Module 16 Lesson 1: Hardening the Agent
·AWS Bedrock

Module 16 Lesson 1: Hardening the Agent

Locking Down the AI. How to use IAM roles and AWS Secrets Manager to ensure your agent can only access exactly what it needs.

Hardening: The Fortress Mindset

An AI agent is only as secure as the Permissions (IAM) and Secrets (Passwords) it has access to. If you give an agent a "God-mode" IAM role, one clever hacker can prompt-inject the AI into deleting your entire cloud footprint.

1. IAM Execution Roles

Every Agent has an Execution Role. This role must follow the Principle of Least Privilege.

  • Bad: Resource: "*"
  • Good: Resource: "arn:aws:s3:::my-hr-data/*" (Only HR data).

2. Using AWS Secrets Manager

Never hardcode API keys (like for your Weather or Flight API) inside your Lambda function.

  • The Workflow:
    1. Save the key in AWS Secrets Manager.
    2. Grant the Lambda permission to secretsmanager:GetSecretValue.
    3. The Lambda retrieves the key at runtime.

3. Visualizing Secure Handoff

graph LR
    Agent[Agent Brain] -->|Triggers| L[Lambda]
    L -->|Needs Key| S[Secrets Manager]
    S -->|Returns encrypted key| L
    L -->|Calls tool| API[External World]
    
    Note[Agent NEVER sees the API key directly]

4. Why Isolation Matters

Assume your agent will eventually be "Tricked." If that happens, the Blast Radius should be tiny. If the agent only has permission to read one S3 bucket, it cannot delete your RDS database, no matter how clever the hacker's prompt is.


Summary

  • Execution Roles control what the agent's "Hands" can touch.
  • Secrets Manager keeps your credentials out of the code.
  • Blast Radius reduction is your primary defense strategy.
  • Never use high-privilege credentials for an autonomous agent.

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