Pentest

CommunityPopular

AKCodez

pentest

Security testing and OSINT toolkit wrapping 183+ tools from Z4nzu/hackingtool (nmap, sherlock, amass, subfinder, nuclei, httpx, holehe, maigret, trufflehog, sqlmap, impacket, netexec, and more). Use whenever the user asks to recon a target, scan a network, enumerate subdomains, investigate a username or email, test a web app, check for leaked secrets, or any other pentest / OSINT task. Runs locally on any OS via native Bash, WSL, or purpose-built Docker images — the skill picks the right backend automatically.

Overview

Publisher	AKCodez
Repository	`hackingtool-plugin`
Skill name	`pentest`
Stars	1.1K
Forks	240
Bundled files	2
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by AKCodez on GitHub. Read the source before you install it.

Installation

Install the Pentest AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/AKCodez/hackingtool-plugin/tree/main/plugins/hackingtool/skills/pentest
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/AKCodez/hackingtool-plugin/tree/main/plugins/hackingtool/skills/pentest

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/AKCodez/hackingtool-plugin.git /tmp/hackingtool-plugin
mkdir -p .claude/skills
cp -r /tmp/hackingtool-plugin/plugins/hackingtool/skills/pentest .claude/skills/pentest

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pentest in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pentest on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pentest is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Pentest / OSINT Skill

You have real Bash, real filesystem, real process execution, and a fleet of pentest tools one wrapper call away. Use the wrappers — manual curl loops are a fallback, not a default.

Step 0 — Preflight (run first, every session)

bash
python ${CLAUDE_PLUGIN_ROOT}/scripts/ht_preflight.py

Read the verdict and act:

ready → state the backend in one sentence (e.g. "Running native on macOS" / "Running via Docker on Windows" / "Running native in WSL Ubuntu") and start work.
partial → tell the user what's missing (use recommendations); offer to proceed with reduced coverage.
blocked → stop. Surface the recommendations and wait. Do not substitute manual curl / Invoke-WebRequest probes for a missing tool — that misleads the user about coverage.

Re-run preflight if the user installs something, starts Docker, or switches into WSL.

Tool-first defaults

When the ask is "audit / scan / find vulns", reach for:

Ask	Default chain
Subdomain enumeration	`subfinder -all` → `httpx -title -tech-detect`
Web vuln scan	`nuclei -severity medium,high,critical`
Port scan	`nmap -sV -sC` (or `naabu` for fast SYN sweep)
Directory / API discovery	`ffuf -w wordlist -u https://target/FUZZ`
Secret hunting	`trufflehog filesystem .` or `gitleaks detect`
Username / email investigation	`holehe` → `sherlock` → `maigret`
TLS audit	`nuclei -tags ssl,tls`
Domain OSINT	`amass intel` → `theharvester`

Anti-patterns: for-looping curl across many paths instead of ffuf / nuclei; hand-parsing TLS output instead of nuclei -tags ssl; saying "I don't have nuclei" when preflight returned ready (you have it via Docker).

The execution model

Every tool runs through ht_run.py, which:

Reads ht_env.py to pick a backend — native on Linux/macOS, WSL on Windows with a real distro, Docker anywhere with Docker Desktop.
Looks up a purpose-built Docker image for the tool if one exists (instrumentisto/nmap, projectdiscovery/nuclei, caffix/amass, 20+ more). Falls back to kalilinux/kali-rolling.
Executes the command. Auto-retries with sudo -n on permission-denied (native/WSL).
Returns JSON: status, stdout, stderr, returncode, command.

Only one pre-block: tools flagged interactive. Bypass with --force + --command if you have non-interactive args.

Bundled scripts

All at ${CLAUDE_PLUGIN_ROOT}/scripts/. Emit JSON.

Script	Purpose
`ht_preflight.py`	Run first. Capability check + setup recommendations.
`ht_search.py`	Query the tool index (`--q`, `--category`, `--tag`, `--capability`, `--os`).
`ht_env.py`	Low-level env detect. (Preflight wraps this.)
`ht_run.py`	Execute. `--command "..."` to override, `--args "..."` to append, `--network-host` for LAN, `--privileged` for raw sockets, `--force` to bypass the interactive block.

Golden path

Preflight — handle verdict per Step 0.
Read the ask — map to a workflow (reference/workflows.md) and apply the defaults table.
Find tool ids — ht_search.py --q "<keyword>". Don't guess; ids are namespaced (e.g. web_attack.Nuclei).
Execute — ht_run.py <tool_id> --args "...", or --command "<full>" for tools where runnable=False. Add --network-host for LAN, --privileged for raw sockets.
Parse status: ok → summarize highlights; error → report stderr, decide whether to retry; fallback → see reference/runtime-fallbacks.md; timeout → raise --timeout or chunk the scan.
Compose — subfinder → httpx → nuclei, holehe → sherlock → maigret. Feed outputs forward.

Docker image overrides

ht_run.py maps common tools to purpose-built images (faster pulls, proper ENTRYPOINTs):

Tool	Image
NMAP	`instrumentisto/nmap`
Nuclei	`projectdiscovery/nuclei`
Subfinder / Httpx / Katana	`projectdiscovery/*`
Amass	`caffix/amass`
TheHarvester	`secsi/theharvester`
Holehe / Maigret / SpiderFoot	official images
TruffleHog / Gitleaks	official images
Sqlmap	`paoloo/sqlmap`
Impacket / NetExec	`rflathers/impacket`, `byt3bl33d3r/netexec`

Override with --docker-image my/image for one-offs.

Ad-hoc commands

Bash directly is fine for spot-checks: a single curl -I, arp -a, dig @8.8.8.8 example.com. Reach for ht_run.py whenever:

The tool is in the index and you want auto image/backend selection.
You're chaining multiple tools and want uniform JSON output.
The task is enumeration / scanning / fuzzing at any scale (≥5 requests against a target).

If you're about to write a for loop hitting many paths with curl, stop — use ffuf / nuclei / gobuster instead.

References

${CLAUDE_PLUGIN_ROOT}/skills/pentest/reference/workflows.md — named playbooks
${CLAUDE_PLUGIN_ROOT}/skills/pentest/reference/runtime-fallbacks.md — templates per fallback reason

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Pentest AI skill do?

Why use Pentest on TypingMind?

Because you install it once and use it with any model. Pentest is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pentest in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AKCodez/hackingtool-plugin/tree/main/plugins/hackingtool/skills/pentest. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Pentest?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pentest?

As many as you like. As long as a model supports skills, you can use Pentest with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pentest AI skill free?

It is published on GitHub by AKCodez. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Pentest / OSINT Skill

Step 0 — Preflight (run first, every session)

Tool-first defaults

The execution model

Bundled scripts

Golden path

Docker image overrides

Ad-hoc commands

References

Bundled files

Frequently asked questions

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