Agent skill

Reconnaissance

by transilienceai in transilienceai/communitytools

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

MITAuto-check passedSecurity

Install Reconnaissance

skills CLI
$ npx skills add transilienceai/communitytools --skill reconnaissance -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install transilienceai/communitytools reconnaissance --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/transilienceai/communitytools.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/reconnaissance .claude/skills/reconnaissance && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
reconnaissance
GitHub stars
563
Token cost
~1.4k tokens
SKILL.md length
693 words
Files
10
Skills in repo
35
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 3 steps: Subdomain Discovery - Passive DNS,… → Port Scanning - nmap/masscan (top… → Service Enumeration - Version detection,…
  • Tasks that involve Threat modeling
  • SKILL.md covers Phases, Output, Tools and Related Skills, plus 1 more section
  • Calls curl

What it does

Reconnaissance is an agent skill from transilienceai/communitytools. Domain assessment and web application mapping - subdomain discovery, port scanning, endpoint enumeration, API discovery, and attack surface analysis.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files (for example `reference/INDEX.md`, `reference/anti-bot-bypass.md` and `reference/reconnaissance-principles.md`).

It sits in Security, covering Threat modeling and Bug bounty. The repository describes itself as: Open-source Claude Code skills, agents, and slash commands for AI-powered penetration testing, bug bounty hunting, and security research. The licence is MIT.

When your agent uses it

  • Tasks that involve Threat modeling
  • Tasks that involve Bug bounty

Example prompts

  • “/reconnaissance”

Requirements

  • Node.js

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  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

What it can do on your machine

Read from SKILL.md and the folder at commit 95fdc12. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use curl, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Reconnaissance loads about 1.4k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 693 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~41
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from transilienceai/communitytools at commit 95fdc12, republished under its MIT licence (© transilienceai). 693 words, ~1,428 tokens.

Download SKILL.mdSave it as .claude/skills/reconnaissance/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
reconnaissance
description
Domain assessment and web application mapping - subdomain discovery, port scanning, endpoint enumeration, API discovery, and attack surface analysis.

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

  • /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.

© transilienceai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files in skills/reconnaissance of transilienceai/communitytools.

  • SKILL.md
  • reference/INDEX.md
  • reference/anti-bot-bypass.md
  • reference/reconnaissance-principles.md
  • reference/scenarios/api-endpoint-discovery.md
  • reference/scenarios/obfuscated-js-deobfuscation.md
  • reference/scenarios/port-scanning.md
  • reference/scenarios/subdomain-enumeration.md
  • reference/scenarios/vhost-enumeration.md
  • reference/waf-edge-bypass.md

Open the folder on GitHubat commit 95fdc12

Compare with similar skills

Reconnaissance next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Reconnaissance compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Reconnaissance this skilltransilienceai/communitytools563—~1.4kAutomated safety check: PassMIT
Osint Methodologyelementalsouls/Claude-OSINT2.8k—~8.7kAutomated safety check: NotesMIT
Web2 Reconawarexone/Agentic-Bug-Hunter5.3k2 repos~6.4kAutomated safety check: WarnMIT
Security Specialistfabricioctelles/skills106—~2.8kAutomated safety check: PassApache-2.0
Audit Context Buildingtrailofbits/skills7.5k—~996Automated safety check: PassCC-BY-SA-4.0
Reconbriiirussell/cybersecurity-skills413—~1.1kAutomated safety check: NotesMIT

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Categories

Questions about Reconnaissance

What does Reconnaissance do?

Domain assessment and web application mapping - subdomain discovery, port scanning, endpoint enumeration, API discovery, and attack surface analysis. Reconnaissance is an agent skill from transilienceai/communitytools. Domain assessment and web application mapping - subdomain discovery, port scanning, endpoint enumeration, API discovery, and attack surface analysis.

When should I use Reconnaissance?

Reconnaissance fits situations like: tasks that involve Threat modeling; tasks that involve Bug bounty.

How do I install Reconnaissance in Claude Code?

Run `npx skills add transilienceai/communitytools --skill reconnaissance -a claude-code`. Or copy the skill folder (skills/reconnaissance in transilienceai/communitytools) into .claude/skills/reconnaissance in your project. Claude Code loads it when a task matches its description.

How do I install Reconnaissance in Codex?

Run `npx skills add transilienceai/communitytools --skill reconnaissance -a codex`. Or copy the skill folder (skills/reconnaissance in transilienceai/communitytools) into .agents/skills/reconnaissance in your project. Codex loads it when a task matches its description.

Can I use Reconnaissance in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add transilienceai/communitytools --skill reconnaissance -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reconnaissance, .gemini/skills/reconnaissance, .github/skills/reconnaissance and .opencode/skills/reconnaissance in your project.

What does Reconnaissance need to run?

Going by SKILL.md and its folder, Reconnaissance needs the command-line tools its instructions call (curl). Our summary lists: Node.js.

Does Reconnaissance access the network?

SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Reconnaissance safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Reconnaissance use?

Reconnaissance is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Reconnaissance use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Reconnaissance?

Skills that share tags, products or a category with Reconnaissance: Osint Methodology (elementalsouls/Claude-OSINT, 2.8k stars), Web2 Recon (awarexone/Agentic-Bug-Hunter, 5.3k stars), Security Specialist (fabricioctelles/skills, 106 stars) and Audit Context Building (trailofbits/skills, 7.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Reconnaissance?

transilienceai (a GitHub organization) maintains it in transilienceai/communitytools, which has 563 GitHub stars. The repository holds 35 skills in this directory. The repository was last updated on July 29, 2026.

Source: transilienceai/communitytools on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.