Automating Malware Analysis for Threat Intelligence

Overview

Explore automated malware analysis techniques for threat intelligence, including kill chain concepts, Python coding, and C2 clustering to enhance cybersecurity defenses.

Syllabus

• Introduction to Automated Malware Analysis
Overview of Malware Threats and Impact
Importance of Automation in Threat Intelligence
• Cyber Kill Chain Concepts
Understanding the Kill Chain Framework
Applying the Kill Chain to Malware Analysis
• Fundamentals of Python for Cybersecurity
Basic Python Programming
Tools and Libraries for Malware Analysis (e.g., Scapy, Volatility)
• Techniques for Automated Malware Analysis
Static Analysis Automation
File Signature and Hashing
Decompiling and Disassembling
Dynamic Analysis Automation
Sandboxing and Behavior Analysis
Memory Analysis Techniques
• C2 (Command and Control) Clustering
Understanding C2 Infrastructure
Automated Detection and Clustering of C2 Activities
• Enhancing Cybersecurity Defenses through Automation
Integration of Automated Analysis into Security Operations
Case Studies of Automated Threat Intelligence in Real-World Scenarios
• Practical Workshop: Automating a Malware Analysis Task
Setting Up a Lab Environment
Implementing a Basic Automated Analysis Pipeline
• Ethical Considerations and Best Practices
Legal Implications of Malware Analysis
Responsible Disclosure and Ethical Hacking
• Future Trends in Automated Malware Analysis
AI and Machine Learning in Malware Detection
Emerging Tools and Techniques
• Course Review and Q&A Session
Summary of Key Concepts
Open Forum for Discussion and Clarifying Doubts

Subjects

Conference Talks