review-security-k8s-agents-firewall

Name: review-security-k8s-agents-firewall
Availability: InStock
Author: gke-labs

Audit Kubernetes network policies and firewall rules for AI agent sandboxes.

42|32|Updated May 7, 2026

Search Tags:#security #compliance #kubernetes #firewall #network-policy #agent-security

Ready to run

npx skills add https://github.com/gke-labs/kube-agents --skill review-security-k8s-agents-firewall

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: review-security-k8s-agents-firewall
Source: https://github.com/gke-labs/kube-agents/tree/main/.agents/skills/review-security-k8s-agents-firewall
Command: npx skills add https://github.com/gke-labs/kube-agents --skill review-security-k8s-agents-firewall

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill mitigates the risk of unauthorized lateral movement and data exfiltration by auditing network policies and firewall configurations within AI agent execution sandboxes.

Core Features & Use Cases

Egress Control: Validates that agent sandboxes enforce default-deny egress policies to prevent unauthorized external communication.
API Isolation: Ensures agent pods are restricted from accessing sensitive internal cluster APIs, cloud metadata services, and Kubernetes control plane endpoints.
Use Case: Before deploying a new autonomous agent, use this skill to verify that its sandbox environment is properly isolated from the underlying cloud metadata service and internal cluster services.

Quick Start

Use the review-security-k8s-agents-firewall skill to audit the network policy configuration for the current agent deployment namespace.

Frequently Asked Questions about review-security-k8s-agents-firewall

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I audit Kubernetes network policies to prevent AI agent data exfiltration?▼

Auditing Kubernetes network policies for AI agent data exfiltration involves validating that containerized sandboxes enforce default-deny egress rules and restrict access to sensitive internal APIs. This skill automates that review to identify unauthorized external communication vectors.

What is the best way to isolate AI agent pods from cloud metadata services in Kubernetes?▼

Isolating AI agent pods from cloud metadata services in Kubernetes requires network policies that explicitly block egress to metadata endpoints. This skill audits your sandbox configurations to ensure autonomous agents cannot reach underlying cloud metadata services.

Can I use this skill to check if my agent sandbox restricts access to the Kubernetes control plane?▼

Yes, you can use this skill to check if your agent sandbox restricts access to the Kubernetes control plane. It audits network policies to ensure agent pods are restricted from accessing Kubernetes control plane endpoints and internal cluster APIs.

Why do I need a default-deny egress policy for autonomous infrastructure agents?▼

You need a default-deny egress policy for autonomous infrastructure agents to prevent unauthorized lateral movement and data exfiltration. This skill validates that agent sandboxes enforce these strict policies to maintain least-privilege networking compliance.

Does this skill work with standard Kubernetes network policies or does it require specific firewall rules?▼

This skill works by auditing both standard Kubernetes network policies and firewall rules. It targets the identification of egress exfiltration vectors and internal API exposure within containerized sandboxes to secure AI agent execution environments.