NSM-Barii/Bluehound
NSM-Barii/Bluehound has 36 GitHub stars and 3 forks. GitHot measured 0 stars in 24 hours and 0 in 7 days. Last checked 2026-11-09 05:33 UTC. Last push 2026-07-26.
BLE scanning and anomaly detection for RF and IoT security
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README.md
OriginalBluehound
A Bluetooth Low Energy (BLE) reconnaissance and anomaly detection framework with real-time visualization.
Originally built for BLE wardriving, now extended into a dual-mode system for device discovery and environment analysis.
Features
Sniffer Mode (Wardriving)
- Discovers nearby BLE devices in real-time
- Persistent JSON database across sessions
- RSSI-based distance estimation
- Web-based radar visualization
- Fast continuous scanning
Monitor Mode (Anomaly Detection Engine)
Analyzes BLE activity in real-time to detect abnormal behavior across both devices and the environment.
Device-Level Detection
- RSSI spike detection (signal instability)
- Missed scan cycles (intermittent presence)
- Time-based disappearance tracking
Devices are dynamically classified:
stableunstable
Environment-Level Detection
- Unstable device ratio
- Device count drop score
- Real-time session analysis
Detects conditions such as:
- BLE flooding
- RF interference
- Sudden signal disruption
- Suspicious device behavior
Installation
Install BlueZ (Linux Bluetooth Stack)
Debian / Ubuntu
sudo apt-get update && sudo apt-get install -y bluez
Arch Linux
sudo pacman -S bluez bluez-utils
sudo systemctl enable --now bluetooth
Install Bluehound
git clone https://github.com/nsm-barii/bluehound.git
cd bluehound/src
python3 -m venv venv
source venv/bin/activate
pip install -r ../requirements.txt
Usage
Sniffer Mode
sudo venv/bin/python main.py --sniffer
Monitor Mode
sudo venv/bin/python main.py --monitor
Live Web Dashboard
Add --web to either mode to launch the real-time dashboard (radar + device table) at http://localhost:8000:
sudo venv/bin/python main.py --monitor --web
sudo venv/bin/python main.py --sniffer --web
Optional Flags
--save # Save scan results
-s <IP> # Send data to external server (ESP32 / LED system)
--web # Launch live web dashboard at http://localhost:8000
--window <sec> # How long each scan listens for advertisements (default: 5)
--interval <sec> # Wait time between scans; 0 = continuous (default: 0)
Example — 8s scan window with a 3s pause between scans, plus the dashboard:
sudo venv/bin/python main.py --monitor --web --window 8 --interval 3
How It Works
Sniffer Mode
- Scans BLE advertisement packets
- Extracts device metadata (MAC, vendor, RSSI, UUIDs)
- Stores results persistently
- Displays devices in a real-time web UI
Monitor Mode
- Tracks devices across scan cycles
- Builds a live model of BLE activity
- Uses weighted anomaly detection:
RSSI instability + missed cycles + signal loss → unstable device
Real-Time Metrics
- Total devices
- Unstable devices
- Unstable ratio (%)
- Drop score
Example:
Session Devices: 42
Unstable Devices: 8
Unstable Ratio: 19.04%
Drop Score: 0.27
Project Structure
src/
├── main.py
├── scanner/
│ └── BLE_Sniffer.py
├── monitor/
│ └── Monitor_Bluetooth.py
├── web/
├── database/
│ └── database.json
Use Cases
- BLE wardriving and mapping
- IoT device discovery
- RF environment monitoring
- BLE anomaly detection
- Early-stage BLE intrusion detection research
Roadmap
- BLE jamming detection
- Device fingerprinting (behavior + vendor)
- Multi-adapter support
- ESP32 real-time alert integration
- Data export / analytics pipeline
Requirements
- Linux (BlueZ required)
- Python 3.7+
- BLE-compatible adapter
Disclaimer
This tool is intended for authorized security research and educational use only.
Do not scan or analyze devices without permission.
Author
Built by
https://github.com/nsm-barii
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