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 skills add san-npm/skills-ws --skill security-pentestergit clone --depth 1 https://github.com/san-npm/skills-wsWrote 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/san-npm/skills-ws/security-pentester)<a href="https://agentmods.dev/skills/san-npm/skills-ws/security-pentester"><img src="https://agentmods.dev/badge/skills/san-npm/skills-ws/security-pentester/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/san-npm/skills-ws/security-pentester"><img src="https://agentmods.dev/badge/skills/san-npm/skills-ws/security-pentester.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 | $0.00064 | $0.00658 |
| Opus 5 | $0.00032 | $0.00329 |
| Sonnet 5 | $0.00013 | $0.00132 |
| Haiku 4.5 | $0.00006 | $0.00066 |
Grade A, and why
security-pentester 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 5d 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 — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Pentester
Disambiguation: this skill = active offensive testing. For defensive code patterns see
security-hardening. For runtime threat intel / URL+wallet scam scanning seesecurity-sentinel.
Autonomous web application penetration testing driven by an LLM-agent pipeline (Shannon), backed by manual validation. Source-aware analysis combines code reading with live exploitation attempts and prioritizes findings that come with a reproducible proof-of-concept.
This skill is tool-agnostic in principle: Shannon is the reference automated driver, but the workflow (recon → analyze → exploit → triage → remediate → regression-test) and every remediation playbook below apply to any pentest engagement (manual, Burp/ZAP-driven, or other agents).
Scope first. Only run against applications you own or have explicit written authorization to test, and never against production. See §8 for the full rules of engagement.
Safety gate
Before executing commands or changing external systems, confirm scope, credentials, target environment, rollback, and required approval. Pin and verify third-party artifacts; never expose secrets to client code or logs.
Reference guide
Read only the references needed for the current request:
- Core Principle: references/core-principle.md
- 1. Vulnerability Coverage: references/1-vulnerability-coverage.md
- 2. Running a Pentest: references/2-running-a-pentest.md
- 3. Understanding the Pipeline: references/3-understanding-the-pipeline.md
- 4. Interpreting Reports: references/4-interpreting-reports.md
- [CRITICAL] SQL Injection in /api/users/search: references/critical-sql-injection-in-api-users-search.md
- 4a. Remediation Playbooks: references/4a-remediation-playbooks.md
- 5. CI/CD Integration: references/5-ci-cd-integration.md
- 6. Post-Pentest Workflow: references/6-post-pentest-workflow.md
- 7. What Shannon Doesn't Cover: references/7-what-shannon-doesn-t-cover.md
- 8. Safe Testing Practices: references/8-safe-testing-practices.md
What ships with it
12 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.
- agents/openai.yaml 190 B
- references/1-vulnerability-coverage.md 2.3 KB
- references/2-running-a-pentest.md 3.5 KB
- references/3-understanding-the-pipeline.md 2.1 KB
- references/4-interpreting-reports.md 687 B
- references/4a-remediation-playbooks.md 6.0 KB
- references/5-ci-cd-integration.md 7.4 KB
- references/6-post-pentest-workflow.md 1.9 KB
- references/7-what-shannon-doesn-t-cover.md 1.6 KB
- references/8-safe-testing-practices.md 4.2 KB
- references/core-principle.md 718 B
- references/critical-sql-injection-in-api-users-search.md 1.4 KB
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.
- 5d ago First seen · 34 lines · 64 tokens per session scan A 46967cc60f01
security-pentester is a skill published in the GitHub repository san-npm/skills-ws (2 stars, last pushed 5d ago), licensed MIT. It adds 64 tokens to every session and 658 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 2026-09-07.
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