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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-generate…

Install / Use

npx skills add elementalsouls/Claude-OSINT --skill osint-autopilot

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

88/100

Category

Security

Supported Platforms

Zed

Tags

Our assessment of osint-autopilot

osint-autopilot scores 88/100 on our quality scale, 500th of 867 Security skills we index.

Its SKILL.md is 5.5 KB long, well organised into 11 sections with 3 code examples: a solid amount of guidance for an agent.

With 2,654 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
18/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 30 days ago, so osint-autopilot is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-29. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

osint-autopilot compared with similar skills

All 4 of these similar skills score higher than osint-autopilot; compare them before choosing.

SkillScoreStarsUpdatedFormat
osint-autopilot (this skill)by elementalsouls882.7k30d agoSKILL.md
algorithmic-artby anthropics100177.9k7d agoSKILL.md
pptxby anthropics100177.9k7d agoSKILL.md
designby nextlevelbuilder100130.2k8d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k8d agoSKILL.md

Frequently asked questions

How do I install osint-autopilot?
Run npx skills add elementalsouls/Claude-OSINT --skill osint-autopilot. The install tabs above show the steps for each supported agent.
Which AI agents does osint-autopilot work with?
It is written for Zed, as a SKILL.md file. Other agents that read the same format can often use it too.
Is osint-autopilot safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is osint-autopilot still maintained?
The repository was last updated 30 days ago, so osint-autopilot is actively maintained.

name: osint-autopilot description: 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. version: 1.0 sources: asm_reference_impl, community triggers:

  • run OSINT
  • run recon
  • run the full recon pipeline
  • attack surface on
  • OSINT autopilot
  • full external recon
  • end to end recon
  • recon to completion
  • consolidated OSINT workbook

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.

Related Skills

View on GitHub
GitHub Stars2.7k
CategorySecurity
Updated1mo ago
Forks478

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions