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The Ultimate CyberGuard AI Platform is a comprehensive cybersecurity demonstration system that simulates advanced AI-powered security operations. This platform showcases how modern cybersecurity tools can integrate multiple AI agents, threat intelligence, and automated response capabilities.

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๐Ÿค– CyberGuard AI Agent

A comprehensive AI-powered cybersecurity agent capable of handling multiple cybersecurity tasks including incident response, penetration testing, threat intelligence, vulnerability assessment, security monitoring, and forensic analysis.

๐Ÿš€ Features

Core Capabilities

  • Incident Response: Automated threat detection and response
  • Penetration Testing: Vulnerability scanning and exploitation simulation
  • Threat Intelligence: Gathering and analysis of threat indicators
  • Vulnerability Assessment: Comprehensive security scanning
  • Security Monitoring: Real-time security event analysis
  • Forensic Analysis: Digital evidence collection and analysis

Key Features

  • ๐ŸŽฏ Modular Architecture: Each cybersecurity domain is a separate module
  • ๐Ÿ”„ Asynchronous Processing: Non-blocking task execution
  • ๐Ÿ“Š Real-time Results: Immediate feedback and reporting
  • ๐ŸŒ Web Interface: Modern, responsive web dashboard
  • ๐Ÿ“ Comprehensive Logging: Detailed audit trails
  • ๐ŸŽจ Beautiful UI: Professional, modern interface

๐Ÿ› ๏ธ Installation

Prerequisites

  • Python 3.8+
  • pip (Python package installer)

Setup

  1. Clone or download the project files
  2. Install dependencies:
    pip install -r requirements.txt

๐ŸŽฎ Usage

Command Line Interface

Run the agent with the CLI interface:

python cyber_agent.py

Web Interface

Start the web interface:

python web_interface.py

Then open your browser to http://localhost:5000

Demonstration

Run the comprehensive demonstration:

python demo.py

๐Ÿ“‹ Available Tasks

1. Incident Response

  • Purpose: Respond to security incidents
  • Input: Target system/IP, incident type
  • Output: Threat analysis, response recommendations, evidence collection

2. Penetration Testing

  • Purpose: Simulate cyber attacks to test defenses
  • Input: Target system/application
  • Output: Vulnerability report, exploitation results, security recommendations

3. Threat Intelligence

  • Purpose: Gather intelligence on threats and threat actors
  • Input: Target domain/IP, threat type
  • Output: Threat indicators, actor profiles, attack patterns

4. Vulnerability Assessment

  • Purpose: Identify security vulnerabilities
  • Input: Target system/network
  • Output: Vulnerability report, risk assessment, remediation guidance

5. Security Monitoring

  • Purpose: Monitor security events and activities
  • Input: Target network/system
  • Output: Security events, anomaly detection, monitoring recommendations

6. Forensic Analysis

  • Purpose: Analyze digital evidence
  • Input: Target system/device
  • Output: Forensic artifacts, timeline analysis, evidence collection

๐ŸŒ Web Interface Features

Dashboard

  • Real-time agent status
  • Task execution history
  • Quick action buttons
  • Risk level indicators

Quick Actions

  • Quick Security Scan: Rapid vulnerability assessment
  • Incident Response: Emergency incident handling
  • Penetration Test: Automated penetration testing
  • Threat Intelligence: Threat analysis and intelligence gathering

Results Display

  • Interactive results modal
  • Risk level visualization
  • Detailed findings and recommendations
  • Evidence collection summary

๐Ÿ”ง API Endpoints

Core Endpoints

  • GET /api/status - Get agent status
  • GET /api/capabilities - Get available capabilities
  • POST /api/tasks - Create and execute a task
  • GET /api/tasks - Get task history
  • GET /api/tasks/<task_id> - Get specific task details

Specialized Endpoints

  • POST /api/quick-scan - Perform quick security scan
  • POST /api/incident-response - Handle incident response

๐Ÿ“Š Example Usage

Python API

from cyber_agent import CyberAgent, TaskRequest, TaskType
import asyncio

async def main():
    agent = CyberAgent()
    
    # Create a penetration testing task
    request = TaskRequest(
        task_type=TaskType.PENETRATION_TESTING,
        target="example.com",
        parameters={"scan_type": "comprehensive"}
    )
    
    # Execute the task
    result = await agent.execute_task(request)
    
    print(f"Task completed: {result.status}")
    print(f"Risk level: {result.risk_level}")
    print(f"Findings: {len(result.findings)}")

asyncio.run(main())

Web Interface

  1. Open http://localhost:5000
  2. Click "Quick Security Scan"
  3. Enter target (IP, domain, or hostname)
  4. Click "Start Scan"
  5. View results in the modal

๐ŸŽฏ Demonstration Scenarios

The demo.py script includes comprehensive demonstrations:

  1. Malware Detection Response
  2. Web Application Penetration Testing
  3. Network Vulnerability Assessment
  4. APT Threat Intelligence
  5. SIEM Security Monitoring
  6. Digital Forensic Analysis

๐Ÿ”’ Security Considerations

  • This is a demonstration/training tool
  • Do not use against systems you don't own
  • Always follow responsible disclosure practices
  • Ensure proper authorization before testing

๐Ÿš€ Future Enhancements

  • Integration with real security tools (Nmap, Metasploit, etc.)
  • Machine learning threat detection
  • Automated remediation capabilities
  • Integration with SIEM platforms
  • Advanced reporting and analytics
  • Multi-tenant support

๐Ÿ“ License

This project is for demonstration purposes. Please ensure compliance with local laws and regulations when using cybersecurity tools.

๐Ÿค Contributing

This is a demonstration project showcasing AI capabilities in cybersecurity. Feel free to extend and improve the functionality!


๐ŸŽ‰ Ready to revolutionize cybersecurity with AI!

This AI agent demonstrates the potential for automated cybersecurity operations, combining multiple security domains into a unified, intelligent system.

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The Ultimate CyberGuard AI Platform is a comprehensive cybersecurity demonstration system that simulates advanced AI-powered security operations. This platform showcases how modern cybersecurity tools can integrate multiple AI agents, threat intelligence, and automated response capabilities.

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