Agent skill

Securing Kubernetes On Cloud

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Hardens managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity (IRSA for EKS, Workload Identity for GKE, Managed Identities for…

Apache-2.0Auto-check passedDevOps & Cloud

Install Securing Kubernetes On Cloud

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill securing-kubernetes-on-cloud -a claude-code

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

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills securing-kubernetes-on-cloud --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/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/securing-kubernetes-on-cloud .claude/skills/securing-kubernetes-on-cloud && 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
securing-kubernetes-on-cloud
GitHub stars
34k
Token cost
~3.3k tokens
SKILL.md length
645 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Hardens managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity (IRSA for EKS, Workload Identity for GKE, Managed Identities for…

  • Works in 6 steps: Enforce Pod Security Standards → Configure Cloud-Native Workload Identity → Implement Network Policies → …
  • Deploying a new managed Kubernetes cluster with security requirements
  • SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; calls kubectl, az and gcloud; reaches falcosecurity.github.io and hooks.slack.com

What it does

Securing Kubernetes On Cloud is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Hardens managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity (IRSA for EKS, Workload Identity for GKE, Managed Identities for AKS), RBAC scoping, image admission controls, and runtime security monitoring. Use when deploying a new managed Kubernetes cluster with security requirements or hardening an existing EKS, AKS, or GKE cluster after an audit or pentest finding.

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in DevOps & Cloud, covering Container orchestration, Authorization and RBAC and Penetration testing. It works with Kubernetes and Google Kubernetes Engine. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Deploying a new managed Kubernetes cluster with security requirements
  • Hardening an existing EKS
  • GKE cluster after an audit
  • Pentest finding

Example prompts

  • “Use the securing-kubernetes-on-cloud skill to harden managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards…”
  • “/securing-kubernetes-on-cloud”

Requirements

  • Python 3
  • Docker

Workflow steps

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

  1. Enforce Pod Security Standards
  2. Configure Cloud-Native Workload Identity
  3. Implement Network Policies
  4. Configure RBAC with Least Privilege
  5. Deploy Image Admission Controls
  6. Enable Runtime Security Monitoring

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. 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/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • kubectl
    • az
    • gcloud
    • helm

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • falcosecurity.github.io
    • hooks.slack.com
    • raw.githubusercontent.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

Securing Kubernetes On Cloud loads about 3.3k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 645 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.8k

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 mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 645 words, ~3,262 tokens.

Download SKILL.mdSave it as .claude/skills/securing-kubernetes-on-cloud/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
securing-kubernetes-on-cloud
description
Hardens managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity (IRSA for EKS, Workload Identity for GKE, Managed Identities for AKS), RBAC scoping, image admission controls, and runtime security monitoring. Use when deploying a new managed Kubernetes cluster with security requirements or hardening an existing EKS, AKS, or GKE cluster after an audit or pentest finding.
domain
cybersecurity
subdomain
cloud-security
tags
kubernetes-security, eks, aks, gke, pod-security-standards, container-runtime
version
1.0.0
author
mahipal
license
Apache-2.0
nist_csf
PR.IR-01, ID.AM-08, GV.SC-06, DE.CM-01
mitre_attack
T1078.004, T1530, T1537, T1580, T1610

Securing Kubernetes on Cloud

When to Use

  • When deploying new managed Kubernetes clusters in production with security requirements
  • When hardening existing EKS, AKS, or GKE clusters after a security audit or pentest finding
  • When implementing workload identity to eliminate static cloud credentials in pods
  • When enforcing pod security policies across namespaces to prevent container escapes
  • When integrating runtime security monitoring for detecting container-level threats

Do not use for non-Kubernetes container deployments like ECS Fargate or Azure Container Instances, for application-level security within containers (see securing-serverless-functions), or for CI/CD pipeline security (see implementing-cloud-devsecops).

Prerequisites

  • Managed Kubernetes cluster provisioned on EKS, AKS, or GKE with admin access
  • kubectl configured with cluster admin credentials
  • Familiarity with Kubernetes RBAC, namespaces, and security contexts
  • Container network interface plugin supporting network policies (Calico, Cilium)

Workflow

Step 1: Enforce Pod Security Standards

Apply Pod Security Admission labels at the namespace level to enforce the Restricted profile in production namespaces. Pod Security Policies were removed in Kubernetes v1.25 and replaced with Pod Security Admission.

yaml
# Production namespace with restricted Pod Security Standard
apiVersion: v1
kind: Namespace
metadata:
  name: production
  labels:
    pod-security.kubernetes.io/enforce: restricted
    pod-security.kubernetes.io/enforce-version: latest
    pod-security.kubernetes.io/audit: restricted
    pod-security.kubernetes.io/warn: restricted
---
# Staging namespace with baseline enforcement
apiVersion: v1
kind: Namespace
metadata:
  name: staging
  labels:
    pod-security.kubernetes.io/enforce: baseline
    pod-security.kubernetes.io/audit: restricted
    pod-security.kubernetes.io/warn: restricted
yaml
# Pod spec compliant with restricted profile
apiVersion: v1
kind: Pod
metadata:
  name: secure-app
  namespace: production
spec:
  automountServiceAccountToken: false
  securityContext:
    runAsNonRoot: true
    runAsUser: 1000
    fsGroup: 1000
    seccompProfile:
      type: RuntimeDefault
  containers:
    - name: app
      image: company/app:v2.1@sha256:abc123...
      securityContext:
        allowPrivilegeEscalation: false
        readOnlyRootFilesystem: true
        capabilities:
          drop: ["ALL"]
      resources:
        limits:
          cpu: "500m"
          memory: "256Mi"
        requests:
          cpu: "100m"
          memory: "128Mi"
Step 2: Configure Cloud-Native Workload Identity

