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AI-Driven Cybersecurity: The Future of Digital Defense

Project Chapter 16

✅ Chapter 16: AI-Driven SOC Lab — Build Your Own AI-Augmented SOC Environment

A complete hands-on guide to creating a personal AI-powered Security Operations Center at home

📌 Introduction

Modern SOCs are no longer human-only. They use:

  • SIEM + AI
  • EDR with behavioural ML
  • Threat Intel + LLMs
  • Automated IR playbooks (SOAR)
  • Network anomaly detection (NDR AI)

But most students never get access to real SOC tools. This chapter solves that by teaching you how to build a fully working AI-powered SOC lab using:

  • free tools
  • open-source ML models
  • cloud-free setups
  • your laptop or VM

This lab gives you: ✔ hands-on experience ✔ real logs and alerts ✔ AI-assisted investigation ✔ SOC automation workflows ✔ projects for your resume

Let’s build it step by step.

🧩 1. SOC Lab Architecture (Simple Diagram)

               +-------------------------+
               |   Attack Simulation     |
               |  (Caldera / AtomicRed) |
               +------------+------------+
                            |
                   Security Data Pipeline
                            |
        +-------------------+-----------------------+
        |                                           |
+-------v-------+                           +-------v-------+
|   Wazuh SIEM  | <-- Logs, Alerts -------> | Zeek NDR AI  |
+-------+-------+                           +-------+-------+
        |                                           |
        |                              ML Models (Anomaly, RF)
        |                                           |
+-------v-------+                           +-------v-------+
|  Shuffle SOAR | <------ AI Decisions ---- | LLM Assistant |
+---------------+                           +---------------+

This SOC includes:

  • SIEM (Wazuh)
  • NDR (Zeek ML)
  • SOAR (Shuffle)
  • LLM Assistant (ChatGPT locally or API)
  • Attack tools (Caldera, Atomic Red Team)

🔧 2. Tools You Will Use (All Free)

1. Wazuh (SIEM + EDR Agent)

Collects:

  • system logs
  • authentication logs
  • file integrity events
  • security alerts

2. Zeek (Network Detection Tool)

Monitors:

  • network flows
  • DNS anomalies
  • scans
  • unusual behaviour

3. Shuffle SOAR

Automates:

  • alert triage
  • enrichment
  • response
  • blocking actions

4. MITRE Caldera (Adversary Simulation)

Generates friendly attacks:

  • privilege escalation
  • lateral movement
  • credential theft

5. Atomic Red Team (TTP Testing)

Runs individual tactics from MITRE ATT&CK.

6. LLM Assistant (Optional but recommended)

Use:

  • ChatGPT
  • LM Studio + Llama
  • Local Ollama

To generate:

  • summaries
  • IR recommendations
  • Sigma rules
  • detection logic

🏗️ 3. Step-by-Step Lab Setup Guide

Below is the exact setup used by SOC teams for training.

🔹 Step 1 — Install Wazuh (SIEM/EDR)

Option A: Use Wazuh Docker (recommended)

git clone https://github.com/wazuh/wazuh-docker
cd wazuh-docker
docker-compose up -d

Components installed:

  • Wazuh Manager
  • Wazuh Indexer
  • Wazuh Dashboard

Access dashboard at:

https://localhost:5601

🔹 Step 2 — Deploy Wazuh Agents

Install agent on:

  • Windows VM
  • Linux VM
  • Kali attack machine

Example:

curl -s https://packages.wazuh.com/install.sh | bash

Agent logs will now flow to the SIEM.

🔹 Step 3 — Install Zeek for Network Monitoring

Deploy Zeek on:

  • Ubuntu VM
  • Security gateway
  • Proxmox / ESXi VM

Commands:

sudo apt install cmake make gcc g++ flex bison libpcap-dev python3
git clone --recursive https://github.com/zeek/zeek
cd zeek
./configure && make && sudo make install

Start Zeek:

sudo zeekctl deploy

Zeek generates:

  • conn.log
  • dns.log
  • http.log
  • weird.log (suspicious behaviour)

🔹 Step 4 — Add ML to Zeek (Anomaly Detection)

Install the ML plugin for Zeek:

git clone https://github.com/zeek/spicy-ml

This enables:

  • behavioural anomaly detection
  • DNS tunneling detection
  • flow classification

🔹 Step 5 — Install Shuffle SOAR

Run Shuffle via Docker:

docker run -d -p 3001:3001 frikky/shuffle:latest

Access:

http://localhost:3001

In Shuffle, integrate:

  • Wazuh API
  • VirusTotal
  • AbuseIPDB
  • LLM Webhook

🔹 Step 6 — Add LLM Assistant (Optional but powerful)

You can use:

  • ChatGPT API
  • Claude API
  • LM Studio (local)
  • Ollama (local Llama)

Integrate via:

  • Shuffle Webhook
  • Python script
  • Simple REST API

Now alerts can be sent to LLM → summarized → returned to SOAR.

