Automate IaC Security Auditing with Google ADK Agents

Use the ADK CLI to scaffold a new specialized agent dedicated to security auditing. This agent will be configured with a 'Security Analyst' persona and given access to tools that can parse and analyze IaC files.

adk init --name='iac-security-auditor' --template='security-analyst'

Watch out: Ensure the agent's runtime has sufficient memory (at least 2GB) if you plan on auditing large monorepos with thousands of Terraform resources.

Expose your internal security policies (e.g., 'all buckets must be encrypted') to the agent using ADK tools. These tools allow the agent to fetch the latest compliance rules from a central repository or a managed database like BigQuery.

@adk.tool
def get_compliance_rules():
    """Fetch SOC2 and CIS compliance rules for GCP."""
    return fetch_policy_db()

Watch out: Keep the policy descriptions extremely clear. The agent relies on these descriptions to understand which rule to apply to which infrastructure block.

Configure a GitHub Action or GitLab CI pipeline to trigger the ADK agent whenever an IaC file is modified in a Pull Request. The pipeline sends the diff to the agent's API endpoint for real-time analysis.

- name: Run ADK Audit
  run: adk-agent-client audit --diff='${{ github.event.pull_request.diff_url }}'

Watch out: Use a service account with 'Vertex AI User' permissions to allow the CI pipeline to securely communicate with your ADK agent.

Configure the agent to not just flag issues, but also provide the corrective code. If a resource is missing a mandatory tag or encryption setting, the agent generates a snippet that the developer can copy-paste directly into their code.

agent.set_behavior('If a violation is found, generate the corrected HCL block.')

Watch out: The agent might occasionally hallucinate non-existent Terraform provider attributes. Always verify the generated code against the provider's official documentation.

The final step is for the agent to aggregate all findings into a concise Markdown table and post it as a comment on the Pull Request. This table should include the severity, the rule violated, and a link to the remediation snippet.

Watch out: Don't block the PR for 'Low' severity issues unless your organization has a zero-tolerance policy. Use labels to distinguish between 'Warning' and 'Critical' failures.