Agent Sandboxing: Isolation Strategies for Execution Environments

Agent Sandboxing#

An AI agent that can execute code, run shell commands, or call APIs needs a sandbox. Without one, a single bad tool call – whether from a bug, a hallucination, or a prompt injection attack – can read secrets, modify production data, or pivot to other systems. This article is a decision framework for choosing the right sandboxing strategy based on your trust level, threat model, and performance requirements.

Container Runtime Security Hardening

Why Runtime Security Matters#

Container images get scanned for vulnerabilities before deployment. Admission controllers enforce pod security standards at creation time. But neither addresses what happens after the container starts running. Runtime security fills this gap: it detects and prevents malicious behavior inside running containers.

A compromised container with a properly hardened runtime is limited in what damage it can cause. Without runtime hardening, a single container escape can compromise the entire node.

GKE Security and Identity

GKE Security and Identity#

GKE security covers identity (who can do what), workload isolation (sandboxing untrusted code), supply chain integrity (ensuring only trusted images run), and data protection (encryption at rest). These features layer on top of standard Kubernetes RBAC and network policies.

Workload Identity Federation#

Workload Identity Federation is the successor to the original Workload Identity. It removes the need for a separate workload-pool flag and uses the standard GCP IAM federation model. The concept is the same: bind a Kubernetes service account to a Google Cloud service account so pods get GCP credentials without exported keys.