My research focuses on understanding how sensitive data is unintentionally exposed
at scale across public web infrastructure. I design and deploy measurement systems
that analyze millions of URLs using a combination of dynamic rendering,
programmatic inspection, and AI-assisted classification.
This work involves building end-to-end pipelines that detect and validate leaks
such as authentication tokens, financial information, and personally identifiable
data — combining heuristic filtering with LLM-based reasoning to improve precision
while maintaining scalability.
Beyond research, I have hands-on experience in web application security,
network traffic analysis, and vulnerability discovery, with findings leading
to publicly disclosed CVEs.
