Duration 5 days – 35 hrs
Overview.
The Advanced Threat Intelligence (ATINT) Training Course provides a deep dive into threat intelligence gathering, analysis, and mitigation strategies. This course equips participants with advanced skills in threat modeling, intelligence lifecycle management, malware analysis, and strategic threat intelligence sharing. Through hands-on exercises and real-world case studies, participants will learn to identify, assess, and mitigate cyber threats, making informed decisions to enhance organizational security. The course is ideal for individuals seeking to expand their expertise in advanced threat intelligence.
Objectives
- Master the threat intelligence lifecycle, including data collection, analysis, and dissemination.
- Develop and apply threat models to identify and assess potential risks.
- Gain advanced skills in threat data analysis, reporting, and actionable intelligence development.
- Learn to conduct malware analysis for in-depth understanding of threats.
- Facilitate strategic threat intelligence sharing within and between organizations for proactive defense.
Audience
- Threat Intelligence Analysts
- Cybersecurity Professionals
- SOC Analysts and Incident Responders
- Threat Hunters and Security Researchers
- Cybersecurity Managers and Consultants
- Professionals seeking advanced skills in threat intelligence
Pre- requisites
- Basic knowledge of cybersecurity fundamentals, including threat intelligence concepts.
- Experience with cybersecurity tools, malware analysis, and incident response is beneficial.
- Familiarity with networking, systems architecture, and common attack vectors is recommended.
Course Content
Day 1: Threat Modeling and Intelligence Lifecycle
- Introduction to Advanced Threat Intelligence: Overview of the role of threat intelligence in cybersecurity.
- Threat Intelligence Lifecycle: Understanding the stages of the intelligence lifecycle, including collection, processing, analysis, and dissemination.
- Threat Modeling Fundamentals: Developing threat models to identify, assess, and prioritize threats.
- Common Frameworks: Utilizing frameworks such as MITRE ATT&CK and STRIDE for structured threat modeling.
- Identifying Threat Actors and Motives: Analyzing attacker behavior, motives, and techniques.
- Developing Intelligence Requirements: Aligning intelligence efforts with organizational goals and security needs.
Day 2: Threat Data Collection and Analysis
- Threat Data Sources and Collection Methods: Leveraging open-source intelligence (OSINT), dark web, and commercial data sources.
- Data Processing and Enrichment: Techniques for cleaning, organizing, and contextualizing raw threat data.
- Analytical Techniques for Threat Intelligence: Methods to interpret data, including trend analysis, anomaly detection, and behavioral analysis.
- Threat Correlation and Indicator Development: Identifying Indicators of Compromise (IOCs) and correlating threat data across systems.
- Threat Intelligence Reporting: Crafting clear, actionable intelligence reports for various audiences.
Day 3: Malware Analysis
- Introduction to Malware Analysis: Understanding the goals of static and dynamic malware analysis.
- Static Analysis Techniques: Analyzing malware without execution, including examining file structures, hashes, and identifying malicious indicators.
- Dynamic Analysis Techniques: Running malware in a controlled environment to observe behavior.
- Sandboxing and Virtualization: Setting up safe environments for dynamic analysis.
- Behavioral Analysis: Tracking processes, network activity, and registry changes to understand malware functions.
- Reverse Engineering Basics: Introduction to reverse engineering malware to uncover code functions and threat capabilities.
Day 4: Strategic Threat Intelligence and Information Sharing
- Strategic Intelligence: Developing long-term insights on cyber threats to inform decision-making at an organizational level.
- Intelligence Sharing Frameworks: Utilizing frameworks and standards, such as STIX/TAXII, for structured threat sharing.
- Cross-Organizational Threat Intelligence: Best practices for sharing intelligence between organizations, sectors, and threat intelligence communities.
- Legal and Privacy Considerations: Addressing legal, privacy, and ethical considerations in intelligence sharing.
- Building Relationships with Threat Intelligence Communities: Engaging with ISACs (Information Sharing and Analysis Centers) and other threat-sharing groups.
Day 5: Practical Labs and Exam Preparation
- Hands-On Labs: Practical exercises in threat modeling, data analysis, and malware analysis.
- Case Studies and Scenario-Based Labs: Analyzing real-world scenarios to apply learned concepts.
- Review of Key Concepts: Summary of key points across threat modeling, data analysis, malware analysis, and intelligence sharing.
- Practice Questions and Exercises: Sample questions to test understanding and readiness.
- Exam Strategy and Tips: Guidance on answering exam questions, managing time, and reviewing key concepts.
- Q&A Session: Final opportunity to address questions and clarify complex topics.
