Security advisory · agentic AI

Your agents are in production.
Your guardrails aren't.

AI agents already call APIs, move data, and act with little oversight. Below is what that looks like when it goes wrong — and the one control that stops it. The guide is how you build that protection across your whole stack.

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That was one agent, one tool, and a guardrail you flipped on in a second. Your environment has dozens of agents and integrations — and no map of where they are or what they can reach. Here's how you actually secure them.

// the attack surface, mapped to what OWASP is formalizing

⌗ Prompt injection⌗ Tool abuse⌗ Excessive agency⌗ Data exfiltration⌗ Context poisoning⌗ Shadow AI

Treat AI as untrusted

Validate every output before it executes. Never assume it is safe.

Least privilege

Minimum data, tools, and permissions an agent actually needs.

Guardrails

Input validation, output filtering, and policy enforcement around the model.

Isolate execution

Sandboxes, scoped tokens, and limited runtime permissions.

Monitor everything

Log prompts, decisions, tool usage, and data access for audit.

Human-in-the-loop

Approval gates for payments, deletion, and external comms.

The demo flipped one switch. Real defense takes a plan.

You just watched a guardrail block a live attack. Building that guardrail — plus five more controls, mapped to every agent and permission you run — is the actual work. The guide walks you through it, end to end.

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Your agents are in production.Your guardrails aren't.