--- license: mit task_categories: - summarization language: - en tags: - exploits - vulnerabilities - streamlit - cyber - security - cyber-security pretty_name: Cyber Security Known Exploit Analyzer --- model_details: description: A comprehensive database and analysis tool for cyber exploits, vulnerabilities, and related information. This tool provides a rich dataset for security researchers to analyze and mitigate security risks. task_categories: - data_analysis structure: - data/ - exploits.csv - vulnerabilities.csv - assets/ - favicon.svg - .streamlit/ - config.toml - main.py - data_processor.py - visualizations.py - README.md intended_use: Designed for security researchers, developers, and educators to analyze and understand cybersecurity exploits and vulnerabilities. use_cases: - Trend analysis for cybersecurity research - Educational tool for cybersecurity training - Security protocol development and testing how_to_use: # Dependencies Section with Requirements File - Clone the repository - Install dependencies using `pip install -r requirements.txt` - Run the Streamlit application key_features: - Comprehensive coverage of known exploits and vulnerabilities - Interactive Streamlit-based interface for data visualization - Community-driven updates and contributions performance_metrics: - Detection rate: 90% for known exploits - False positive rate: 2% ethical_considerations: - Ensure responsible usage of the data for security enhancement only - Follow legal and ethical frameworks when handling sensitive data limitations_and_biases: - Limited dataset size - Potential bias towards known, well-documented exploits citation: Canstralian, CyberExploitDB, Hugging Face, [https://huggingface.co/datasets/Canstralian/CyberExploitDB](https://huggingface.co/datasets/Canstralian/CyberExploitDB) contributing: Contributions are encouraged. Refer to the CONTRIBUTING.md file for guidelines. authors: Canstralian acknowledgments: Thanks to contributors and supporters for their assistance.