audit

audit is a skill for Claude Code from xChechi/xche-ai-app-security-pack. It costs 32 tokens per session (571 once invoked), scanned A, original, MIT.

A security review command for selected code or recent changes, based on the xChe AI-App Security policy. It checks areas such as secrets, injection, access control, login sessions, APIs, and network requests.

In plain words
What is it for?
It is for reviewing hardcoded credentials, unsafe database or HTML handling, missing permissions, weak cookies or passwords, risky uploads, SSRF, open redirects, and related issues.
Why use it?
It gives developers a prioritized list of security problems and suggested fixes before vulnerable code reaches users.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Part of the ai-app-security plugin — 2 skills, 1 hook shipped together

Good fit It is for reviewing hardcoded credentials, unsafe database or HTML handling, missing permissions, weak cookies or passwords, risky uploads, SSRF, open redirects, and related issues.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xchechi/xche-ai-app-security-pack/audit
Install

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.

Any agent
npx skills add xChechi/xche-ai-app-security-pack --skill audit
Clone the repo
git clone --depth 1 https://github.com/xChechi/xche-ai-app-security-pack

Made for: Claude Code.

Or install ai-app-security, the plugin that ships this one along with the rest of its 2 skills, 1 hook.

Wrote 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.

agentmods badge for audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/xchechi/xche-ai-app-security-pack/audit/github.svg)](https://agentmods.dev/skills/xchechi/xche-ai-app-security-pack/audit)
Your own site
<a href="https://agentmods.dev/skills/xchechi/xche-ai-app-security-pack/audit"><img src="https://agentmods.dev/badge/skills/xchechi/xche-ai-app-security-pack/audit/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.

agentmods 80×15 button for audit

Your own site · 80×15
<a href="https://agentmods.dev/skills/xchechi/xche-ai-app-security-pack/audit"><img src="https://agentmods.dev/badge/skills/xchechi/xche-ai-app-security-pack/audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 571 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.00571
Opus 5 $0.00016 $0.00285
Sonnet 5 $0.00006 $0.00114
Haiku 4.5 $0.00003 $0.00057

Measured 9d ago against content hash c910262c8bd3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

audit 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 9d 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.

plugins/ai-app-security/skills/audit/SKILL.md · 36 lines

How it starts

The opening of the file, as written. The whole thing — 36 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Security audit

Audit the code I've selected (or the most recent changes) for security issues. Use the checklist below. For full rationale, see reference/SECURITY.md in this plugin directory.

Check for

  1. Secrets — hardcoded keys/tokens/DB URLs; secrets in client code, logs, URLs, or errors; missing .env gitignore.
  2. Injection — string-built SQL (concatenation/f-strings/.format()/%); dangerouslySetInnerHTML/innerHTML/v-html/document.write with user input; shell/eval/unsafe deserialization; missing server-side validation.
  3. Access control — endpoints that read/write objects without verifying ownership/permission server-side (IDOR/BOLA); missing tenant scoping; unprotected admin/debug routes; mass assignment of role/owner/price/tenant.
  4. Auth & sessions — weak password hashing (MD5/SHA-1/unsalted); no rate limiting on auth; cookies missing HttpOnly/Secure/SameSite; secrets/PII in JWT or signed-cookie payloads.
  5. API & network — missing security headers (CSP/HSTS/X-Frame-Options/nosniff); wildcard CORS on authed endpoints; SSRF (user-controlled request targets, no private-range block); open redirect; unsafe file uploads; path traversal.
  6. Dependencies — hallucinated/slopsquatted package names; unpinned versions; known-vulnerable deps.
  7. LLM/MCP — model/tool output used without validation or encoding; un-sandboxed MCP servers; commands not allow-listed by absolute path; secrets/unminimized PII sent to models; high-impact actions without human confirmation.
  8. Errors/logging — stack traces, SQL, or internal paths leaked to clients; secrets/PII in logs.

Output format

For each finding:

  • Severity: Critical / High / Medium / Low
  • Location: file:line
  • Issue: one sentence
  • Fix: the concrete change (show the corrected pattern)

Order findings by severity. Be concise and actionable. If nothing is found in a category, skip it rather than padding the report.

This is a baseline review, not a guarantee. Business-logic flaws and novel issues still need human judgment. For money/auth/PII code, recommend a full audit.

Read the full file on GitHub · 36 lines

Changes

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.

  1. 9d ago First seen · 36 lines · 32 tokens per session scan A c910262c8bd3

Subscribe to this mod's changes

audit is a skill published in the GitHub repository xChechi/xche-ai-app-security-pack (5 stars, last pushed 2mo ago), licensed MIT. It adds 32 tokens to every session and 571 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.

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