Network & Security Engineer focused on AI Security research, evidence-driven diagnostics and engineering tools for the investigation of complex systems.
Projects focused on understanding complex behaviour, reducing investigation time and turning technical evidence into defensible conclusions.
A structured experimental environment for studying security weaknesses in Large Language Models and AI systems, including prompt injection, adversarial behaviour, evaluation methodologies and defensive controls.
An evidence-driven investigation platform designed
to transform raw packet captures into structured
TCP analysis, incident evidence and engineering
conclusions.
From Packets to Root Cause.
Network architecture, TCP/IP, VPN, security infrastructure, troubleshooting and complex incident investigation.
LLM security research, prompt injection, adversarial testing, threat modelling and security evaluation methodologies.
Building deterministic tools that convert telemetry and protocol evidence into reproducible technical investigations.