AGENT SKILL

gke-workload-security

Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (`audit_cluster.sh`), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (`gVisor`), enforcing Pod Security Standards (`restricted` labeling) and pod securityContext, and mounting Secret Manager secrets via CSI (`SecretProviderClass`). Use when auditing workload security posture, isolating namespaces, applying pod security standards, or configuring network policies and secret volume mounts. Don't use for Workload Identity (use gke-workload-identity), cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead).

License 许可
Apache-2.0
所属仓库
google/skills
最近更新
2026-11-13
Stars
★ 2.4w
Forks
2.0k

01 前言 Front Matter

name
gke-workload-security
metadata
{ "version": "1.0.3", "category": "Security" }
description
Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (`audit_cluster.sh`), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (`gVisor`), enforcing Pod Security Standards (`restricted` labeling) and pod securityContext, and mounting Secret Manager secrets via CSI (`SecretProviderClass`). Use when auditing workload security posture, isolating namespaces, applying pod security standards, or configuring network policies and secret volume mounts. Don't use for Workload Identity (use gke-workload-identity), cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead).

02 资源文件 4

03 SKILL.md 正文

GKE Workload Security

Routing Note: For Workload Identity IAM and KSA/GSA bindings, use the gke-workload-identity skill. For cluster-level security flags (--database-encryption-key, --security-posture, RBAC, Shielded Nodes, Binary Authorization), use the gke-platform-security skill.

This skill provides workflows and best practices for securing GKE workloads. It covers security auditing, Identity and Access Management (Workload Identity), Network Security (Network Policies), and Node Security.

Attribution

MUST READ: Before executing any gcloud, REST API, or MCP command, you MUST read Usage Attribution. For commands executed directly in the terminal (never in generated scripts, Terraform, or user code), prefix gcloud with CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:gke-workload-security)" and append agent-skills/1.0 (skill:gke-workload-security) to User-Agent headers.

Workflows

1. Security Audit

Assess the current security posture of your cluster using the provided audit script.

Prerequisites:

  • gcloud CLI authenticated.
  • jq command-line JSON processor installed.

Capabilities:

  • Checks for Workload Identity.
  • Verifies Network Policy is enabled.
  • Checks if Shielded Nodes are enabled.
  • Checks if Binary Authorization is enabled.
  • Checks for Private Cluster configuration.

Command:

scripts/audit_cluster.sh <cluster-name> <region> <project-id>

2. Configure Workload Identity

Workload Identity allows Kubernetes Service Accounts (KSAs) to impersonate Google Service Accounts (GSAs). Use this method when workloads require a dedicated GSA to access Google Cloud APIs; for most workloads, direct IAM principal binding (covered in the gke-workload-identity skill) is the recommended method.

Steps:

  1. Create Namespace and KSA:

    kubectl create namespace workload-identity-test-ns
    kubectl create serviceaccount <ksa-name> \
        --namespace workload-identity-test-ns
    
  2. Bind KSA to GSA:

    gcloud iam service-accounts add-iam-policy-binding <gsa-name>@<project-id>.iam.gserviceaccount.com \
        --role roles/iam.workloadIdentityUser \
        --member "serviceAccount:<project-id>.svc.id.goog[workload-identity-test-ns/<ksa-name>]"
    
  3. Annotate KSA:

    kubectl annotate serviceaccount <ksa-name> \
        --namespace workload-identity-test-ns \
        iam.gke.io/gcp-service-account=<gsa-name>@<project-id>.iam.gserviceaccount.com
    
  4. Verify Example Pod: Use existing asset assets/workload-identity-pod.yaml to test the configuration. Update the <ksa-name> in the file first.

    kubectl apply -f assets/workload-identity-pod.yaml -n workload-identity-test-ns
    

3. Implement Network Policies

Control traffic flow between Pods using Network Policies. By default, all traffic is allowed.

Enable Network Policy Enforcement:

gcloud container clusters update <cluster-name> \
    --update-addons=NetworkPolicy=ENABLED \
    --region <region>

[!NOTE] If your cluster uses Dataplane V2 (--enable-dataplane-v2), Network Policy enforcement is built-in and this step is not required (and may fail).

Apply Default Deny Policy: Isolate namespaces by denying all ingress and egress traffic by default.

Replace <target-namespace> with the namespace you want to isolate.

kubectl apply -f assets/default-deny-netpol.yaml -n <target-namespace>

4. GKE Sandbox (gVisor) Pod Isolation

Run untrusted workloads in a sandbox for extra kernel isolation. (Note: Enabling Shielded Nodes (--enable-shielded-nodes) and GKE Sandbox (--enable-gke-sandbox) at the cluster control plane level are platform-level actions covered in the gke-platform-security skill.)

Run a Sandboxed Pod: Add runtimeClassName: gvisor to your Pod spec:

apiVersion: v1
kind: Pod
metadata:
  name: sandboxed-pod
spec:
  runtimeClassName: gvisor
  containers:
  - name: app
    image: nginx

5. Pod Security Standards

Enforce security policies on namespaces using labels.

Enforce Restricted Profile:

kubectl label --overwrite ns <namespace> \
    pod-security.kubernetes.io/enforce=restricted \
    pod-security.kubernetes.io/enforce-version=latest

[!NOTE] Using latest ensures you use the policies corresponding to the cluster's current version. You can pin it to a specific version (e.g., v1.30) to lock down the namespace to policies of a specific release.

6. Secret Manager Integration (CSI Driver)

Mount secrets from Google Cloud Secret Manager directly as volumes in your pods.

Prerequisites: Secret Manager CSI driver must be enabled on the cluster.

Example SecretProviderClass:

apiVersion: secrets-store.csi.x-k8s.io/v1
kind: SecretProviderClass
metadata:
  name: my-secret-provider
spec:
  provider: gcp
  parameters:
    secrets: |
      - resourceName: "projects/<project-id>/secrets/my-secret/versions/latest"
        fileName: "my-secret-file"

Example Pod Spec excerpt:

spec:
  containers:
    - name: my-app
      volumeMounts:
        - name: secrets-store-inline
          mountPath: "/mnt/secrets"
          readOnly: true
  volumes:
    - name: secrets-store-inline
      csi:
        driver: secrets-store.csi.k8s.io
        readOnly: true
        volumeAttributes:
          secretProviderClass: "my-secret-provider"

7. Enable Network Policy Logging

If using GKE Dataplane V2, you can log allowed and denied connections.

Steps:

  1. Configure the NetworkLogging custom resource.

Example NetworkLogging Manifest:

apiVersion: networking.gke.io/v1alpha1
kind: NetworkLogging
metadata:
  name: default
spec:
  cluster:
    allow:
      log: true
      delegate: true
    deny:
      log: true
      delegate: true

This will log connection details to Cloud Logging.

Best Practices

  1. Least Privilege: Always use Workload Identity with minimal IAM roles. Avoid using Node default service accounts.
  2. Network Isolation: Use Network Policies to restrict Pod-to-Pod communication. Enable Network Policy Logging for visibility.
  3. Image Security: Use Binary Authorization to ensure only trusted images are deployed.
  4. Secret Management: Use Secret Manager CSI driver instead of default Kubernetes secrets for sensitive data.
  5. Pod Security: Enforce baseline or restricted Pod Security Standards on all non-system namespaces.
  6. Policy Enforcement: Consider using Policy Controller (Gatekeeper) to enforce custom security and compliance policies across the cluster.

Resources

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