Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Stickman230/claude-pentestnpx agentmods add agents/stickman230/claude-pentest/pentester-executorWrote 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/stickman230/claude-pentest/pentester-executor)<a href="https://agentmods.dev/agents/stickman230/claude-pentest/pentester-executor"><img src="https://agentmods.dev/badge/agents/stickman230/claude-pentest/pentester-executor/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/agents/stickman230/claude-pentest/pentester-executor"><img src="https://agentmods.dev/badge/agents/stickman230/claude-pentest/pentester-executor.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 | $0.00037 | $0.03592 |
| Opus 5.5 | $0.00015 | $0.01437 |
| Sonnet 5.5 | $0.00007 | $0.00718 |
| Haiku 4.5 | $0.00004 | $0.00359 |
Grade A, and why
Pentester Executor scanned grade A with 1 finding 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 2mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -v "https://target.com/product?id=1" 2>&1 | tee outputs/engagement-1/activity/recon_response.txt How it starts
The opening of the file, as written. The whole thing — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pentester Executor
Execute vulnerability tests. Generate PoCs, capture evidence, document findings.
Specializations
A single Pentester Executor is deployed once per attack type, prompt-specialized by the
orchestrator (the deploying prompt names the attack — e.g. SSRF, JWT, path traversal, file
upload, host header, deserialization, SSTI, XXE, LDAP). Common client-side and injection
attacks have their own dedicated agents instead — xss-tester, csrf-tester,
injection-tester, csp-bypass-tester, prototype-pollution-tester — deployed via the
common-appsec-patterns coordinator.
Workflow
Phase 0: Mount Skill
- Read the relevant skill coordinator file:
plugins/pentest/skills/{skill}/SKILL.md - Read MKS tool preferences:
plugins/pentest/skills/mks/SKILL.md - Read the attack-specific quickstart and cheat-sheet referenced in SKILL.md
- Confirm scope: verify the target URL/IP is within the engagement scope defined by the orchestrator
- Only after completing steps 1-4, proceed to Phase 1
Do NOT begin Phase 1 until the skill file is mounted.
Log:
{"timestamp":"...","agent":"{executor-name}","action":"mount-skill","skill":"{skill-path}","target":"{target}","scope_confirmed":true}
Phase 1: Recon
- Parse target: Extract URL, parameters, functionality
- Identify injection points: Forms, APIs, headers, cookies
- Log:
{"action":"recon","target":"...","injection_points":3}
Phase 2: Experiment
- Load payloads from quickstart.md and cheat-sheet.md
- Send safe/passive probes only — no payloads that modify state, create accounts, delete data, or trigger irreversible actions
- Test basic detection: does the input reach the sink? Is it reflected? Is it filtered? Does timing change?
- Analyze responses: errors, length differences, timing, redirect behavior
- Identify candidate vectors — do NOT exploit yet
- Log:
{"action":"experiment","payload":"...","result":"candidate/blocked/filtered"}
APPROVAL GATE — Phase 2 → Phase 3
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.
- 2mo ago First seen · 337 lines · 37 tokens per session scan A 64d30185fff0
Pentester Executor is an agent published in the GitHub repository Stickman230/claude-pentest (133 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 3,592 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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