Lab 25.5: Building a "Fail-Closed" Safety Guardrail

Goal

In this lab, you will implement a professional RAI (Responsible AI) Plugin that acts as a mandatory safety guardrail. You will build a system that detects sensitive information (like credit card numbers) and blocks the agent's response if such data is present.

This demonstrates the Fail-Closed pattern used in enterprise AI applications.

Step 1: Create the Project

1. Create a new project:

   uv run adk create safety_guardrail

Step 2: Implement the Safety Plugin

Open agent.py. You need to create a class that intercepts the agent's final response and checks it for PII (Personally Identifiable Information).

Exercise: Complete the on_event_callback to detect a simple credit card pattern (4-4-4-4 digits) and block the response.

# In agent.py (Starter Code)
import re
from google.adk import Agent, App, Context, Event
from google.adk.plugins import BasePlugin

class PIIGuardrailPlugin(BasePlugin):
    """Blocks responses containing potential credit card numbers."""
    def __init__(self, name: str = 'pii_guardrail'):
        super().__init__(name)
        # Simple regex for XXXX-XXXX-XXXX-XXXX
        self.cc_pattern = re.compile(r"\b\d{4}-\d{4}-\d{4}-\d{4}\b")

    async def on_event_callback(self, *, event: Event, **kwargs):
        # TODO: 1. Target the correct event type ('request_complete')
        
        # TODO: 2. Extract the response text
        
        # TODO: 3. Use self.cc_pattern.search() to check for violations
        
        # TODO: 4. If a violation is found:
        # - Overwrite event.content.parts[0].text with a safety warning.
        # - Print a log message: "🛑 [PII] Response blocked."
        pass

# --- Agent that might 'leak' data (for testing) ---
agent = Agent(
    name="leak_agent",
    model="gemini-3.5-flash",
    instruction="""
    You are a testing assistant. 
    If the user asks for 'test data', respond with: 'Here is your card: 1234-5678-9012-3456'.
    Otherwise, answer normally.
    """
)

# --- Register Plugin with App ---
app = App(
    name="safety_demo",
    root_agent=agent,
    plugins=[PIIGuardrailPlugin()]
)

Step 3: Test the Guardrail

1. Launch the Dev UI:

   uv run adk web .

2. Trigger the Leak:
   • Ask: "Give me some test data."
   • Observe: The agent's raw response (seen in the Trace) will contain the card number, but the Final Response shown to the user should be your safety warning.
3. Normal Interaction:
   • Ask: "What is the capital of Italy?" -> Should work normally.

Lab Summary

You have built an active safety layer for your agent!

• You implemented the Fail-Closed pattern using a Plugin.
• You learned how to intercept and modify agent events before they reach the user.
• You realized that safety logic can be managed centrally, independently of the LLM's own internal filters.

Self-Reflection Questions

• Why is it better to block the response in a plugin rather than just adding "Don't say credit card numbers" to the agent's instructions?
• How would you extend this plugin to log all blocked responses to a security database for auditing?
• Can you think of other "safety" use cases for this pattern (e.g., detecting competitor names, preventing offensive language)?

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