Intelligent Web Asset Scanner with AI-Powered Contextual Analysis

v1 Major Release: Now featuring 1,183+ Detection Patterns including Gitleaks, PII, and extensive Cloud Secrets!

ReconFusionAI is an advanced security reconnaissance tool that combines massive regex pattern libraries with AI contextual reasoning (Ollama) to detect exposed secrets, credentials, PII, and vulnerabilities across web applications with unparalleled accuracy.

• 1,183+ Total Detection Patterns (The "Brain" of the operation)
  • Gitleaks Integration: 199+ high-fidelity patterns for Stripe, Slack, modern CI/CD tokens.
  • Secrets Database: 803+ patterns for API Keys, AWS/GCP/Azure, SaaS tokens, and more.
  • PII Detection: 97+ patterns for Credit Cards (Visa/Master), SSNs, Passports (US/UK/EU), and IDs.
  • Critical & Discovery: 84 core patterns for reconnaissance and immediate threats.

• Ollama Integration: Uses qwen2.5:1.5b (or custom models) for reasoning.
• Contextual Fusion Scoring: Doesn't just match regex; it understands context (e.g., "Is this API key in a config file or a comment?").
• False Positive Reduction: AI filters out dummy data and example code.

• Production Hardened: Hardware monitoring (CPU/GPU auto-cooldown), Request Throttling, and Robust Error Handling.
• Efficient Caching:
  • AI Cache (SQLite): Reduces redundant LLM calls (1h TTL).
  • Memory Cache (LRU): Efficiently handles duplicates during large scans.
• Modular Architecture: Patterns separated into external_patterns.py for easy updates.
• Dual Output:
  • findings.json - Critical secrets with AI analysis.
  • discoveries.json - Recon & passive intel.

• Python: 3.8+
• Ollama: Installed and running efficiently.
• OS: Linux (Recommended), macOS, Windows (WSL).

pip install -r requirements.txt

# Install Ollama
curl https://ollama.ai/install.sh | sh

# Pull the optimized model
ollama pull qwen2.5:1.5b

# Clone the repository
git clone https://github.com/george1-adel/ReconFusionAi.git
cd ReconFusionAI

# Install Python requirements
pip install -r requirements.txt

# Configure settings
cp config.json.example config.json
nano config.json

Edit config.json to tailor the scanner to your hardware and needs:

{
  "telegram": {
    "bot_token": "YOUR_BOT_TOKEN",
    "chat_id": "YOUR_CHAT_ID",
    "enabled": true
  },
  "ollama": {
    "url": "http://localhost:11434/api/generate",
    "model": "qwen2.5:1.5b"
  },
  "scanning": {
    "concurrent_requests": 10,
    "timeout": 15.0
  }
}

python3 reconfusionai.py urls.txt

Useful for lists of URLs you know are valid or internal.

python3 reconfusionai.py s-mylist.txt

(Prefix the filename with s- to bypass the initial connectivity check)

Simple text file, one URL per line:

https://example.com
https://api.example.com/v1/config.js
http://dev.internal-dashboard.com

Our pattern database (external_patterns.py + patterns.py) covers:

• 100% Local Processing: AI analysis runs on your machine via Ollama. No data leaves your network.
• Safe Scanning: Built-in rate limiting and hardware monitoring prevent system overload.

Contributions are welcome! If you have new regex patterns or features:

1. Fork the repo.
2. Create your feature branch.
3. Submit a Pull Request.

This tool is designed for security professionals and authorized testing only. Usage of ReconFusionAI for attacking targets without prior mutual consent is illegal. The developers assume no liability and are not responsible for any misuse or damage caused by this program.

Made with and for the Cyber Security Community