🔹 Step 7 — Install MITRE Caldera (Attack Simulation)

git clone https://github.com/mitre/caldera
cd caldera
pip3 install -r requirements.txt
python3 server.py --insecure

Use Caldera to simulate:

  • privilege escalation
  • lateral movement
  • credential extraction

These events will hit Wazuh + Zeek.

🔹 Step 8 — Install Atomic Red Team

git clone https://github.com/redcanaryco/atomic-red-team

Run specific ATT&CK tests:

Invoke-AtomicTest T1059

This generates realistic attack logs.

🔥 4. Building the AI-Driven SOC Workflow

Let’s design your alert flow.

Step A: Log Collection (Wazuh + Zeek)

Wazuh collects:

  • authentication logs
  • Windows event logs
  • file integrity alerts
  • EDR behaviour logs

Zeek collects:

  • DNS
  • network flows
  • HTTP
  • SSL fingerprints

Together: 360° visibility.

Step B: AI Detection

AI models process:

  • anomalies (Isolation Forest)
  • clustering (DBSCAN)
  • behaviour scoring

Add ML jobs using:

from sklearn.ensemble import IsolationForest

Use Zeek logs as input.

Step C: SOAR Automation (Shuffle)

Create playbooks:

  • If malicious IP → auto block
  • If suspicious PowerShell → isolate endpoint
  • If login anomaly → disable user
  • If ransomware detected → stop processes

Shuffle uses:

  • triggers
  • logic blocks
  • enrichment steps
  • responses

Step D: LLM-Assisted Alert Triage

When Wazuh sends an alert:

  1. Shuffle forwards it to LLM

  2. LLM evaluates:

    • severity
    • threat behaviour
    • ATT&CK mapping
    • recommended actions

  3. Shuffle parses LLM output

  4. Executes automatic containment

Sample LLM prompt:

You are a SOC analyst.
Analyze this alert and map it to MITRE ATT&CK.
Provide severity and response steps.
Alert:
<alert JSON>

🕵️‍♂️ 5. SOC Attack Simulation (Red Team Testing)

Use Caldera + Atomic Red Team.

Example Attacks:

  • Brute force (T1110)
  • PowerShell malicious commands (T1059)
  • Credential dumping (T1003)
  • Lateral movement (T1021)

Logs flow into SIEM → ML detects anomalies → SOAR responds.

📊 6. Visualizing Alerts & Dashboards

Use Wazuh dashboard to see:

  • attack timelines
  • MITRE coverage
  • endpoint alerts
  • network events

Use Grafana + Zeek logs for:

  • DNS anomalies
  • cryptomining traffic
  • botnet C2 patterns

🧪 7. Hands-On Student Projects (Portfolio Ready)

Here are projects you can publish:

Project 1: Build an ML-Based Anomaly Detector Using Zeek Logs

Model: Isolation Forest Input: conn.log Output: suspicious flows

Project 2: Automated SOC Playbook (Shuffle SOAR)

Example playbook:

  • detect brute force
  • enrich with VirusTotal
  • auto-lock account

Project 3: LLM-Powered SOC Assistant

Build a system that:

  • summarizes alerts
  • creates reports
  • maps ATT&CK TTPs

Project 4: MITRE Red Team Attack Simulation Lab

Run:

  • T1059
  • T1003
  • T1021 Analyze SIEM results.

Project 5: Cloud Attack Detection (Optional add-on)

Feed AWS CloudTrail logs → Wazuh → ML scoring.

🛡️ 8. What Students Learn from This SOC Lab

You gain experience in:

  • SIEM
  • NDR
  • EDR
  • SOAR automation
  • LLM-driven triage
  • ML anomaly detection
  • threat intel
  • MITRE ATT&CK

These skills are exactly what companies expect in:

  • SOC Analyst
  • Threat Hunter
  • Red Team Intern
  • Cloud Security Analyst
  • Detection Engineer

📌 Key Takeaways

  • You can build a real SOC with SIEM, EDR, NDR, SOAR, and AI on your laptop.
  • AI helps analyze, triage, and respond to security events automatically.
  • Zeek + Wazuh + Shuffle + LLM is a powerful open-source SOC stack.
  • MITRE Caldera and Atomic Red Team let you simulate real attacks safely.
  • This lab gives students hands-on, job-ready experience in modern defensive cybersecurity.