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Osint Recon

Organization
SpecterOps
osint-recon

Perform OSINT and external reconnaissance for approved targets. Use for subdomain discovery, infrastructure mapping, technology fingerprinting, and recon reporting with optional command execution.

Overview

PublisherSpecterOps
Repositoryskills
Skill nameosint-recon
Stars
706
Forks
80
Bundled files
3
LicenseApache-2.0
Links
Skill sourceRepository
  • 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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Osint Recon 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/SpecterOps/skills/tree/main/plugins/ops-reconnaissance/skills/osint-recon
  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/SpecterOps/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/ops-reconnaissance/skills/osint-recon .claude/skills/osint-recon
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Osint Recon 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 Osint Recon 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 Osint Recon 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.

OSINT Recon

Run structured reconnaissance against user-provided authorized targets.

Input Parsing

Accept input as: TARGET [DEPTH] [MODE]

Depth:

  • passive (default)
  • active
  • full

Mode:

  • plan: report plan + command set only
  • execute (default, preferred): run command batches and capture evidence

If mode is omitted, default to execute.

Examples:

  • $osint-recon example.com
  • $osint-recon example.com active
  • $osint-recon "Acme Corp" full execute
  • $osint-recon 203.0.113.0/24 passive execute

Execution Policy

  • Always generate recon plan first.
  • In execute mode (default):
    • run command batches autonomously for routine in-scope actions,
    • request approval only for OPSEC-dangerous actions,
    • provide brief OPSEC warning for active/noisy actions.
  • Capture exact commands and key outputs in the report.

Workflow

  1. Create output directory:
    • mkdir -p recon/<target-slug>/
  2. Run passive recon for all depths.
  3. Run active recon only for active or full depth; require approval only for OPSEC-dangerous steps.
  4. Correlate findings and prioritize exploitable attack surface.
  5. Save report:
    • recon/<target-slug>/recon-report.md

Phase 1: Passive Recon (All Depths)

Suggested commands:

bash
# Subdomains
subfinder -d <target> -silent -o recon/<target-slug>/subdomains.txt

# DNS records
dig +short <target> A
dig +short <target> MX
dig +short <target> TXT
dig +short <target> NS

# Certificate transparency
curl -s "https://crt.sh/?q=%25.<target>&output=json"

# WHOIS
whois <target>

Investigate:

  • ASN/IP ownership and provider footprint
  • CDN/WAF presence
  • exposed technologies and externally reachable services
  • credential/leak indicators from public sources

Phase 2: Active Recon (Active/Full Depth)

Suggested commands:

bash
# HTTP probing / tech fingerprinting
httpx -l recon/<target-slug>/subdomains.txt -title -status-code -tech-detect -o recon/<target-slug>/httpx.txt

# Quick TCP service scan
nmap -sC -sV --top-ports 1000 -oA recon/<target-slug>/nmap-quick <target>

# Full TCP scan (noisier)
nmap -sC -sV -p- -oA recon/<target-slug>/nmap-full <target>

# Directory discovery
ffuf -u https://<target>/FUZZ -w <wordlist> -mc 200,301,302,403

# Template-based checks
nuclei -l recon/<target-slug>/subdomains.txt -o recon/<target-slug>/nuclei.txt

Reporting Template

markdown
# OSINT Report ? <target>
## Depth: <passive|active|full>
## Mode: <plan|execute>
## Timestamp: <utc timestamp>

## Executive Summary
- High-level attack-surface summary.

## Findings
- Subdomains / hosts
- Infrastructure ownership and hosting
- Technology fingerprints
- Notable exposures

## Commands and Evidence
- exact command
- key output
- interpretation

## Prioritized Next Steps
1. next action
2. next action

Quality Rules

  • Keep results target-specific and evidence-backed.
  • Distinguish confirmed findings vs hypotheses.
  • Prioritize exploitability over raw finding count.

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 Osint Recon AI skill do?

Perform OSINT and external reconnaissance for approved targets. Use for subdomain discovery, infrastructure mapping, technology fingerprinting, and recon reporting with optional command execution.

Why use Osint Recon on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SpecterOps/skills/tree/main/plugins/ops-reconnaissance/skills/osint-recon. 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 Osint Recon?

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 Osint Recon?

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

Is the Osint Recon AI skill free?

Yes. It is published on GitHub by SpecterOps under the Apache-2.0 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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