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Osint Autopilot

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elementalsouls
osint-autopilot

End-to-end external OSINT engagement autopilot. Run the FULL osint-methodology pipeline to completion in ONE go for an authorized domain — engagement folder, Stages 1-5 (seed, expansion, enrichment, exposure, convergence), multi-agent per-host content+JS fan-out, headline verification, auto-generated findings, and a consolidated multi-tab .xlsx deliverable. Stops ONLY for Stage 6 (active exploitation) arming and out-of-scope sibling assets. Use whenever asked to "run OSINT / recon / attack-surface" on a target — do NOT deliver a thin passive first pass.

Overview

Publisherelementalsouls
RepositoryClaude-OSINT
Skill nameosint-autopilot
Stars
2.6K
Forks
474
Bundled files
7
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.

  • 7 bundled files

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

  • Open source

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

Installation

Install the Osint Autopilot 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.
  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/elementalsouls/Claude-OSINT.git /tmp/Claude-OSINT
mkdir -p .claude/skills
cp -r /tmp/Claude-OSINT/skills/osint-autopilot .claude/skills/osint-autopilot
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Osint Autopilot 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 Autopilot 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 Autopilot 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 Autopilot

Purpose: eliminate the "thin first pass, then user pushes for more" failure. When the user says run OSINT/recon on <domain> (authorized), execute the whole pipeline to completion and hand back the consolidated workbook — no stopping to ask except the two hard gates below.

Read the companion osint-methodology skill for the framework; this skill is the executable runbook. Feedback memory osint-full-pipeline-default governs the default.

Hard gates (the ONLY reasons to stop and ask)

  1. Authorization — if not already asserted, ask the one scope question, then proceed. (Here it's typically already signed.)
  2. Stage 6 (active exploitation) — BOLA/IDOR, credential replay, injection confirmation. Never run under autopilot; present the ranked target queue and wait for arming.
  3. Out-of-scope siblings — a newly-discovered sibling domain/brand (e.g. <company>.io when scope was .com). Flag; don't scan until confirmed.

Everything in Stages 1–5 runs without pausing for questions.

Run sequence

Let S = ~/.claude/skills/osint-autopilot/scripts.

1. Deterministic recon (Stages 1–3 + harvest + breach + ports)

bash $S/recon_pipeline.sh <domain>

Creates ~/Research/engagements/<domain>/ and populates evidence (DNS/WHOIS/RDAP/email-sec, subdomain union via subfinder+certspotter+crt.sh, dig-resolve, HTTP probe, identity fabric, /version disclosure, S3 takeover check, gau+wayback+JS harvest, HudsonRock breach, bounded public-IP port scan), hashes everything, and splits responsive hosts into buckets/bucket-NN.

Host notes baked in: uses dig/curl (ProjectDiscovery dnsx/httpx segfault on this M1 — cgo m1cpu); nmap is time-capped at 10 min so it can't stall.

2. Multi-agent per-host fan-out (Stage 4 exposure)

Read buckets/COUNT and the buckets/bucket-* paths, then launch the workflow (ffuf must be on PATH — go install github.com/ffuf/ffuf/v2@latest if missing):

Workflow({ scriptPath: "<S>/host_enum.workflow.js",
  args: { domain:"<domain>", engDir:"~/Research/engagements/<domain>" (absolute),
          ffuf:"<gopath>/bin/ffuf", wordlist:"<S>/wordlist.txt",
          buckets:[ absolute bucket-00 … bucket-NN ] } })

Pass args as a real JSON object, NOT a stringified one — the harness hands args to the script verbatim; a string makes args.domain/args.buckets undefined and only the synthesize agent runs. The script fails loudly if args are malformed. engDir must be absolute. buckets = absolute paths of every buckets/bucket-* file (read buckets/COUNT).

It fans out ffuf content-discovery + JS/endpoint analysis per bucket (agentType general-purpose), then synthesizes a ranked BOLA/IDOR target queue. Save synthesis to evidence/stage6-content/SYNTHESIS.md. Optional screenshots: gowitness scan file -f <urls> --screenshot-path evidence/stage6-screens --write-db (Chrome required).

3. Verify headlines yourself (do NOT trust agent output blindly)

Re-curl every CONFIRMED-worthy claim before reporting it: exposed secrets (fetch the JS/vars file), /version disclosures, Cognito/Auth0 config, any "unauth admin 200". Downgrade anything you can't reproduce.

4. Auto-findings + workbook

build_xlsx.py requires the openpyxl pip package (pip install -r $S/requirements.txt if missing).

python3 $S/findings_gen.py <domain>     # evidence -> findings/findings.csv (rules engine)
python3 $S/build_xlsx.py  <domain>      # findings.csv + evidence -> <domain>-osint-consolidated.xlsx

findings_gen.py encodes the rubric (non-prod exposure, CDN/WAF-bypass origins, internal-IP leak, DMARC/SPF, /version disclosure, JS secrets, S3 takeover, identity fabric, breach severity, WordPress, port exposure). Hand-add any nuanced findings the rules miss by editing findings.csv, then re-run build_xlsx.py.

5. Report

Give the consolidated .xlsx path + a short severity summary, then present the two open gates (Stage 6 queue + any out-of-scope siblings). Offer passive CVE mapping against disclosed versions as a next step.

Deliverable

~/Research/engagements/<domain>/:

  • <domain>-osint-consolidated.xlsx — 9–10 tabs (Summary, Findings, Subdomains, Live Hosts, API Endpoints, Secrets, Ports, Internal-IP-Leak, Screenshots)
  • findings/findings.csv · evidence/** (+ .sha256) · evidence/stage6-content/SYNTHESIS.md · run-log.jsonl

Time budget

Small org (<100 hosts): ~15–25 min wall-clock. Medium (100–1K): ~30–60 min, dominated by the fan-out workflow and gau harvest.

Scale note

The fan-out is ~1 agent per 18 hosts. Keep total agents ≤15 (default guideline); for >270 responsive hosts, raise bucket size in recon_pipeline.sh (split -l) rather than agent 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 Autopilot AI skill do?

End-to-end external OSINT engagement autopilot. Run the FULL osint-methodology pipeline to completion in ONE go for an authorized domain — engagement folder, Stages 1-5 (seed, expansion, enrichment, exposure, convergence), multi-agent per-host content+JS fan-out, headline verification, auto-generated findings, and a consolidated multi-tab .xlsx deliverable. Stops ONLY for Stage 6 (active exploitation) arming and out-of-scope sibling assets. Use whenever asked to "run OSINT / recon / attack-surface" on a target — do NOT deliver a thin passive first pass.

Why use Osint Autopilot on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/elementalsouls/Claude-OSINT/tree/main/skills/osint-autopilot. 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 Autopilot?

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 Autopilot?

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

Is the Osint Autopilot AI skill free?

Yes. It is published on GitHub by elementalsouls 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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