vichhka-git

vichhka-git / OpenTor

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Tor/Dark Web access skill for AI agents (OpenCode & Claude Code). Search 12 dark web engines, spider .onion sites, extract IOCs. Orchestrator-conductor architecture — zero external LLM deps.

31
6
100% credibility
Found May 02, 2026 at 27 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

OpenTor is a collection of scripts that allow AI agents to search dark web engines, crawl hidden sites, and extract useful details like emails or crypto addresses via the Tor network for security research.

How It Works

1
📰 Discover OpenTor

You hear about a helpful tool that lets AI assistants safely explore hidden corners of the internet for research.

2
📥 Bring it home

Download the tool to your computer and follow simple steps to get it ready.

3
🔗 Connect to hidden network

Set up a secure pathway to reach secret websites without leaving traces.

4
🤖 Team up with your AI

Tell your AI helper to load the tool, and it handles the setup automatically.

5
🔍 Start your search

Ask for info on topics like security threats, and watch it scan hidden sites for clues.

6
📋 Review findings

Get a list of links, key details like addresses or contacts, all neatly organized.

✅ Mission accomplished

You complete your investigation with safe, reliable insights from the shadows.

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Star Growth

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AI-Generated Review

What is OpenTor?

OpenTor equips AI agents in OpenCode or Claude Code with direct Tor network access for dark web exploration, solving the problem of LLMs being stuck on clearnet data during OSINT hunts. In Python, it proxies requests through Tor SOCKS5, searches 12 dark web engines in parallel, spiders .onion sites up to configurable depths, and extracts IOCs like emails, crypto addresses, and PGP keys. Users get CLI commands like `opentor.py search "ransomware leak"` for scored JSON results or STIX/MISP exports, plus circuit rotation and content safety filters—no external LLM APIs needed.

Why is it gaining traction?

It skips bloated browsers or manual Tor setup by self-installing via skills.sh and handling Tor bootstrapping, letting developers focus on queries over plumbing. Parallel engine pings with caching, analysis modes for ransomware or threat intel, and outputs feeding straight into MISP make it a practical tor dark web app for automated workflows. Zero deps on cloud LLMs hooks AI tinkerers building tor dark web search engine links tools.

Who should use this?

Threat hunters tracking ransomware leaks on .onion sites, OSINT analysts pulling IOCs from hidden forums, or security devs prototyping tor dark web telegram bots with Claude. Ideal for red teams needing quick .onion crawls or corporate intel teams exporting to STIX before clearnet searches.

Verdict

At 14 stars and 1.0% credibility, OpenTor is raw and unproven—docs shine but expect bugs in edge cases like slow circuits. Grab it for dark web tor tutorial experiments if you're comfy debugging Python Tor stacks.

(198 words)

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