ShadowStrike

ShadowStrike is a professional-grade network security assessment toolkit designed for educational and ethical hacking purposes.

⚠️ Important Notice: This tool is intended for educational and authorized testing environments only. Always obtain proper permissions before testing any systems.

Features

• Advanced Reconnaissance

  • Comprehensive network vulnerability scanning
  • Intelligent port and service detection
  • Automated system fingerprinting

• Adaptive Attack Simulation

  • SYN Flood testing
  • HTTP DDoS simulation
  • Custom exploit testing
  • Stealth probe capabilities

• Detailed Logging

  • Real-time monitoring
  • Customizable logging options
  • Comprehensive security assessment documentation

Installation

git clone https://github.com/MrShankarAryal/ShadowStrike.git
cd ShadowStrike
pip install -r requirements.txt
python gui.py

Quick Start Guide

1. Reconnaissance

1. Start Recon

   • Enter the Target IP in the designated field
   • Click "Start Recon" to begin
   • Monitor results in the log box

2. Interpret Data

   • Review open ports information
   • Analyze operating system details
   • Evaluate active services

2. Attack Modes

1. Configure Target

   • Enter Target IP and URL
   • Select appropriate attack mode

2. Available Attack Modes

   • SYN Flood: TCP connection overload testing
   • HTTP DDoS: Web server stress testing
   • Stealth Probe: Low-profile vulnerability scanning
   • Custom Exploit: Configurable attack parameters

3. Operation

   • Click "Start Attack" to begin
   • Monitor real-time feedback
   • Use "Stop Attack" to halt operations

3. Logging System

All activities are logged in logs/shadowstrike.log including:

• Reconnaissance results
• Attack timestamps
• System events
• Error messages

Project Structure

ShadowStrikeAuto/
├── core/                     
│   ├── __init__.py
│   ├── recon.py              # Reconnaissance
│   ├── auto_attack.py        # Attack coordinator
│   ├── packet_flood.py       # SYN Flood attacks
│   ├── http_ddos.py          # HTTP DDoS attacks
│   ├── stealth_probe.py      # Stealth probing
│   └── exploit_module.py     # Custom exploits
├── config/                   
│   ├── targets.json          # Target configs
│   └── attack_config.yaml    # Attack settings
└── utils/                    
    ├── ip_utils.py           # IP helpers
    ├── logger.py             # Logging system
    └── decision_engine.py    # Attack strategy

Best Practices

1. Strategic Reconnaissance

   • Conduct thorough reconnaissance before attacks
   • Analyze target infrastructure carefully

2. Attack Mode Selection

   • Choose appropriate attack modes based on reconnaissance
   • Consider target system characteristics

3. Real-Time Monitoring

   • Keep log display visible
   • Monitor for unexpected responses
   • Adjust parameters as needed

4. Documentation

   • Maintain detailed testing records
   • Document all findings systematically

Legal and Ethical Considerations

• Only use in authorized testing environments
• Obtain proper permissions before testing
• Follow responsible disclosure practices
• Comply with all applicable laws and regulations

FAQ

Q: Why is my attack not starting?

• Verify target IP and URL are correct
• Confirm attack mode is selected

Q: How can I access detailed logs?

• Check the latest .log file in the logs directory
• Files are timestamped for easy reference

Future Updates

• Enhanced reconnaissance capabilities
• AI-powered adaptive attacks
• Modular plugin system
• Interface themes
• Network mapping improvements

Technical Details

API Endpoints

Reconnaissance API

POST /api/v1/recon/scan

Parameters:
- target (string): Target IP or hostname
- scan_type (enum): SYN_STEALTH, TCP_CONNECT, UDP_SCAN
- timeout (integer): Scan timeout in seconds (optional)

Error Handling

The system implements comprehensive error handling for:

• Network timeouts
• Connection failures
• Resource limitations
• System errors

License

Copyright © 2022 Shankar Aryal. All Rights Reserved.

Contact

For questions and support, please refer to the project's GitHub repository.