Training Course on Network Segmentation and Micro-segmentation Forensics

Course Title: Training Course on Network Segmentation and Micro-segmentation Forensics

Executive Summary

This two-week intensive course on Network Segmentation and Micro-segmentation Forensics equips professionals with the knowledge and skills to design, implement, and investigate security incidents within segmented networks. Participants will explore segmentation strategies, technologies, and forensic techniques specific to these environments. The course covers topics such as firewall rule analysis, intrusion detection in segmented networks, and data exfiltration investigations. Through hands-on labs and real-world case studies, participants will learn to identify vulnerabilities, detect malicious activity, and respond effectively to security breaches. This course will enable organizations to enhance their security posture, reduce the attack surface, and improve incident response capabilities within segmented network environments.

Introduction

Network segmentation and micro-segmentation are crucial security strategies for modern organizations, limiting the blast radius of attacks and enhancing overall security posture. However, these environments introduce unique challenges for forensic investigations. This course provides a comprehensive understanding of network segmentation principles, technologies, and forensic techniques tailored to these complex architectures. Participants will learn how to navigate segmented networks, analyze traffic flows, and identify indicators of compromise. The course covers essential tools and methodologies for conducting thorough investigations, including log analysis, packet capture analysis, and anomaly detection. By the end of this program, participants will be equipped with the expertise to effectively investigate security incidents, mitigate risks, and maintain the integrity of their segmented network environments.

Course Outcomes

• Understand the principles and benefits of network segmentation and micro-segmentation.
• Design and implement effective segmentation strategies.
• Identify and analyze network traffic patterns within segmented environments.
• Utilize forensic tools and techniques for investigating security incidents in segmented networks.
• Detect and respond to data exfiltration attempts.
• Enhance incident response capabilities within segmented environments.
• Improve overall security posture and reduce the attack surface.

Training Methodologies

• Expert-led lectures and presentations.
• Hands-on labs and practical exercises.
• Real-world case studies and incident simulations.
• Group discussions and knowledge sharing.
• Interactive Q&A sessions.
• Demonstrations of forensic tools and techniques.
• Post-course support and resources.

Benefits to Participants

• Enhanced knowledge of network segmentation and micro-segmentation principles.
• Improved skills in incident response and forensic investigation.
• Ability to design and implement effective segmentation strategies.
• Proficiency in using forensic tools and techniques.
• Increased understanding of data exfiltration detection and prevention.
• Career advancement opportunities in cybersecurity.
• Certification recognizing competence in network segmentation forensics.

Benefits to Sending Organization

• Enhanced security posture and reduced attack surface.
• Improved incident response capabilities.
• Reduced risk of data breaches and financial losses.
• Increased compliance with security regulations.
• Enhanced ability to protect sensitive data.
• Improved operational efficiency and reduced downtime.
• Enhanced reputation and customer trust.

Target Participants

• Security analysts and incident responders.
• Network engineers and administrators.
• System administrators.
• IT security managers.
• Forensic investigators.
• Cybersecurity professionals.
• Auditors and compliance officers.

WEEK 1: Network Segmentation Fundamentals and Design

Module 1: Introduction to Network Segmentation

1. Defining network segmentation and micro-segmentation.
2. Benefits of segmentation: security, compliance, and performance.
3. Segmentation strategies: physical, logical, and virtual.
4. Segmentation technologies: VLANs, firewalls, and micro-segmentation platforms.
5. Regulatory compliance standards: PCI DSS, HIPAA, and GDPR.
6. Risk assessment and segmentation planning.
7. Case study: Segmentation implementation in a financial institution.

Module 2: Segmentation Technologies and Architectures

1. VLANs and subnetting for network isolation.
2. Firewalls and access control lists (ACLs).
3. Next-generation firewalls (NGFWs) and intrusion prevention systems (IPS).
4. Micro-segmentation platforms: VMware NSX, Illumio, and Cisco ACI.
5. Software-defined networking (SDN) and network virtualization.
6. Cloud-based segmentation strategies.
7. Hands-on lab: Configuring VLANs and firewall rules.

