ShadowStrike: Advanced Network Security Testing

Empowering Ethical Hackers with Cutting-Edge Network Security Tools

Advanced Reconnaissance

Comprehensive network vulnerability scanning with intelligent port and service detection.

Adaptive Attack Simulation

Sophisticated attack modes including SYN Flood, HTTP DDoS, and custom exploit testing.

Detailed Logging

Real-time, customizable logging for thorough security assessment documentation.

Toolkit Workflow

1. Reconnaissance: Intelligent network intelligence gathering
    2. Analysis: Advanced vulnerability evaluation
    3. Simulation: Precision-targeted controlled attacks
    4. Documentation: Comprehensive interaction logging

Elevate Your Security Testing

ShadowStrike provides professional-grade network security assessment capabilities.

Get ShadowStrike

User Documentation

⚠️ Important Notice: ShadowStrike is intended for educational and ethical hacking purposes only. Use this tool exclusively in authorized environments and testing scenarios.

Installation

Get ShadowStrike

OR

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

Quick Start Guide

1.1. Reconnaissance

1Start Recon

Enter the Target IP in the designated field
Click on the Start Recon button to initiate reconnaissance
Results will display in the log box

2Interpret Recon Data

Review displayed information about open ports, operating systems, and active services
Use this intelligence to inform your testing strategy

1.2. Attack Modes

1Select Target Details

Enter both Target IP and Target URL

2Choose Attack Mode

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

3Initiate Attack

Click the Start Attack button
Monitor real-time feedback in the log section

4Stop Attack

Press the Stop Attack button to halt operations
Always terminate attacks promptly to prevent unintended system damage

1.3. Logging and Monitoring

All activities are logged in the logs directory under shadowstrike.log

Logged Information:

Reconnaissance results (ports, OS, services)
Attack timestamps and system events
Error messages and warnings

Effective Use of ShadowStrike

1. Strategic Reconnaissance

Conduct thorough reconnaissance before launching attacks
Analyze target infrastructure to select appropriate attack modes

2. Attack Mode Selection

Choose attack modes based on reconnaissance findings
Consider target system characteristics when selecting attack parameters

3. Real-Time Monitoring

Keep log display visible during operations
Monitor for unexpected responses or errors
Adjust parameters based on real-time feedback

4. Documentation

Maintain detailed records of all testing sessions
Include reconnaissance data and attack results in reports
Document discovered vulnerabilities systematically

Legal and Ethical Considerations:

Only use ShadowStrike in authorized testing environments
Obtain proper permissions before testing any systems
Follow responsible disclosure practices for discovered vulnerabilities

FAQ and Troubleshooting

Q: Why is my attack not starting?

Verify target IP and URL are correctly entered
Confirm an attack mode is selected

Q: How can I access detailed logs?

Open the latest .log file in the logs directory. Each log is timestamped for easy reference.

Future Updates and Planned Features

Enhanced Reconnaissance: Network mapping and automated vulnerability detection
Advanced Attack Modules: AI-powered adaptive attacks
User Customization: Modular plugin system and interface themes

Developer Documentation

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

Key Components

Reconnaissance Module

Handles target data collection including port scanning and OS detection. Initiates before attacks to gather intelligence.

Attack Module

Coordinates attack strategies based on reconnaissance data and user configurations. Manages different attack types.

Utilities Module

Provides IP handling, logging, and decision-making functionality. Core support for all operations.

Interface Module

Manages the PyQt5 GUI and automatic attack mode interfaces. Handles user interaction and display.

Architecture Overview

ShadowStrike is built on a modular architecture that separates concerns into distinct components while maintaining high cohesion and loose coupling. The system is designed around these core principles:

Asynchronous operation handling for non-blocking network operations
Event-driven architecture for real-time attack monitoring
Modular plugin system for extensible attack vectors
Comprehensive logging and monitoring infrastructure

Core Components

1. Network Reconnaissance Engine

The reconnaissance engine implements intelligent network scanning with adjustable stealth levels.

    from shadowstrike.core.recon import ReconEngine
    
    async def perform_stealth_scan(target: str, stealth_level: int = 2):
        recon = ReconEngine(
            target=target,
            scan_type='SYN_STEALTH',
            timeout=30,
            max_retries=3
        )
        
        try:
            scan_results = await recon.execute_scan()
            return scan_results
        except ReconTimeout as e:
            logger.error(f"Scan timeout: {str(e)}")
            raise

2. Attack Orchestration System

The attack orchestrator manages concurrent attack vectors while maintaining system stability.

    from shadowstrike.core.orchestrator import AttackOrchestrator
    from shadowstrike.models import AttackVector
    
    async def launch_coordinated_attack(
        target: str,
        vectors: List[AttackVector],
        duration: int
    ):
        orchestrator = AttackOrchestrator(
            max_concurrent_attacks=5,
            resource_monitor=True
        )
        
        attack_config = {
            'target': target,
            'vectors': vectors,
            'duration': duration,
            'fallback_strategy': 'graceful_degradation'
        }
        
        return await orchestrator.execute(attack_config)

API Reference

Reconnaissance API

POST /api/v1/recon/scan

Initiates a new reconnaissance scan on the target.

Parameters

Parameter	Type	Description	Required
target	string	Target IP or hostname	Yes
scan_type	enum	SYN_STEALTH, TCP_CONNECT, UDP_SCAN	Yes
timeout	integer	Scan timeout in seconds	No

Error Handling

ShadowStrike implements a comprehensive error handling system:

    from shadowstrike.exceptions import ShadowStrikeError
    
    class ReconError(ShadowStrikeError):
        """Base exception for reconnaissance errors."""
        def __init__(self, message: str, error_code: int):
            super().__init__(message)
            self.error_code = error_code
    
    class NetworkTimeout(ReconError):
        """Raised when network operations timeout."""
        pass
    
    # Implementation
    try:
        await recon_engine.execute()
    except NetworkTimeout as e:
        logger.error(f"Operation failed: {e.error_code}")
        await cleanup_resources()
    except ShadowStrikeError as e:
        logger.critical(f"Critical error: {str(e)}")
        await emergency_shutdown()

Performance Optimization

Key performance considerations for production deployment:

Implement connection pooling for HTTP-based attacks
Use asynchronous I/O for network operations
Employ rate limiting and backoff strategies
Monitor system resource utilization

    from shadowstrike.utils.performance import ConnectionPool
    
    async with ConnectionPool(
        max_size=100,
        timeout=30,
        keep_alive=True
    ) as pool:
        async for target in targets:
            await pool.execute_attack(
                target,
                rate_limit=1000,  # requests per second
                backoff_strategy='exponential'
            )

Security Considerations

Critical security practices for implementation:

Implement proper authentication and authorization
Encrypt all sensitive configuration data
Use secure random number generation for attack patterns
Implement rate limiting and attack throttling
Maintain comprehensive audit logs

Testing Framework

Comprehensive testing suite for validation:

    import pytest
    from shadowstrike.testing import MockNetwork
    
    @pytest.mark.asyncio
    async def test_attack_vector(mock_network: MockNetwork):
        config = {
            'target': '192.168.1.1',
            'vector': 'SYN_FLOOD',
            'duration': 30
        }
        
        async with mock_network.simulate():
            result = await launch_attack(config)
            assert result.success
            assert result.packets_sent > 0
            assert result.response_time < 1000  # ms

Legal and Ethical Requirements