handles user input, authentication, authorization, payments, or PII.
- Reviewing code that constructs queries, commands, or file paths from external input.
- The user asks for a "security review" or "security audit."
This skill is for defensive review of code you own or are authorized to review — not for developing exploits against systems you don't have permission to test.
What to Analyze
- Injection — SQL/NoSQL/command/template injection wherever user input reaches a query, shell command, or template without parameterization/escaping.
- Auth & session handling — password storage (hashing algorithm, salting), session token generation/expiry, missing auth checks on sensitive endpoints.
- Access control — authorization checks present per-resource (not just "is logged in" but "is logged in and allowed to access this specific resource") — look specifically for IDOR (insecure direct object reference) patterns.
- Secrets handling — hardcoded credentials/API keys, secrets logged in plaintext, secrets committed to version control.
- Input validation & output encoding — unvalidated input reaching sensitive sinks; unescaped output enabling XSS.
- Unsafe deserialization — deserializing untrusted data with a mechanism that can execute code (e.g. unsafe
pickle,eval, certain YAML loaders). - Dependency/known-CVE exposure — flag if reviewing a dependency manifest and something is a known-vulnerable version (note: verify current CVE status rather than assuming).
Output Format
- Findings grouped by severity: Critical (remote code execution, auth bypass, data exposure) → High (injection, IDOR) → Medium (weak crypto, missing rate limiting) → Low (defense-in-depth gaps).
- Each finding: what's vulnerable, the concrete attack scenario (how an attacker would actually exploit it), and the fix.
- Note explicitly if a finding requires further verification (e.g., "confirm this endpoint isn't also protected by a gateway-level check").
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 39 lines · 48 tokens per session scan A 0d714df9aaa8
security-auditor is a skill published in the GitHub repository codebygarv/Ai-skills (24 stars, last pushed 14d ago), licensed MIT. It adds 48 tokens to every session and 604 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 2026-08-30.
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