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gke-workload-security

Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces.

Install / Use

npx skills add google/skills --skill gke-workload-security

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

97/100

Category

Security

Supported Platforms

Universal

Our assessment of gke-workload-security

gke-workload-security scores 97/100 on our quality scale, 77th of 544 Security skills we index (top 15%).

Its SKILL.md is 7.4 KB long, well organised into 11 sections with 8 code examples: a thorough specification that gives an agent plenty to work with.

With 20,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
18/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 2 days ago, so gke-workload-security is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

gke-workload-security compared with similar skills

All 4 of these similar skills score higher than gke-workload-security; compare them before choosing.

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Frequently asked questions

How do I install gke-workload-security?
Run npx skills add google/skills --skill gke-workload-security. The install tabs above show the steps for each supported agent.
Which AI agents does gke-workload-security work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is gke-workload-security safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is gke-workload-security still maintained?
The repository was last updated 2 days ago, so gke-workload-security is actively maintained.

name: gke-workload-security description: >- Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (audit_cluster.sh), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (gVisor), enforcing Pod Security Standards (restricted labeling), and mounting Secret Manager secrets via CSI (SecretProviderClass). Use when auditing cluster security posture, isolating namespaces, applying pod security standards, setting up Workload Identity, or configuring network policies and secret volume mounts. Don't use for cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead). metadata: version: "1.0.0" category: Security

GKE Workload Security

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.

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). This is the recommended method for workloads to access Google Cloud APIs.

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-s…[redacted]"

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

Related Skills

View on GitHub
GitHub Stars20.3k
CategorySecurity
Updated2d ago
Forks1.7k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions