CIPHER-OSINT

CIPHER-OSINT v7.0.1 is a high-performance information gathering framework built with Golang. It leverages LLM integration for automated data analysis and utilizes Tor-based routing for secure, anonymous reconnaissance.

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About The Project

CIPHER-OSINT is built to solve a common problem in reconnaissance: information overload. Instead of manually sifting through raw logs, this tool uses Golang for high-speed scanning and integrates AI (Gemini/GPT/Claude) to filter and analyze the data.

It's designed to run efficiently on Linux environments (including Termux), handling everything from scraping to reporting with minimal configuration.

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Key Features

Feature	Details
AI Analysis	Uses Gemini, GPT-4, or Claude to clean raw data and highlight sensitive information.
Dark Web Support	Routes requests through Tor (SOCKS5) to scan .onion services safely.
High Concurrency	Built with Go routines to scan multiple targets simultaneously without lag.
Clean Reporting	Generates structured Markdown reports instead of messy JSON dumps.
Smart Filtering	Automatically strips irrelevant metadata to save on AI processing costs.

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How It Works

graph LR
    A[Target Input] --> B{Main Engine}
    B -->|Scrape| C[Surface Web]
    B -->|Proxy| D[Tor / Dark Web]
    C --> E[Data Cleaner]
    D --> E
    E --> F{AI Models}
    F -->|Summary| G[Final Report]

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Installation

Make sure you have Go installed and a working Tor connection (if using dark web features).

# 1. Clone the repo
git clone https://github.com/cipher-attack/cipher-osint.git

# 2. Install dependencies
cd cipher-osint && go mod tidy

# 3. Setup API Keys
echo "GEMINI_API_KEY=your_key_here" > .env
echo "OPENAI_API_KEY=your_key_here" >> .env
echo "ANTHROPIC_API_KEY=your_key_here" >> .env

# 4. Run the tool
go run .

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👤 THE ARCHITECT

Biruk Getachew (CIPHER)

Offensive Security Researcher & AI Integrator

I am a 12th-grade student passionate about Offensive Security and AI. I manage my entire development and auditing workflow directly from mobile interfaces, focusing on the integration of Large Language Models (LLMs) to automate vulnerability discovery and high-precision reconnaissance.

GitHub • YouTube • Telegram

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Disclaimer

This tool is for educational purposes and authorized security testing only. Please use responsibly.