OnionClaw 🧅

by JacobJandon

OpenClaw skill + standalone tool — full Tor / dark web access for AI agents

OnionClaw gives AI agents full access to the Tor network and .onion hidden services. It runs as an OpenClaw skill (drop-in, zero config beyond a .env file) and also works standalone from any terminal.

Based on the SICRY engine — 17 dark web search engines, Robin OSINT pipeline, four LLM analysis modes.

# As an OpenClaw skill:
cp -r OnionClaw ~/.openclaw/skills/onionclaw
# → agent now has 7 dark web commands available in every session

# Standalone:
python3 doctor.py           # check the whole setup, and what to fix
python3 check_tor.py        # verify Tor
python3 check_engines.py && python3 search.py --query "ransomware healthcare" --alive
python3 pipeline.py --query "acme.com data leak" --mode corporate

---

⚠️ The Rabbit Hole

Autonomous agents paired with the Tor network will be one of the most dangerous automation stacks on the internet within the next five years. OnionClaw is living proof that the rabbit hole goes deeper than most people think.

This tool is built for legitimate OSINT, threat intelligence, and security research. But the same primitives — anonymous routing, bulk scraping, AI-driven synthesis, zero-attribution browsing, automated identity rotation — are precisely what make this combination genuinely dangerous in the wrong hands.

This is not a warning tucked in fine print. It is the whole point of writing it down openly.

What the stack enables — the full map

Use case	What it looks like
Dark-web crawling	Automated, headless spidering of .onion services at scale — forums, paste sites, markets, leak boards — with full identity rotation between every request. No human ever touches a keyboard.
Threat intelligence	Continuous monitoring of ransomware group blogs, initial access broker ads, CVE exploit drops, and actor chatter long before it surfaces on clearnet feeds.
Marketplace monitoring	Price tracking, stock alerts, vendor reputation scraping, and availability checks across darknet markets — the same logic a researcher uses to track fentanyl price trends is the same logic a supplier uses to undercut competitors.
Credential surveillance	Watching paste boards, breach dumps, and forum leaks for specific email domains, API keys, SSH keys, or internal hostnames the moment they appear — at a scale no human analyst can match.
Deanonymisation research	Cross-correlating .onion service metadata with clearnet traces, timing attacks, correlation of writing style and PGP keys — used both by law enforcement hunting criminals and by threat actors hunting journalists and dissidents.
Criminal automation	Autonomous agents placing orders, posting ads, messaging vendors, managing mule accounts, draining wallets — an entire criminal operation running without a human ever in the loop.
Disinformation infrastructure	Coordinated persona networks on hidden boards, fabricated document drops timed to bleed into legitimate OSINT pipelines, synthetic intelligence that reads real but originates from nowhere.
Zero-day brokerage	Automated monitoring of exploit vendor channels, private CVE auction boards, and vulnerability markets — buy-side and sell-side intelligence gathered faster than any human analyst.

The ugly side

The 2026 internet is already at the edge of this. Within five years, AI agents that can:

1. Browse anonymously through rotating Tor circuits with no persistent identity
2. Understand context well enough to navigate dark web UIs, CAPTCHA logic, and forum culture without hardcoded selectors
3. Act autonomously — search, buy, post, exfiltrate, rotate — in closed loops with no human confirmation step
4. Self-orchestrate across dozens of simultaneous Tor identities on parallel threads

…represent a qualitative shift from human criminals using tools to autonomous criminal infrastructure operating at machine speed with no human in the loop. The bottleneck has always been human attention. Remove it and the scaling properties of dark web operations change completely.

OnionClaw demonstrates all four of those primitives working together today. The full pipeline.py step — query refinement → multi-engine search → result filtering → batch scrape → LLM synthesis → identity rotation — is a complete autonomous dark web intelligence loop. Remove the OSINT framing and it is equally a complete autonomous dark web operation loop. The code is the same either way.

Why this is written explicitly

Security tools that pretend the dual-use problem does not exist are more dangerous than ones that name it directly. If you are building on top of OnionClaw:

• Know what you are building. The pipeline does not know if the query is "acme.com credential leak" for a pentest or "rival vendor SSH keys" for espionage.
• Know your jurisdiction. Automated access to dark web content and .onion services may be illegal in your country regardless of intent or findings.
• Tor is not legal protection. It is operational security. The two are different things with very different limits.
• AI + Tor + autonomy is not a theoretical threat. It is a present capability. This repo is one of many signals that the tooling is ready.

This is the beginning of the README. Read the rest at the original. Read the full README ↗