Essays and breakdowns for people who design and run security systems: Zero Trust and privileged access, workforce and endpoint guardrails, detection engineering, and frameworks like NIST CSF, CDM, and MITRE D3FEND. Recent work focuses on securing AI coding agents (skill and supply-chain risk, sandboxed runtimes) plus credential and software supply-chain failures. Earlier writing includes high-profile breach and architecture case studies (for example Change Healthcare ransomware and the Duolingo API exposure), cryptography, microsegmentation, and passwordless authentication.

Docker Sandboxes: Why Your AI Coding Agents Should Never Run on Bare Metal
Executive summary Enterprises are racing to adopt AI coding agents like Claude Code to accelerate development, improve code quality, and automate maintenance tasks. But running these agents directly on developer laptops or shared workstations quietly reshapes your threat model. You are no longer hardening a human with tools; you are giving a semi-autonomous process broad, continuous access to endpoints, credentials, and networks at machine speed. On a typical enterprise laptop, an AI coding agent can execute shell commands, install packages, run arbitrary code, talk to your host Docker daemon, touch production-like data, and probe every file and credential within reach. Even if the model is benign and your vendor is trustworthy, this is still an avoidable expansion of attack surface. Misconfiguration, prompt injection, compromised dependencies, or simple agent mistakes can all turn that power into damage. ...








