Research & Publications
Welcome to my research library, where I share my ongoing work, my published work, technical studies, and findings in offensive security, AI red teaming, and vulnerability analysis. This section highlights in-depth research, published books, security frameworks, and case studies focused on exploit development, patch evaluation, and adversarial testing across modern technologies and complex digital ecosystems.
Benchmarking GenAI Risk Detection with the OWASP AI Testing Guide
This project benchmarks the OWASP AI Testing Guide (AITG) by running its test cases against real LLM applications to measure how effectively it detects modern GenAI exploits. The goal is to quantify AITG’s strengths and blind spots, validate its coverage, and provide evidence-based recommendations for improving future versions.
Detecting Living-Off-the-Land Attacks: A Behavioral Telemetry Study
Simulate offensive post-compromise LOTL attacks using only native tools to expose detection blind spots and deliver actionable playbooks for faster containment.
Detecting In-Memory Malware Implants: Behavioral Indicators for Reflective Injection and Runtime Polymorphism
A red-team driven study that reveals how in-memory implants behave and delivers practical detection patterns and evaluation guidance for defenders.