Awesome Cybersecurity Datasets

Overview

Awesome Cybersecurity Datasets is a comprehensive GitHub repository maintained by Santiago H. Ramos, providing a curated collection of high-quality datasets for cybersecurity research and education.

Repository Statistics

• Stars: ~1,900
• Forks: 326
• Status: Actively maintained
• Community: Used by universities, private industry, and independent researchers worldwide

Featured Datasets

Network Security Datasets

Unified Host and Network Dataset

• Source: Los Alamos National Laboratory
• Coverage: ~90 days of enterprise network data
• Contains: Network events and computer events
• Use case: Insider threat detection, lateral movement analysis

Canadian Institute for Cybersecurity Datasets

• Widely used globally by researchers
• Multiple datasets covering different attack scenarios
• Well-documented and maintained

KDD Cup 1999 Data

• Classic benchmark dataset
• Simulated military network environment
• Wide variety of intrusion types
• Standard for comparing IDS performance

CTU-13 Dataset

• Labeled botnet traffic
• Includes normal and background traffic
• Real-world botnet captures
• Multiple botnet families represented

Specialized Datasets

• JavaScript Vulnerability Datasets: For web application security research
• Web Attack Payloads: Common attack patterns and exploits
• Machine Learning Firewall Data: Training data for ML-driven WAFs
• Malware Samples: Various malware families and variants
• Phishing Datasets: Email and URL phishing examples

Use Cases

• Academic Research: Training ML models, publishing research papers
• Security Tool Development: Building and testing IDS/IPS systems
• Education: Teaching cybersecurity concepts and techniques
• Benchmarking: Comparing detection algorithm performance
• Threat Intelligence: Understanding attack patterns and TTPs

Dataset Categories

• Network intrusion detection
• Malware analysis
• Web application security
• Botnet detection
• Insider threat detection
• DDoS attack analysis
• Phishing and social engineering