Robin，一个 AI 驱动的暗网情报调查工具，思路挺直接：

用大模型帮你把搜索词改精准 自动过滤暗网搜索引擎吐出来的一堆结果 最后还给你生成一份调查总结

OpenAI、Claude、Gemini、Ollama 想接哪个接哪个，Docker 拉起来就能跑。就是有句话得记牢：暗网这地方，工具再顺手，也别拿去干犯法的事，后果自己扛。

https://github.com/apurvsinghgautam/robin…

apurvsinghgautam/robin

Source: https://github.com/apurvsinghgautam/robin

Robin: AI-Powered Dark Web OSINT Tool

Robin is an AI-powered tool for conducting dark web OSINT investigations. It leverages LLMs to refine queries, filter search results from dark web search engines, and provide an investigation summary.

Installation • Usage • Contributing • Acknowledgements

Architecture

Features

• ⚙️ Modular Architecture – Clean separation between search, scrape, and LLM workflows.
• 🤖 Multi-Model Support – Easily switch between OpenAI, Claude, Gemini, Ollama, or any OpenAI-compatible API (LM Studio, llama.cpp, Groq, etc.).
• 🌐 Web UI – Streamlit-based interface for interactive investigations.
• 🐳 Docker-Ready – Recommended Docker deployment for clean, isolated usage.
• 📝 Custom Reporting – Save investigation output to file for reporting or further analysis.
• 🧩 Extensible – Easy to plug in new search engines, models, or output formats.

⚠️ Disclaimer

This tool is intended for educational and lawful investigative purposes only. Accessing or interacting with certain dark web content may be illegal depending on your jurisdiction. The author is not responsible for any misuse of this tool or the data gathered using it.

Use responsibly and at your own risk. Ensure you comply with all relevant laws and institutional policies before conducting OSINT investigations.

Additionally, Robin leverages third-party APIs (including LLMs). Be cautious when sending potentially sensitive queries, and review the terms of service for any API or model provider you use.

Installation

The tool needs Tor to do the searches. You can install Tor using apt install tor on Linux/Windows(WSL) or brew install tor on Mac. Once installed, confirm if Tor is running in the background.

You can provide your LLM of choice API key by either creating .env file (refer to sample env file in the repo) or by setting env variables in PATH.

For Ollama, provide http://host.docker.internal:11434 as OLLAMA_BASE_URL in your env if running using docker method or http://127.0.0.1:11434 for other methods. You might need to serve Ollama on 0.0.0.0 depending on your OS. You can do by running OLLAMA_HOST=0.0.0.0 ollama serve & in your terminal.

For any other OpenAI-compatible provider (LM Studio, llama.cpp, Groq, etc.), use the 🔌 Custom API Provider expander in the sidebar — no .env changes required. Enter the base URL, an optional API key, and optionally a model name if the provider doesn’t expose /v1/models for auto-discovery.

Docker [Recommended]

• Pull the latest Robin docker image

docker pull apurvsg/robin:latest

• Run the docker image as:

docker run --rm \
   -v "$(pwd)/.env:/app/.env" \
   --add-host=host.docker.internal:host-gateway \
   -p 8501:8501 \
   apurvsg/robin:latest

To persist saved investigations across Docker restarts, mount a local directory:

docker run --rm \
   -v "$(pwd)/.env:/app/.env" \
   -v "$(pwd)/investigations:/app/investigations" \
   --add-host=host.docker.internal:host-gateway \
   -p 8501:8501 \
   apurvsg/robin:latest

Investigations are saved to the investigations/ folder in your working directory and can be loaded from the Past Investigations panel in the sidebar.

• Open your browser and navigate to http://localhost:8501

Using Python (Development Version)

• With Python 3.10+ and Tor installed, run the following:

pip install -r requirements.txt
streamlit run ui.py

• Open your browser and navigate to http://localhost:8501

Contributing

Contributions are welcome! Please feel free to submit a Pull Request if you have major feature updates.

• Fork the repository
• Create your feature branch (git checkout -b feature/amazing-feature)
• Commit your changes (git commit -m ‘Add some amazing feature’)
• Push to the branch (git push origin feature/amazing-feature)
• Open a Pull Request

Open an Issue for any of these situations:

• If you spot a bug or bad code
• If you have a feature request idea
• If you have questions or doubts about usage
• If you have minor code changes

Acknowledgements

• Idea inspiration from Thomas Roccia and his demo of Perplexity of the Dark Web.
• Tools inspiration from my OSINT Tools for the Dark Web repository.
• LLM Prompt inspiration from OSINT-Assistant repository.
• Logo Design by my friend Tanishq Rupaal