A comprehensive framework for detecting and mitigating security vulnerabilities in operating systems, featuring real-time monitoring, attack simulation, and recovery recommendations.
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Real-time Vulnerability Detection 🔍
- Buffer Overflow Detection
- Trapdoor Detection
- Cache Poisoning Detection
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Interactive GUI Dashboard 📊
- Real-time Security Alerts
- Visual Attack Simulations
- Severity-based Color Coding
- Recovery Recommendations
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Attack Simulation 🎯
- Buffer Overflow Simulation
- Trapdoor Injection Simulation
- ARP Cache Poisoning Simulation
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Recovery Management 🛡️
- Detailed Recovery Steps
- Prevention Recommendations
- Best Practices Guidelines
- Python 3.x
- Tkinter (GUI)
- Flask (Web Interface)
- Threading (Real-time Monitoring)
- Python 3.x or higher
- Required Python packages:
flask
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Clone the repository:
git clone https://github.com/yourusername/security-vulnerability-detection-framework.git
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Navigate to the project directory:
cd security-vulnerability-detection-framework -
Install required packages:
pip install -r requirements.txt
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Run the application:
python new.py
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The GUI dashboard will open with the following sections:
- Simulation Controls
- Security Alerts
- Recovery Recommendations
- Visual Attack Simulations
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Use the simulation buttons to test different vulnerability scenarios:
- Buffer Overflow Simulation
- Trapdoor Injection Simulation
- Cache Poisoning Simulation
- Simulates buffer overflow attacks
- Visual representation of memory allocation
- Real-time detection and alerts
- Recovery recommendations
- Simulates hidden backdoor creation
- Port monitoring and detection
- Connection attempt visualization
- Prevention guidelines
- ARP cache poisoning simulation
- Network traffic monitoring
- Cache integrity verification
- Mitigation strategies
- Simulation Panel: Control and initiate vulnerability simulations
- Alert Panel: Real-time security alerts with severity indicators
- Recovery Panel: Detailed recovery steps and prevention measures
- Visualization Panel: Animated attack simulations
- Real-time monitoring
- Severity-based alerting
- Detailed recovery procedures
- Prevention recommendations
- Visual attack simulations
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
- AMBUJ KUMAR
- SATISH KUMAR
- JAI KUMAR RAI
- Security research community
- Open-source security tools
- Contributors and maintainers
