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---
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. |