Video summary
Build these 5 cyber projects this weekend and get a job
Main summary
Key takeaways
Main ideas / lessons
- Hands-on experience is essential to land a first cybersecurity role. If you don’t have a job/internship, build practical home labs using only a laptop and virtual machines.
- The video proposes 5 cybersecurity home lab projects you can do this weekend to build skills relevant to real work (e.g., SOC, SIEM, blue/red teaming, and AI-assisted analysis).
- 3 labs are already covered on the channel (with guides to be shared via comments). The other 2 are “concept” labs (not yet built in the video maker’s channel content), but you can extend the earlier labs.
- A consistent best practice: document your labs (LinkedIn write-up, resume links, GitHub evidence) to show proof to recruiters.
Methodology / project list (detailed)
Prerequisites (implied approach)
- Use VirtualBox (or similar) to run virtual machines.
- Build all labs with free components where possible.
- Expect to use at least:
- A Windows VM and/or Ubuntu VM
- Optionally a Kali Linux VM as an attacker
- Skills emphasized across the labs:
- Blue teaming and red teaming
- Networking / IT fundamentals
- Python programming
- Some use of AI agents (cloud or local LLMs)
1) Build your own SIEM home lab (WSO / Wazuh SIEM) — real lab with guide
Goal: Learn SOC analyst fundamentals by creating a log/alert collection and monitoring environment.
Definition:
- SIEM = Security Information and Event Management Collects logs from devices and displays alerts/insights on a central dashboard.
Components / setup described:
- VirtualBox
- 2 VMs:
- Windows VM
- Ubuntu VM
- Install/run:
- WSO agent on the Windows VM
- WSO server on the Ubuntu VM
What to do / lab features demonstrated:
- File and integrity monitoring:
- Monitor/log changes to directories/files
- View results on the WSO dashboard
- Add an attacker VM for deeper learning:
- Add Kali Linux VM
- Attack the Windows VM
- Observe what logs/events are produced in WSO
2) AI-based cybersecurity home lab: “AI junior SOC analyst bot” — real lab with guide
Goal: Use AI to analyze security alerts/events and simulate a junior SOC workflow.
Tools described:
- VirtualBox with:
- Ubuntu VM
- Optional Kali Linux VM (attacker)
- An AI agent:
- Example used: Area AI (cloud-based AI agent)
- The presenter says you can use different agents/models, but the lab follows Area AI
- Critical requirement:
- Python programming (needed to connect events/alerts to the AI agent)
What the lab does (workflow):
- Run a Python script on Ubuntu VM
- The Python script includes an API integration to the AI agent
- Use Kali Linux to generate a DoS attack against the Ubuntu VM
- Python script:
- Generates alert logs
- Sends alert/event data to the Area AI agent
- AI agent:
- Applies guardrails/logic
- Returns analysis to Ubuntu
- Output includes:
- Alert explanation
- Risk rating
Extensibility:
- Tweak the Python + AI “guardrails” logic
- Integrate other components for increased complexity
3) Concept home lab: AI-based phishing email analyzer — concept only (not yet built by presenter)
Goal: Build a tool that analyzes phishing emails and produces a risk report, optionally with AI explanations.
Components / required knowledge:
- VirtualBox with VMs
- Python knowledge
- Optionally use:
- ChatGPT or Claude to help generate a Python script (but you must still understand it)
Proposed system behavior:
- Build a web app using Streamlit or Flask (Python backend)
- User uploads a phishing email to the web app
- The app performs analysis such as:
- URL extraction
- Keyword detection
- Risk scoring
- Generate a risk report
AI integration options:
- Use a cloud AI agent (example: Area AI) or
- Use Ollama with a local LLM
- The local AI explains findings in plain English
Portfolio/documentation intention:
- Use test cases and documentation to strengthen a recruiter-facing portfolio
4) Build your own Web Application Firewall (WAF) — real lab referenced with guide recommendation
Goal: Learn how firewalls (especially WAFs) protect against web attacks.
Rationale:
- The presenter previously covered two firewall home labs:
- pfSense network firewall
- Web application firewall
- They strongly recommend the WAF lab as more interesting
Suggested stack / lab arrangement:
- Use an Ubuntu VM
- Install/run Suricata/SafeLine WAF (presenter mentions “Safe Line web application firewall”)
- Run DVWA (Damn Vulnerable Web Application) on the Ubuntu VM
- Use Kali Linux VM to attack the DVWA app
Example attack mentioned:
- SSL injection attacks
What you implement/learn:
- WAF “controls and guards”
- How they block attacks originating from the attacker machine
5) Concept extension home lab: honeypot + attack dashboard — concept extension to the SIEM lab
Goal: Detect attacker activity using a honeypot and visualize logs in real time via a dashboard.
Relationship to prior lab:
- Extension of the Wazuh SIEM lab (project 1)
Proposed architecture (topology described generally):
- Start with the project 1 environment:
- Windows VM + Ubuntu VM as server setup for Wazuh/Wazoo SIEM
- Add a third VM:
- Run OpenCanary (honeypot simulator)
- Fake services like:
- Fake SSH
- Fake HTTP
- Fake SMTP
- Fake FTP
Attack simulation:
- Spin up a Kali Linux VM
- Attack the honeypot services
How it detects and feeds SIEM:
- OpenCanary produces logs/alerts when attackers interact/exploit fake services
- Those alerts/logs are integrated into Wazuh SIEM
Dashboard goal:
- Add a dashboard to visualize honeypot activity/logs in real time
Honeypot definition (as taught here):
- A honeypot is a decoy system/device designed to attract attackers and expose bogus, deliberately open services so you can observe exploitation attempts
Advice on using the labs to get a job (explicit guidance)
- Document everything:
- Add projects to LinkedIn
- Write short explanations
- Include links in your resume
- Upload artifacts/projects to GitHub
- Emphasis:
- Recruiters should see evidence, not just claims on a resume
- Call-to-action:
- The presenter suggests commenting “labs” to get guides for the 3 labs already covered on their channel.
Speakers / sources featured
- Speaker/host: Royden (cybersecurity content creator based in Melbourne, Australia)
- Named tools/sources used or recommended:
- WSO / Wazuh (SIEM/home lab components; “WSO” is how it’s referred to in the subtitles)
- VirtualBox
- Windows VM, Ubuntu VM, Kali Linux VM
- Area AI (cloud-based AI agent)
- Brilliant (Thinking in Python course; “Brilliant Tutor”)
- Ollama (local LLM)
- Streamlit and Flask (web app frameworks)
- ChatGPT and Claude (optional script assistance)
- SafeLine (web application firewall mentioned)
- DVWA (Damn Vulnerable Web Application)
- OpenCanary (honeypot services simulator)
- Forced Wazoo SIEM (referenced as the base for extending into the honeypot project)
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