Leveraging LLMs for Cyber Security: Getting Started with Robin AI

apurvsinghgautam/robin

In the OSINT (Open Source Intelligence) world, the "Dark Web" is notoriously difficult to parse because it's slow, unindexed by Google, and filled with "noise" (scams or dead links). Robin acts as an AI-powered middleman that automates the tedious parts of this investigation.

From an engineering perspective, Robin solves the "Signal-to-Noise" problem. Here is how it helps

Query Expansion
Instead of just searching for "ransomware," the tool uses an LLM to expand your query into semantically related terms (e.g., "leak site," "onion repository," "IOCs"), increasing hit rates.

Orchestration
It manages the connection to the Tor network (via SOCKS proxies) and handles multi-threaded scraping across multiple dark web search engines simultaneously.

Automated Summarization
It doesn't just give you raw HTML. It passes the scraped content back to an LLM to filter out the junk and provide a structured summary of actual threats.

To get this running, you’ll need Python 3.10+, Docker (optional but recommended), and a running Tor service.

First, ensure you have Tor installed and running locally to act as your gateway

# On macOS
brew install tor
tor

git clone https://github.com/apurvsinghgautam/robin.git
cd robin
pip install -r requirements.txt

Create a .env file to store your API keys. Robin is modular, so you can use OpenAI, Anthropic, or even local models via Ollama.

OPENAI_API_KEY=your_key_here
# Or use other providers
ANTHROPIC_API_KEY=your_key_here

Robin is designed as a CLI-first tool. Here’s how you would initiate an investigation into a specific keyword

# Run a search using GPT-4o as the reasoning engine
python robin.py --query "company_name data leak" --model gpt4o

Input
Your raw query.

Expansion
The LLM refines the search terms.

Search
Robin hits engines like Ahmia, Torch, or Haystak via the Tor proxy.

Scrape
It pulls the content of the top .onion results.

Summarize
The LLM reads the scraped text and outputs a Markdown report.

If you wanted to use Robin's core logic inside your own Python automation script, the modular architecture makes it easy to import its components

from robin.modules.search import DarkSearch
from robin.modules.llm import LLMProcessor

# 1. Initialize the Search (Assumes Tor is on 9050)
searcher = DarkSearch(proxy="socks5h://127.0.0.1:9050")
results = searcher.perform_search("targeted_keyword")

# 2. Process with AI
processor = LLMProcessor(model="gpt-4o")
summary = processor.analyze_results(results)

print(f"Investigation Summary: {summary}")

Since you are dealing with the Dark Web, always run this inside a VPN or a Docker container to isolate your environment. Avoid clicking on links manually; let the tool do the "viewing" for you to minimize the risk of executing malicious scripts in your local browser.

Would you like me to show you how to set up the Docker version for better environment isolation?