Technology Writeups:

This section contains hands-on writeups documenting experiments with modern technologies, platforms, and systems in controlled and authorized environments. The focus is on understanding how real-world systems behave in practice, including how and why they fail, how tools and automation can be leveraged effectively, and what defensive or architectural lessons emerge from that work. Topics range from applied security testing to AI-assisted platform development, with an emphasis on practical outcomes, technical reasoning, and responsible experimentation.

This writeup examines common weaknesses in Wi-Fi authentication through controlled testing and exploitation in a personal lab environment, demonstrating how real-world wireless attacks succeed and how those weaknesses can be effectively mitigated through proper configuration and defensive controls. By examining how attackers typically target wireless authentication and how those attacks succeed, this study highlights practical defensive lessons and configuration best practices that can be applied to home and enterprise networks alike.

This writeup documents an end-to-end examination of SQL injection vulnerabilities in a controlled lab environment, including intentionally creating insecure database queries, exploiting those flaws to demonstrate real-world impact, and implementing appropriate patches to eliminate the vulnerability. The focus is on understanding how SQL injection arises from common development mistakes, how attackers leverage those weaknesses in practice, and how proper defensive techniques—such as parameterized queries, input validation, and least-privilege database access—effectively mitigate the risk. Exploitation is used as a learning tool to reinforce secure development principles and highlight the importance of remediation.

This writeup documents hands-on experimentation with AI tools and agent-style workflows in a personal ServiceNow Developer Instance. It focuses on evaluating the practical capabilities of AI-assisted development within the platform, including code generation, explanation, automation support, and workflow augmentation. The goal is to assess where AI meaningfully improves workflow efficiency, how it integrates with existing ServiceNow development patterns, and what considerations are important when incorporating AI into enterprise platform workflows.