Projects

Learning how to replace manual cloud configuration with a secure, immutable Infrastructure-as-Code (IaC) pipeline to deploy hardened AWS environments. Project Impact & Core Functionality This project transitioned a manual workflow into a repeatable, version-controlled architecture, ensuring that every security group rule and subnet association is documented as code. By architecting a custom Virtual Private Cloud (VPC), I established a baseline for secure cloud operations that eliminates the risks of manual misconfiguration. The result is a functional, hardened web server environment that serves as the scalable foundation for future security labs. ...

How I built a containerized, high-performance portfolio using Hugo and Docker to ensure consistent deployments and secure web hosting. Project Impact & Core Functionality This project moved beyond simple web design to focus on the infrastructure required to host a professional cybersecurity brand. By using Docker, I created an isolated environment that ensures the site runs identically on my local machine and the production server, eliminating “it works on my machine” errors. The final architecture serves as a low-latency, secure platform to showcase my technical labs and research. ...

A segregated virtual lab used to simulate the end-to-end lifecycle of a cyberattack to identify and mitigate defensive gaps. Project Impact & Core Functionality This lab environment allowed for the safe execution of offensive security tactics against a hardened Linux target, bridging the gap between theoretical knowledge and technical application. By utilizing a Kali Linux attack vector, I successfully mapped the target’s attack surface and executed a series of exploits to gain unauthorized access. The project concludes with a full post-exploitation analysis, demonstrating how weak service configurations and poor credential management lead to total system compromise. ...

I built a high-performance Retrieval-Augmented Generation (RAG) pipeline designed to securely query massive datasets using vector embeddings and cloud-native architecture. Project Impact & Core Functionality This project engineered a scalable solution for AI-driven data retrieval, allowing a chatbot to provide accurate, source-backed answers from a sprawling Amazon product dataset. By moving away from local file processing and implementing a DuckDB streaming architecture, I ensured the system could handle enterprise-scale data without crashing under memory constraints. The final architecture is fully isolated within a VPC, ensuring that sensitive data remains invisible to the public internet while remaining highly accessible to the internal API. ...