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📌 Overview

This repository documents a hands-on Security Operations Centre (SOC) simulation based on a segmented healthcare network that handles sensitive patient data.
The lab demonstrates how network misconfigurations, insufficient monitoring, and weak segmentation can expose critical systems and how centralised visibility, detection, and response can significantly improve security posture.

The project mirrors real-world SOC workflows by combining network design, attack simulation, SIEM monitoring, traffic analysis, and active response in a controlled environment.


🧠 Lab Concept

Healthcare organisations are prime targets for cyberattacks due to the value of Electronic Health Records (EHRs) and the stringent regulatory requirements.
This lab simulates a healthcare technology environment with:

  • A DMZ-hosted Ubuntu EHR server
  • Internal SOC and analyst systems
  • Centralised security enforcement and monitoring

Common attacker techniques, such as network reconnaissance and SSH brute-force attempts, are simulated to evaluate the effectiveness of detection, correlation, and response across segmented network zones.


🎯 Objectives

  • Design and deploy a segmented WAN / LAN / DMZ architecture
  • Identify weaknesses caused by overly permissive firewall rules
  • Simulate real-world attack techniques
  • Detect malicious activity using SIEM and packet analysis
  • Demonstrate automated incident response
  • Apply remediation to improve security posture

🛠 Tools & Technologies Used

Category Tools
Network & Firewall pfSense
SIEM / SOC Platform Wazuh
Operating Systems Ubuntu, Kali Linux
Traffic Analysis Wireshark
Attack Simulation Nmap, Hydra
Design & Documentation Draw.io, VirtualBox

🏗 Network Architecture

  • WAN – External network access
  • LAN – Internal SOC systems (Kali, Wazuh Manager)
  • DMZ – Ubuntu-based EHR server
  • pfSense – Central routing, firewall enforcement, and logging

Initial misconfigurations (broad “allow any” rules and exposed services) were intentionally identified to demonstrate real-world security gaps.


🔍 Attack Simulation

Simulated attacks were executed from Kali Linux to emulate common attacker behaviour:

  • Network reconnaissance with Nmap
  • Service and port discovery
  • SSH brute-force attempts using Hydra
  • Packet capture and analysis via Wireshark

These activities generated realistic indicators suitable for SOC detection and investigation.


🚨 Detection & Response

  • Wazuh agents collected authentication, system, and security logs
  • Alerts detected:
    • Port scanning
    • Repeated SSH authentication failures
    • Suspicious access attempts
  • Log correlation identified the attacker source IP, rules group and MITRE technique
  • Active Response automatically blocked malicious IPs via firewall actions
  • pfSense rules were hardened, and unnecessary services (e.g., SNMP) were disabled

📊 Key Findings

  • Network segmentation alone is ineffective without strict firewall enforcement
  • Overly permissive rules increase the risk of lateral movement
  • Centralised logging and correlation greatly improve visibility
  • Attack activity is often noisy and detectable when monitoring is correctly configured
  • Automated response significantly reduces exposure time

🧩 Indicators of Compromise (IoCs)

  • Repeated SSH login failures
  • Port scanning patterns
  • Correlated Wazuh alerts tied to sshd rule group
  • Source IP identified as the attacking Kali host

✅ Key Takeaways

  • Proper firewall configuration is critical to segmentation
  • SIEM effectiveness depends on log quality and rule tuning
  • Packet-level evidence strengthens investigations
  • SOC operations rely on integration, correlation, and response
  • Continuous validation of controls is essential

🔐 Recommendations

  • Enforce least-privilege firewall policies
  • Disable unnecessary services on security devices
  • Harden SSH with key-based authentication and restricted sources
  • Improve log retention and alert tuning
  • Establish incident response playbooks
  • Regularly review and test firewall and SOC configurations

🧾 Conclusion

This project demonstrates how a well-integrated SOC environment can detect, analyse, and respond to common attack techniques in a healthcare context.
By combining segmentation, SIEM monitoring, traffic analysis, and automated response, the lab reflects real-world blue-team operations and highlights the importance of continuous security validation.


📄 Full Project Report

The complete technical report, including screenshots, configurations, alerts, and traffic analysis evidence, is available below:

👉 SOC Threat Detection in a Segmented Healthcare Network – Full Report (https://drive.google.com/file/d/1ASOgZOTvpC-tx5cO-0MWDXvvhmfVVDP_/view?usp=sharing)


“Defence is not a single decision, but a continuous practice of attention and restraint.”
— Oluwamuyiwa Aikomo

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Hands-on SOC lab demonstrating threat detection, log correlation, and incident response in a segmented enterprise network using SIEM and network monitoring.

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