GH05TCREW/pentestagent is an AI agent framework that performs black-box penetration testing with security tools such as nmap, Metasploit, and sqlmap. It is for bug bounty hunters, red teams, penetration testers, and security learners, with the catalogue instruction helping users operate the framework.
Borrowing it
Nothing to install: this file belongs to GH05TCREW/pentestagent. 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/GH05TCREW/pentestagent/main/CLAUDE.mdgit clone --depth 1 https://github.com/GH05TCREW/pentestagentWrote 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/instructions/gh05tcrew/pentestagent/claude-md)<a href="https://agentmods.dev/instructions/gh05tcrew/pentestagent/claude-md"><img src="https://agentmods.dev/badge/instructions/gh05tcrew/pentestagent/claude-md/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/instructions/gh05tcrew/pentestagent/claude-md"><img src="https://agentmods.dev/badge/instructions/gh05tcrew/pentestagent/claude-md.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 | $0.02345 | $0.02345 |
| Opus 5.5 | $0.00938 | $0.00938 |
| Sonnet 5.5 | $0.00469 | $0.00469 |
| Haiku 4.5 | $0.00234 | $0.00234 |
Grade A, and why
pentestagent CLAUDE.md 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.
How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PentestAgent — CLAUDE.md
Project overview
PentestAgent (v0.2.0) is an AI-powered penetration testing framework built in Python. It wraps LiteLLM to support any provider (Anthropic, OpenAI, etc.) and exposes a TUI, a CLI, and an MCP server interface. The agent can run tools locally or inside a Docker sandbox (base or Kali image).
Tech stack
- Python 3.10+, packaged with Hatchling (
pyproject.toml) - LiteLLM — provider-agnostic LLM wrapper
- Textual — TUI framework (
pentestagent/interface/) - Typer — CLI framework
- Playwright — browser tool
- MCP (Model Context Protocol) — both client (consuming external servers) and server (exposing PentestAgent to Claude Desktop / Cursor / etc.)
- FAISS + sentence-transformers — optional RAG engine (
pip install -e ".[rag]")
Repository layout
pentestagent/
agents/
crew/ # Multi-agent mode: orchestrator + worker pool + shadow graph
pa_agent/ # Single-agent implementation
state.py # Shared agent state
config/
settings.py # Global Settings dataclass (singleton via get_settings())
constants.py # Model defaults, iteration limits, etc.
interface/
cli.py # Typer CLI entry-point
notifier.py # Event bus between agent and UI
utils.py # Shared UI helpers
knowledge/
graph.py # ShadowGraph — derives strategic insights from notes
indexer.py # Indexes knowledge sources for RAG
rag.py # FAISS-backed retrieval
llm/
config.py # LiteLLM configuration
memory.py # Conversation/token management
utils.py # Streaming helpers
mcp/
stdio_adapter.py # STDIO MCP server transport
example_adapter.py # SSE MCP server transport
playbooks/
base_playbook.py
thp3_recon.py / thp3_network.py / thp3_web.py
runtime/
docker_runtime.py # Runs tool commands inside Docker
tool_server.py # Local runtime
tools/
loader.py # Discovers & dynamically imports tool modules
executor.py # Executes tool calls, tracks tokens
token_tracker.py
terminal/ # Shell execution tool
browser/ # Playwright browser tool
web_search/ # Tavily web search (needs TAVILY_API_KEY)
notes/ # Persistent findings store → loot/notes.json
finish/ # Signals task completion
workspaces/ # Workspace isolation helpers
loot/ # Persisted notes and findings (git-ignored)
mcp_examples/ # Example MCP configs and adapters
scripts/ # setup.sh / setup.ps1
tests/ # pytest suite
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 · 251 lines · 2,345 tokens per session scan A 8071367d7012
pentestagent CLAUDE.md is an instructions file published in the GitHub repository GH05TCREW/pentestagent (3,217 stars, last pushed yesterday), licensed MIT. It adds 2,345 tokens to every session, about $0.0094 per session on Opus 5.5. 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.