Module 3: Designing a Segmentation Strategy

1. Identifying critical assets and sensitive data.
2. Defining segmentation zones based on risk and compliance requirements.
3. Implementing least-privilege access controls.
4. Developing firewall rule policies and segmentation guidelines.
5. Network mapping and vulnerability assessments.
6. Segmentation testing and validation.
7. Practical exercise: Designing a segmentation plan for a healthcare organization.

Module 4: Implementing Micro-segmentation

1. Understanding workload-centric security.
2. Implementing zero-trust security principles.
3. Using micro-segmentation platforms for granular control.
4. Dynamic policy enforcement and automation.
5. Integrating with existing security tools.
6. Monitoring and managing micro-segmented environments.
7. Case study: Micro-segmentation deployment in a data center.

Module 5: Security Monitoring and Logging

1. Importance of logging in segmented networks.
2. Centralized log management and analysis.
3. Security information and event management (SIEM) systems.
4. Configuring network devices for effective logging.
5. Monitoring network traffic for anomalies and suspicious activity.
6. Alerting and incident response workflows.
7. Hands-on lab: Configuring logging and SIEM integration.

WEEK 2: Network Segmentation Forensics and Incident Response

Module 6: Forensic Investigation Techniques in Segmented Networks

1. Challenges of forensic investigations in segmented environments.
2. Identifying network boundaries and access controls.
3. Analyzing network traffic flows across segments.
4. Investigating lateral movement and privilege escalation.
5. Data exfiltration detection and analysis.
6. Log correlation and event reconstruction.
7. Case study: Investigating a data breach in a segmented network.

Module 7: Forensic Tools and Methodologies

1. Network packet capture and analysis using Wireshark.
2. Log analysis using tools like Splunk and ELK Stack.
3. Endpoint detection and response (EDR) tools.
4. Memory forensics and malware analysis.
5. Timeline analysis and event correlation.
6. Reverse engineering and vulnerability analysis.
7. Hands-on lab: Analyzing network traffic using Wireshark.

Module 8: Incident Response in Segmented Environments

1. Developing an incident response plan for segmented networks.
2. Identifying and containing security incidents.
3. Eradicating malware and vulnerabilities.
4. Recovering from security breaches.
5. Communicating with stakeholders and regulatory bodies.
6. Post-incident analysis and lessons learned.
7. Simulation: Incident response exercise in a segmented network.

Module 9: Data Exfiltration Detection and Prevention

1. Identifying data exfiltration techniques.
2. Monitoring network traffic for suspicious activity.
3. Implementing data loss prevention (DLP) controls.
4. Using threat intelligence to detect known exfiltration patterns.
5. Detecting and preventing insider threats.
6. Monitoring cloud-based data storage and transfer.
7. Practical exercise: Identifying and blocking data exfiltration attempts.

Module 10: Advanced Segmentation Forensics and Future Trends

1. Advanced malware analysis techniques.
2. Investigating cloud-based security incidents.
3. Using machine learning for anomaly detection.
4. Threat hunting in segmented networks.
5. Emerging trends in network segmentation and micro-segmentation.
6. Zero-trust architecture and secure access service edge (SASE).
7. Capstone project: Developing a comprehensive segmentation forensics plan.

Action Plan for Implementation

1. Conduct a thorough assessment of the current network architecture and identify potential segmentation gaps.
2. Develop a detailed segmentation plan that aligns with business requirements and security objectives.
3. Implement segmentation technologies and access controls based on the segmentation plan.
4. Configure logging and monitoring systems to capture relevant security events.
5. Develop and test incident response procedures for segmented environments.
6. Provide training to security personnel on forensic investigation techniques.
7. Regularly review and update the segmentation plan to address emerging threats and changes in the network environment.