Desktop & Laptop Setup
Primary Machine
"15.6" 2-in-1 convertible with a Super AMOLED 1080p touchscreen, Intel Core i7 (11th Gen) with Intel Iris Xe Graphics, 16GB LPDDR4x RAM, 512GB NVMe SSD, and a 360° hinge for tablet/laptop switching. Runs Windows 11 + Ubuntu dual-boot for cross-platform security testing. MIL-STD-810 military-grade rated. Ships with S Pen.
- VS Code / JetBrains
- Docker Desktop & WSL2
- Wireshark / Splunk / Burp Suite
- Windows 11 + Ubuntu dual-boot
- S Pen (note-taking, diagramming)
- Thunderbolt 4 / USB-C only ports
Mobile / Responsive Testing
Browser devtools, responsive layouts, and lightweight fallback views to make the portfolio fluid on both phones and desktop screens.
- Chrome DevTools device emulation
- Touch-friendly canvas controls
- Graceful mobile fallbacks
Software Stack
Development
Python, JavaScript, Node.js, Bash, PowerShell, SQL, HTML/CSS, and Git. Most work is iteration-based: code, test, review, document.
Security Tools
Splunk, Suricata, Wireshark, Docker, Burp Suite, Nmap, and custom detection rule pipelines. I prefer practical labs over theory.
Cloud & Platform Workflow
I use a hybrid workflow where local labs and cloud services complement each other. That means building secure environments locally, then testing against real cloud telemetry and deployment patterns.
- Local lab first: Docker and VM-based experimentation for BlueTrace, VulnShop, and IoT prototypes.
- Cloud-aware design: AWS-style logging, IAM policy hardening, and detection engineering with realistic audit trails.
- Documentation step: every lab is captured as a write-up so the process and learnings are reproducible.
- Security review: threat modelling, MITRE mapping, and rule tuning are built into the delivery cycle.
Workflow Summary
Plan
Define the threat scenario, pick the lab targets, and choose tooling that matches a real-world security stack.
Build
Construct the lab, deploy services, and instrument logs so that detection and analysis can be measured.
Test
Run attack flows, validate alerts, capture telemetry, and tune detection logic to reduce false positives.
Document
Turn findings into blog posts, lab notes, and reproducible project collateral for future review and recruiter visibility.