Build zero-trust AI agents with Google's Agent Development Kit

Autonomous AI agents connected to databases, APIs, and code execution environments can alter production systems and are vulnerable to prompt injection, unauthorized transactions, secret leakage, and host compromise, as illustrated by an ADK- and Gemini-based customer support and refund agent. The proposed zero-trust approach treats the language model as potentially unreliable and applies three external security layers: hardware-backed cryptographic signatures for every database write to establish agent identity, prevent undetected tampering, and support auditing; gVisor-based sandboxing with disabled network access, restricted capabilities, resource limits, and timeouts for dynamically generated code; and deterministic semantic gateways that inspect prompts, tool calls, and outputs for jailbreak attempts, sensitive data exposure, and violations of business rules such as refund limits. The approach recommends testing these policies through CI/CD regression tests and mapping local demonstrations to managed cloud services, including KMS/HSM-backed keys and VPC Service Controls, so that agent reasoning remains flexible while infrastructure enforces non-negotiable operational boundaries.

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