metadata:
  license: mit
  task_categories:
    - summarization
  language:
    - en
  tags:
    - exploits
    - vulnerabilities
    - streamlit
    - cyber
    - security
    - cyber-security
  pretty_name: Cyber Security Known Exploit Analyzer

model_details:
  model_name: Cyber Security Known Exploit Analyzer
  dataset: Canstralian/CyberExploitDB
  license: MIT License
  language: Python
  tags:
    - exploits
    - vulnerabilities
    - cybersecurity
    - streamlit
  size: Small Dataset (exploits.csv, vulnerabilities.csv)
  pretty_name: Cyber Security Known Exploit Analyzer

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.