Research and perspectives on AI data security.
Short reads for security leaders navigating a category that's still being defined — across the agents you run and the employees using AI.
You Can't Secure What You Can't See
Discovery — not blanket bans — is the way through shadow AI. How to see what employees and agents are really using, and get there without breaking the tools people already rely on.
Read →The Five Vectors of Shadow AI Discovery
Shadow AI hides in five places at once — DNS, processes, browser extensions, MCP configs and local models. Finding all five is the foundation for everything else.
Read →Your Traders Are Using ChatGPT. Your Compliance Team Doesn't Know.
Front-office staff paste positions and client data into public AI all day. Why compliance can't see it — and what runtime visibility changes.
Read →The PHI your clinicians are pasting into personal AI
Clinicians reach for personal AI with patient data in hand. What it takes to see it — and keep PHI from walking out the door.
Read →Most AI breaches start with missing access controls
Most AI deployments ship without real controls on the data they touch. What that means for teams putting AI in front of regulated records.
Read →Shadow AI is the incident you haven't logged yet
Unsanctioned AI is a fast-growing blind spot in the enterprise. Why registries miss it, and what closing the gap takes.
Read →Runtime visibility into the AI your employees use
SDKs need developer adoption; point tools miss encrypted traffic. Why seeing the AI your employees use has to happen inline, at the moment of the call.
Read →The Lethal Trifecta: Why Agentic AI Demands a New Security Paradigm
Sensitive data, untrusted content, and a way to reach out — when all three meet in one agent, the risk peaks. Why agents need data security on every call.
Read →Prompt Injection: The SQL Injection of the AI Era
A model can't tell instructions from data, so anything an agent reads can hijack it. Why the real defense is on the result leg.
Read →