Reconnaissance logo

Reconnaissance

Organization
transilienceai
reconnaissance

Domain assessment and web application mapping - subdomain discovery, port scanning, endpoint enumeration, API discovery, and attack surface analysis.

Overview

Publishertransilienceai
Repositorycommunitytools
Skill namereconnaissance
Stars
565
Forks
81
Bundled files
9
LicenseMIT
Links
  • 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.

  • 9 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by transilienceai on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/transilienceai/communitytools/tree/main/skills/reconnaissance
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/transilienceai/communitytools.git /tmp/communitytools
mkdir -p .claude/skills
cp -r /tmp/communitytools/skills/reconnaissance .claude/skills/reconnaissance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Reconnaissance 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 Reconnaissance 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 Reconnaissance 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.

Reconnaissance

Domain and web application reconnaissance. Discovers subdomains, open ports, endpoints, APIs, and JavaScript routes to build attack surface inventory.

Phases

Domain Assessment

  1. Subdomain Discovery - Passive DNS, certificate transparency, DNS brute-forcing, zone transfers
  2. Port Scanning - nmap/masscan (top 1000/10000/all), service detection, OS fingerprinting
  3. Service Enumeration - Version detection, banner grabbing, protocol-specific enumeration

Web Application Mapping

  1. Software Inventory - Dependencies, frameworks, SBOM generation
  2. Active Scanning - ffuf, gobuster, nikto, ZAP spider for directories/files
  3. API Discovery - REST, GraphQL, SOAP, WebSocket, Swagger/OpenAPI docs
  4. JavaScript & SPA - Client-side routes, dynamic scripts, browser storage
  5. Surface Analysis - Categorize attack surfaces, prioritize by risk

Output

inventory/  - JSON: subdomains, ports, endpoints, APIs, SBOM
analysis/   - MD: attack-surface, testing-checklist
raw/        - Tool outputs (nmap, ffuf, ZAP, subfinder)

Tools

subfinder, amass, certspotter, crt.sh, nmap, masscan, nuclei, sslscan, ffuf, gobuster, nikto, ZAP, Playwright MCP

Related Skills

  • /osint - Run alongside reconnaissance for repository enumeration, secret scanning, and git history analysis

Rules

  1. Passive discovery before active scanning
  2. Always run /osint in parallel during Phase 2
  3. Respect rate limits
  4. Verify subdomains are live before port scanning
  5. Save all raw tool outputs
  6. HTTP response header vhost leaks: Always check response headers on the raw IP (curl -sI http://IP/). Headers like X-Backend-Server, X-Forwarded-Host, X-Served-By, X-Upstream often leak internal hostnames/vhosts not discoverable via DNS or brute-force. Add discovered hostnames to /etc/hosts immediately.
  7. Wildcard SSL certs (*.domain.tld in SAN) = strong indicator of hidden vhosts. Always run vhost brute-force with ffuf -u https://IP -k -H "Host: FUZZ.domain.tld" -w subdomains.txt -mc all -fs <default_size> when wildcard SAN detected. Compare response size/status vs default vhost to identify valid subdomains.
  8. VHost enumeration without ffuf: When ffuf/gobuster unavailable, use shell loop: for sub in admin dev api portal dashboard staging git; do code=$(curl -s -o /dev/null -w "%{http_code}:%{size_download}" -H "Host: ${sub}.DOMAIN" http://IP); echo "$sub: $code"; done — filter by response size difference from default page.
  9. Web management panels: When discovering admin vhosts (admin., panel., manage.*), check for known management UIs: Nginx UI (manifest.json → "Nginx UI"), Cockpit, Webmin, phpMyAdmin. These often have unauthenticated API endpoints or known CVEs. Check /api/backup, /api/settings, /api/install for Nginx UI specifically.
  10. Mobile / native client downloads on the marketing tier: when the public web tier has a download link to an .apk / .dmg / .exe / .ipa, the "real" API endpoint and its required headers are usually only reachable from that client. The web HTML shows nothing useful; the API is gated behind a static User-Agent / Host that's hard-coded in the binary. Always pull the client and decompile/extract before assuming the box is a static-page only. For Android React Native: unzip <app>.apk -d ext/ && file ext/assets/index.android.bundle. The bundle is typically obfuscator.io-style (function _0xNNNN(idx) decoder + array.shift() IIFE that loops until a parseInt-equation == target). Don't reverse it by hand — extract decoder + array literal + IIFE into a standalone Node.js file and dump every index in seconds: for(let i=baseHex; i<baseHex+arr.length; i++) console.log(i.toString(16), _0xDecode(i));. Then reconstruct the obfuscated object literal of the API call (URL = concatenation of 4–7 short fragments, headers likewise) and replay with the recovered values verbatim.
  11. Focused AD port scan for Windows targets: when initial fingerprinting shows a Windows DC archetype (any of 53/135/139/445/389 open), skip -p- and run a focused scan over the 13 AD-relevant ports first — it finishes in seconds and covers everything that matters.
    bash
    nmap -Pn -sC -sV -p 53,88,135,139,389,445,464,593,636,3268,3269,5985,5986,9389 -oA recon/ad-focused TARGET
    Ports rationale: 53 DNS, 88 Kerberos, 135 RPC, 139/445 SMB, 389/636 LDAP/LDAPS, 464 kpasswd, 593 RPC-over-HTTPS, 3268/3269 GC/GC-LDAPS, 5985 WinRM (HTTP), 5986 WinRM (HTTPS — cert auth), 9389 AD Web Services. Always probe BOTH 5985 and 5986 — when 5985 is filtered, 5986 with client-cert auth is a common foothold path (see skills/system/reference/foothold-patterns.md WinRM cert-auth foothold). Only fall back to -p- if (a) no flag-yielding service surfaces in the focused scan, or (b) you suspect a non-standard app on a high port (custom web service, RDP-on-non-3389, etc.). Don't burn 30 minutes on full TCP sweeps when the AD archetype is obvious.
  12. CT-log enumeration is MANDATORY: CT-log enumeration (crt.sh / certspotter / subfinder) is MANDATORY on every engagement that names an apex domain, INCLUDING grey-box engagements where hostnames were provided — provided hostnames are a seed, not the surface. CDN/WAF-fronted targets additionally get an origin-discovery pass (direct cloud endpoints, archive.org CDX, historical DNS). The crt.sh/subfinder commands already ship in reference/scenarios/subdomain-enumeration.md — use them.

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 Reconnaissance AI skill do?

Domain assessment and web application mapping - subdomain discovery, port scanning, endpoint enumeration, API discovery, and attack surface analysis.

Why use Reconnaissance on TypingMind?

Because you install it once and use it with any model. Reconnaissance 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 Reconnaissance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/transilienceai/communitytools/tree/main/skills/reconnaissance. 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 Reconnaissance?

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 Reconnaissance?

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

Is the Reconnaissance AI skill free?

Yes. It is published on GitHub by transilienceai under the MIT license. 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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