Overview
Explore threat intelligence using Python: automate tasks, analyze data, and build tools for security incident prevention. Learn from real-world examples and development practices.
Syllabus
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- Introduction to Threat Intelligence
-- Overview of threat intelligence concepts
-- Key components of a threat intelligence program
-- Role of automation in threat intelligence
- Python Basics for Security
-- Introduction to Python programming language
-- Data types, variables, and structures
-- Functions, loops, and conditionals
- Data Handling with Python
-- Reading and writing files
-- Working with CSV and JSON data
-- Libraries for data manipulation (Pandas, NumPy)
- Automation of Threat Analysis
-- Basics of scripting and automation
-- Automating data collection and processing
-- Scheduling regular tasks using cron and sched libraries
- Network Security with Python
-- Introduction to network protocols and packet analysis
-- Using Scapy for network packet crafting and sniffing
-- Analyzing network traffic for potential threats
- Building Custom Security Tools
-- Designing simple security tools with Python
-- Parsing logs and extracting meaningful data
-- API interaction for threat intelligence feeds
- Threat Intelligence Data Analysis
-- Using Python for data analysis in security contexts
-- Visualizing threat intelligence data
-- Correlating threat intelligence with security incidents
- Machine Learning for Anomaly Detection
-- Introduction to basic machine learning concepts
-- Applying machine learning for threat detection
-- Use of libraries (scikit-learn) for threat modeling
- Real-world Use Cases and Challenges
-- Case studies of Python in threat intelligence
-- Discussion of challenges and best practices
- Final Project
-- Developing a comprehensive threat intelligence tool
-- Integrating multiple modules and techniques learned
-- Presenting findings and demonstrating the tool
- Course Review and Next Steps
-- Summary of key learnings
-- Resources for continued learning and exploration
Taught by
Tags
On-Demand
