ReconX

Mobile-first bug bounty reconnaissance platform for Termux on Android.

Hardware Requirements

Component	Specification
RAM	16GB (8GB physical + 8GB extended/virtual)
Storage	256GB total, 10GB+ available
CPU	MediaTek Helio G88, Octa-core Max 2.00GHz
Architecture	ARM64
OS	Android 14

Installation

curl -sSL https://raw.githubusercontent.com/0xshahriar/reconx/main/install.sh | bash

Or manual:

git clone https://github.com/0xshahriar/reconx.git
cd reconx
chmod +x install.sh
./install.sh

Quick Start

# Start locally
./start.sh

# Start with remote tunnel
./start.sh --with-tunnel

# View logs
tail -f logs/api.log

# Stop
./stop.sh

Features

• Mobile Optimized: Touch-friendly interface for Android
• Offline LLM: Local analysis with llama3.1:8b/gemma3:4b/gemma3:1b auto-scaling
• Power Resilience: Auto-pause/resume on power/internet loss
• Remote Access: Free tunneling via Cloudflare/Ngrok/LocalTunnel
• 16GB Optimized: Memory-aware operation for Helio G88

File Structure

ReconX/
├── api/              # FastAPI backend
├── core/             # Scanner modules
├── web/              # Frontend (vanilla JS)
│   ├── css/
│   ├── js/
│   └── index.html
├── data/             # SQLite database
├── logs/             # Application logs
├── wordlists/        # SecLists integration
├── scripts/          # Helper scripts
├── install.sh        # Installation script
├── start.sh          # Startup script
├── stop.sh           # Shutdown script
└── requirements.txt  # Python dependencies

Configuration

Edit config/settings.py:

• LLM_MEMORY_THRESHOLDS: RAM thresholds for model switching
• TUNNEL_PRIMARY: Preferred tunnel service
• LOW_BATTERY_THRESHOLD: Battery protection level
• MAX_CONCURRENT_SCANS: Parallel scan limit

API Endpoints

Method Endpoint Description GET /```markdown

ReconX

Mobile-first bug bounty reconnaissance platform for Termux on Android.

Hardware Requirements

Component	Specification
RAM	16GB (8GB physical + 8GB extended/virtual)
Storage	256GB total, 10GB+ available
CPU	MediaTek Helio G88, Octa-core Max 2.00GHz
Architecture	ARM64
OS	Android 14

Installation

curl -sSL https://raw.githubusercontent.com/0xshahriar/reconx/main/install.sh | bash

Or manual:

git clone https://github.com/0xshahriar/reconx.git
cd reconx
chmod +x install.sh
./install.sh

Quick Start

# Start locally
./start.sh

# Start with remote tunnel
./start.sh --with-tunnel

# View logs
tail -f logs/api.log

# Stop
./stop.sh

Features

• Mobile Optimized: Touch-friendly interface for Android
• Offline LLM: Local analysis with llama3.1:8b/gemma3:4b/gemma3:1b auto-scaling
• Power Resilience: Auto-pause/resume on power/internet loss
• Remote Access: Free tunneling via Cloudflare/Ngrok/LocalTunnel
• 16GB Optimized: Memory-aware operation for Helio G88

File Structure

ReconX/
├── api/              # FastAPI backend
├── core/             # Scanner modules
├── web/              # Frontend (vanilla JS)
│   ├── css/
│   ├── js/
│   └── index.html
├── data/             # SQLite database
├── logs/             # Application logs
├── wordlists/        # SecLists integration
├── scripts/          # Helper scripts
├── install.sh        # Installation script
├── start.sh          # Startup script
├── stop.sh           # Shutdown script
└── requirements.txt  # Python dependencies

Configuration

Edit config/settings.py:

• LLM_MEMORY_THRESHOLDS: RAM thresholds for model switching
• TUNNEL_PRIMARY: Preferred tunnel service
• LOW_BATTERY_THRESHOLD: Battery protection level
• MAX_CONCURRENT_SCANS: Parallel scan limit

API Endpoints

Method Endpoint Description GET /api/targets List targets POST /api/targets Create target GET /api/scans List scans POST /api/scans Start scan POST /api/scans/{id}/pause Pause scan POST /api/scans/{id}/resume Resume scan GET /api/system/status System stats WS /ws/system Real-time updates

LLM Auto-Scaling

Model RAM Required Use Case llama3.1:8b 6GB Deep analysis (idle) gemma3:4b 3.5GB Balanced (scanning) gemma3:1b 1.5GB Emergency (low memory)

Resilience

• State saved every 30 seconds to SQLite
• Automatic pause on internet loss (30s detection)
• Automatic resume on reconnection (10s stability check)
• Battery protection (< 20% pauses scans)
• Thermal protection (> 45C pauses scans)

Security

• Password-protected dashboard when tunneled
• Input validation and path traversal prevention
• Parameterized command execution (no injection)

License

MIT License