Runtime security and compliance for the AI agent era.
I use AI coding agents all day. So does my team. So does almost everyone I talk to. The agent reads the code, writes the fix, runs the tests, installs packages, and pushes the branch. It does all of this as me. It has my SSH keys, my cloud…
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Anthropic just did something nobody expected. They built a model so good at finding security vulnerabilities that they're scared to release it publicly.
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Two days ago we put a paste box on the open internet. Type a shell command, hit Evaluate, get a verdict — , , or . Same on a second tab for MCP tool calls: tool name, JSON-style args, evaluate, verdict.
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A real bypass, a new analyzer layer, and the design pattern behind it.
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When the agent knows it's being watched — detecting eval-aware code patterns before they ship.
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Last week I sat down to write a single rule — block an AI agent from reading , the 1Password CLI v2 session cache. A junior security person would look at the ticket and think: "one file, one regex, an afternoon."
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AI coding agents are rewriting software faster than any human team could. Cursor, Windsurf, Claude Code, Gemini CLI — they ship features in minutes. But they also run shell commands, call MCP tools, and modify files with the same speed…
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I've been building software for over 20 years. And I'll be honest — when the term "AI agent" started flooding my LinkedIn feed in 2023, I rolled my eyes. It felt like a rebranding of chatbots with better PR. Little could I have predicted…
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I run an AI security company. I'm supposed to tell you AI risk is manageable — that with the right governance framework and a good dashboard, you'll sleep fine.
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The fastest way to wipe your laptop in 2026 is to ask an AI to refactor your repo. Not because the model is malicious, but because a single prompt injection, a poisoned MCP server, or a hallucinated shell command is all it takes to put one…
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