What I Do
I build security tools and write about my discoveries along the way. My work spans reconnaissance automation, vulnerability research, and exploring how AI can actually help cybersecurity—not just the marketing hype, but where it genuinely solves real problems.
Current Projects
MCP Integrations - Building Model Context Protocol servers that bring security data directly into AI workflows. My mcp-censys integration lets you query Censys data conversationally, turning complex API calls into natural language.
Nerve ADK - Agent orchestration and development work.
Prismis - A data ingestion and analysis platform.
Arsenl - Security tooling and automation projects.
Security Tools - From censyspy for FQDN discovery to Sayable for making AI output more speech-friendly.
Recent Discoveries
I’ve been documenting systematic approaches to prompt engineering and exploring why certain AI “reasoning” methods actually make results worse. My work focuses on bridging the gap between AI capabilities and reliable execution in security contexts.
Writing Focus
My writing covers the messy reality of modern security work. I explore questions like: Why do vulnerability scanners generate so much noise? How can we systematically evaluate AI performance? What happens when theoretical security frameworks meet practical exploitation requirements?
I’m particularly interested in the evolution of security roles as AI capabilities expand—how technical depth combines with strategic thinking to orchestrate AI systems while maintaining the adversarial creativity that technology can’t replicate.
Beyond Security
When I’m not building tools or analyzing data:
- Training BJJ
- Reading philosophy
- Making music
- Thinking about random problems
Background
I’ve spent years working on attack surface management, vulnerability discovery campaigns, and building automation for security analysis. My approach focuses on what actually works in practice versus what sounds impressive in theory.