the agent.shield field guide
practical writing on securing ai agents in production — access control, human-in-the-loop review, kubernetes, databases, and audit trails. answer-first, no fluff.
how to secure ai agents in kubernetes production
a practical playbook for securing ai agents that touch kubernetes: scope rbac, intercept destructive kubectl calls, and keep a human in the loop before prod changes.
read the guide→preventing ai agent data breaches: a security guide
how to stop ai agents from causing data breaches: limit data access, intercept destructive and exfiltrating calls, and keep an audit trail your incident team can trust.
read the guide→ai agent access control for devops and sre teams
build access control for ai agents the way sre teams build it for services: least privilege, short-lived scopes, and a human gate on irreversible actions.
read the guide→human-in-the-loop security for ai operations
what human-in-the-loop security means for ai operations, when to require a human gate, and how to add one without killing the speed that makes agents useful.
read the guide→ai agent firewall vs traditional security: what's the difference
an ai agent firewall guards actions, not the perimeter. here's how it differs from wafs, iam, and network firewalls — and why agents need a new layer.
read the guide→logging and auditing ai agent actions in production
how to log and audit ai agent actions in production so incident reviews take minutes, not days: capture every call, decision, and identity in one trustworthy trail.
read the guide→best practices for deploying ai agents safely
a checklist for deploying ai agents safely in production: scope access, gate irreversible actions, log everything, and roll out in stages from read-only to write.
read the guide→ai agents and database security: a practical guide
a practical guide to ai agents and database security: scope connections, intercept destructive sql, gate drops and mass updates, and log every query in production.
read the guide→building trust in ai automation: security workflows
trust in ai automation is earned through security workflows: visible guardrails, human approval on irreversible actions, and an audit trail that proves what happened.
read the guide→ready to put a human back in the loop?
spin up your first proxy in minutes. no agent rewrite, no new sdk — just a url your agent already knows how to call.