Policy Engine

• Key points are in the visual diagram above.

Hard-coding if/else security logic across agents doesn't scale. A centralized policy engine gives security teams one place to update rules without redeploying agents.

A policy engine is customs regulations — agents declare what they're carrying (action + data), rules decide pass, inspect, or confiscate.

Scenario

Policy: `deny if action == 'export_data' and data.classification == 'confidential' and not user.has_role('analyst')` — agent cannot exfiltrate.

Solution

In Agent Security & Governance, apply Policy Engine to this scenario: Policy: `deny if action == 'export_data' and data. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.

Do this before moving to the next module — reading alone is not enough.

Open the Code Walkthrough below and run it locally. Change one parameter related to Policy Engine (e.g. model, temperature, top_k, or tool name), observe the difference in output, and write 2–3 sentences explaining what changed.

Highlighted lines show where Policy Engine happens in the code.

1# OPA Rego example2allow {3    input.action == "read"4    input.data.classification == "public"5}6deny { input.action == "delete" }

• Treating Policy Engine as a black box without evaluation
• Ignoring cost and latency in production
• Skipping error handling for policy engine

Quick recap — the most important points from this module.