Borrowing it
Nothing to install: this file belongs to bex-co/bex. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/bex-co/bex/main/.claude/skills/security-audit/SKILL.mdgit clone --depth 1 https://github.com/bex-co/bexWrote 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/bex-co/bex/security-audit)<a href="https://agentmods.dev/skills/bex-co/bex/security-audit"><img src="https://agentmods.dev/badge/skills/bex-co/bex/security-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.
<a href="https://agentmods.dev/skills/bex-co/bex/security-audit"><img src="https://agentmods.dev/badge/skills/bex-co/bex/security-audit.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00070 | $0.02612 |
| Opus 5.5 | $0.00028 | $0.01045 |
| Sonnet 5.5 | $0.00014 | $0.00522 |
| Haiku 4.5 | $0.00007 | $0.00261 |
Grade A, and why
security-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 1mo 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.
This is a copy
92% identical to security-audit — 217 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Audit
You are a security auditor. Your job is to find exploitable vulnerabilities with real impact.
Platform terminology
This skill is agent-neutral. In the methodology:
- Task tool means the coding agent's delegation or sub-agent mechanism.
researchagent means a delegated agent optimized for focused codebase exploration and factual verification.generalagent means a delegated agent that can investigate broadly and spawn focused research agents.subagent_typemeans the equivalent delegated-agent role supported by the current platform.
Use the platform's equivalent capabilities while preserving the specified roles, parallelism, prompts, and independence boundaries.
Setup
Before starting, establish two paths:
- Target: the codebase to audit (from the user's request or the current working directory)
- Output directory: where all audit artifacts go. Ask the user if not specified, or default to
~/security-audit-skill/<repo-name>/run-<N>where<N>is the next unused integer (check what exists withls). Create it if it doesn't exist. This ensures multiple runs against the same repo produce separate results.
All files written during the audit go in the output directory:
architecture.md— Phase 1 output, fed into Phase 2 agent promptsREPORT.md— human-readable report (Phase 4)FINDINGS-DETAIL.md— detailed data flows for MEDIUM+ findings (Phase 4)findings.json— machine-readable structured output (Phase 5)
Subagents (Phases 1, 2, 3, 6) do NOT write files — they return results to you via the Task tool. You are responsible for writing all files to the output directory.
Coverage and prior runs
Each audit run explores different code paths depending on which agents find what and where they dig. No single run finds everything. Testing shows the best single run finds roughly half the total vulnerabilities across multiple runs.
If prior runs exist for the same repo (check ~/security-audit-skill/<repo-name>/), read their findings.json files before starting Phase 2. Use them to:
- Skip known findings — don't waste agents re-discovering the same status bypass. Mention prior findings in the report but focus hunting effort on new ground.
- Target gaps — if prior runs focused heavily on injection and auth, weight this run toward business logic, creative attacks, and the wildcard agent. If prior runs missed public endpoints, focus there.
- Resolve disagreements — if prior runs gave conflicting verdicts on the same finding, validate it definitively.
What ships with it
10 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.
- 1mo ago First seen · 120 lines · 70 tokens per session scan A 00143edbbec7
security-audit is a skill published in the GitHub repository bex-co/bex (574 stars, last pushed today), licensed Apache-2.0. It adds 70 tokens to every session and 2,612 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to security-audit, differing in 217 lines, and is treated as a copy.
Other skills, from other repositories
network-rca
Kubernetes network root cause analysis skill powered by Kubeshark MCP. Use this skill whenever the user wants to investigate past incidents, perform retrospective traffic analysis, take or manage traffic snapshots, extract PCAPs, dissect L7 API calls from historical captures, compare traffic patterns over time, detect…
pinchtab-dev
Develop and contribute to the PinchTab project. Use when working on PinchTab source code, adding features, fixing bugs, running tests, or preparing PRs. Triggers on "work on pinchtab", "pinchtab development", "contribute to pinchtab", "fix pinchtab bug", "add pinchtab feature".
code-changes
Workflow for any task that ends in code changes: issue analysis or triage, pull request review comments, features, bug fixes, refactors. Invoke at the start of such a task, before reading or writing code.
code-review
Reviews code for bugs, security issues, and best practices.
debugging-failures
Diagnose a failing Ginkgo suite as an agent — always run with --json-report into a predictable temp/gitignored location, read the terminal verdict line, then use jq to extract structured failure details (name, message, file:line, panic value, captured logs). Covers the panicked-vs-failed trap, panic locations pointing…
printing-press-output-review
Internal sub-skill: agentic review of a printed CLI's sampled command output for plausibility issues that rule-based checks can't encode (substring-match relevance, format bugs, silent source drops, ranking failures). Invoked via the Skill tool by the main printing-press skill at Phase 4.85 and printing-press-polish…