Official agent skill

Gke Workload Security

by google in google/skills

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

OfficialApache-2.0Auto-check passedBackend & APIs

Install Gke Workload Security

skills CLI
$ npx skills add google/skills --skill gke-workload-security -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install google/skills gke-workload-security --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cloud/gke-workload-security .claude/skills/gke-workload-security && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
gke-workload-security
GitHub stars
21k
Token cost
~1.9k tokens
SKILL.md length
563 words
Files
4 (incl. scripts, assets)
Skills in repo
145
Repo updated
First seen
Licence
Apache-2.0

At a glance

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

  • Works in 7 steps: Security Audit → Configure Workload Identity → Implement Network Policies → …
  • Auditing workload security posture
  • SKILL.md covers Workflows, Best Practices and Resources
  • Runs Shell scripts from its folder; calls kubectl and gcloud

What it does

Gke Workload Security is an agent skill from google/skills, published by the product's own GitHub organization. Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (auditcluster.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…

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and assets (for example `assets/default-deny-netpol.yaml`, `assets/workload-identity-pod.yaml` and `scripts/audit_cluster.sh`).

It sits in Backend & APIs, covering Authorization and RBAC and Security review. It works with Google Kubernetes Engine. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.

When your agent uses it

  • Auditing workload security posture
  • Isolating namespaces
  • Applying pod security standards
  • Configuring network policies and secret volume mounts

Example prompts

  • “/gke-workload-security”

Requirements

  • A Bash shell

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Security Audit
  2. Configure Workload Identity
  3. Implement Network Policies
  4. GKE Sandbox (gVisor) Pod Isolation
  5. Pod Security Standards
  6. Secret Manager Integration (CSI Driver)
  7. Enable Network Policy Logging

What it can do on your machine

Read from SKILL.md and the folder at commit 8a1ac05. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • kubectl
    • gcloud

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • cloud.google.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Gke Workload Security loads about 1.9k tokens when it runs. Until then it costs about 216 tokens; SKILL.md has 563 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~216
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from google/skills at commit 8a1ac05, republished under its Apache-2.0 licence (© google). 563 words, ~1,939 tokens.

Download SKILL.mdSave it as .claude/skills/gke-workload-security/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
gke-workload-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).
metadata.version
1.0.1
metadata.category
Security

GKE Workload Security

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

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:

bash
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:

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

    bash
    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:

    bash
    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.

    bash
    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:

bash
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.

bash
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:

yaml
apiVersion: v1
kind: Pod
metadata:
  name: sandboxed-pod
spec:
  runtimeClassName: gvisor
  containers:
  - name: app
    image: nginx
Show full SKILL.md (240 more words)Show less
5. Pod Security Standards

Enforce security policies on namespaces using labels.

Enforce Restricted Profile:

bash
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:

yaml
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:

yaml
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:

yaml
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

© google, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, assets) in skills/cloud/gke-workload-security of google/skills.

  • SKILL.md
  • assets/default-deny-netpol.yaml
  • assets/workload-identity-pod.yaml
  • scripts/audit_cluster.sh

Open the folder on GitHubat commit 8a1ac05

Compare with similar skills

Gke Workload Security next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Gke Workload Security compared with similar skills
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Cb Security HardeningBlkLeg/CircuitBreaker201—~2.1kAutomated safety check: PassMIT
Implementing Conditional Access Policies Azure Admukul975/Anthropic-Cybersecurity-Skills34k—~689Automated safety check: PassApache-2.0
Sec Checkwaynesutton/markdown-site628—~753Automated safety check: PassMIT
Security Hardeningchmonitor/chmonitor298—~440Automated safety check: PassGPL-3.0

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Questions about Gke Workload Security

What does Gke Workload Security do?

Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Gke Workload Security is an agent skill from google/skills, published by the product's own GitHub organization. Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces.

When should I use Gke Workload Security?

Gke Workload Security fits situations like: auditing workload security posture; isolating namespaces; applying pod security standards; configuring network policies and secret volume mounts.

How do I install Gke Workload Security in Claude Code?

Run `npx skills add google/skills --skill gke-workload-security -a claude-code`. Or copy the skill folder (skills/cloud/gke-workload-security in google/skills) into .claude/skills/gke-workload-security in your project. Claude Code loads it when a task matches its description.

How do I install Gke Workload Security in Codex?

Run `npx skills add google/skills --skill gke-workload-security -a codex`. Or copy the skill folder (skills/cloud/gke-workload-security in google/skills) into .agents/skills/gke-workload-security in your project. Codex loads it when a task matches its description.

Can I use Gke Workload Security in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google/skills --skill gke-workload-security -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gke-workload-security, .gemini/skills/gke-workload-security, .github/skills/gke-workload-security and .opencode/skills/gke-workload-security in your project.

What does Gke Workload Security need to run?

Going by SKILL.md and its folder, Gke Workload Security needs a shell for the scripts in its folder and the command-line tools its instructions call (kubectl and gcloud). Our summary lists: A Bash shell.

Does Gke Workload Security access the network?

SKILL.md names 1 domain. As links in the text: cloud.google.com. This is read from the text; nothing was executed.

Is Gke Workload Security safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Gke Workload Security use?

Gke Workload Security is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Gke Workload Security use?

About 1.9k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Gke Workload Security?

Skills that share tags, products or a category with Gke Workload Security: Django Access Review (getsentry/skills, 1k stars), Cb Security Hardening (BlkLeg/CircuitBreaker, 201 stars), Implementing Conditional Access Policies Azure Ad (mukul975/Anthropic-Cybersecurity-Skills, 34k stars) and Sec Check (waynesutton/markdown-site, 628 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Gke Workload Security?

google (a GitHub organization, an official publisher) maintains it in google/skills, which has 20,994 GitHub stars. The repository holds 145 skills in this directory. The repository was last updated on October 6, 2026.

Source: google/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.