Eliminate static cloud credentials in pods by binding Kubernetes service accounts to cloud IAM roles.

bash
# EKS: IAM Roles for Service Accounts (IRSA)
eksctl create iamserviceaccount \
  --cluster production-cluster \
  --namespace production \
  --name web-app-sa \
  --attach-policy-arn arn:aws:iam::123456789012:policy/WebAppS3ReadOnly \
  --approve

# GKE: Workload Identity
gcloud iam service-accounts create web-app-sa \
  --project=my-gcp-project

gcloud iam service-accounts add-iam-policy-binding \
  web-app-sa@my-gcp-project.iam.gserviceaccount.com \
  --role roles/storage.objectViewer \
  --member "serviceAccount:my-gcp-project.svc.id.goog[production/web-app-sa]"

kubectl annotate serviceaccount web-app-sa \
  --namespace production \
  iam.gke.io/gcp-service-account=web-app-sa@my-gcp-project.iam.gserviceaccount.com

# AKS: Azure AD Workload Identity
az identity create --name web-app-identity --resource-group production-rg
az identity federated-credential create \
  --name web-app-federation \
  --identity-name web-app-identity \
  --resource-group production-rg \
  --issuer "$(az aks show -n production-cluster -g production-rg --query oidcIssuerProfile.issuerUrl -o tsv)" \
  --subject system:serviceaccount:production:web-app-sa
Step 3: Implement Network Policies

Deploy network policies to restrict pod-to-pod communication following the principle of least privilege. By default, Kubernetes allows all pods to communicate with each other.

yaml
# Default deny all ingress and egress in production namespace
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: default-deny-all
  namespace: production
spec:
  podSelector: {}
  policyTypes:
    - Ingress
    - Egress
---
# Allow web-app to receive traffic from ingress controller only
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: allow-ingress-to-web
  namespace: production
spec:
  podSelector:
    matchLabels:
      app: web-app
  policyTypes:
    - Ingress
  ingress:
    - from:
        - namespaceSelector:
            matchLabels:
              name: ingress-nginx
      ports:
        - protocol: TCP
          port: 8080
---
# Allow web-app to connect to database only
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: allow-web-to-db
  namespace: production
spec:
  podSelector:
    matchLabels:
      app: web-app
  policyTypes:
    - Egress
  egress:
    - to:
        - podSelector:
            matchLabels:
              app: postgres
      ports:
        - protocol: TCP
          port: 5432
    - to:
        - namespaceSelector: {}
          podSelector:
            matchLabels:
              k8s-app: kube-dns
      ports:
        - protocol: UDP
          port: 53
Step 4: Configure RBAC with Least Privilege

Scope Kubernetes RBAC roles to specific namespaces and resources. Avoid ClusterRoleBindings for non-administrative users.

yaml
# Developer role scoped to specific namespace
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  name: developer-role
  namespace: staging
rules:
  - apiGroups: [""]
    resources: ["pods", "pods/log", "services", "configmaps"]
    verbs: ["get", "list", "watch"]
  - apiGroups: ["apps"]
    resources: ["deployments"]
    verbs: ["get", "list", "watch", "update", "patch"]
  # Explicitly deny secrets access
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: developer-binding
  namespace: staging
subjects:
  - kind: Group
    name: developers
    apiGroup: rbac.authorization.k8s.io
roleRef:
  kind: Role
  name: developer-role
  apiGroup: rbac.authorization.k8s.io
Step 5: Deploy Image Admission Controls

Use admission controllers to enforce that only signed images from trusted registries are deployed. Implement OPA/Gatekeeper or Kyverno for policy enforcement.

yaml
# Kyverno policy: require images from approved registries
apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: restrict-image-registries
spec:
  validationFailureAction: Enforce
  rules:
    - name: validate-registries
      match:
        any:
          - resources:
              kinds: ["Pod"]
      validate:
        message: "Images must come from approved registries"
        pattern:
          spec:
            containers:
              - image: "123456789012.dkr.ecr.us-east-1.amazonaws.com/* | gcr.io/my-gcp-project/*"
---
# Kyverno policy: require image digest (no mutable tags)
apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: require-image-digest
spec:
  validationFailureAction: Enforce
  rules:
    - name: require-digest
      match:
        any:
          - resources:
              kinds: ["Pod"]
      validate:
        message: "Images must use digest references, not tags"
        pattern:
          spec:
            containers:
              - image: "*@sha256:*"
Step 6: Enable Runtime Security Monitoring

Deploy runtime security tools to detect anomalous behavior inside containers including process execution, file system modifications, and network connections.

bash
# Deploy Falco for runtime threat detection
helm repo add falcosecurity https://falcosecurity.github.io/charts
helm install falco falcosecurity/falco \
  --namespace falco-system --create-namespace \
  --set falcosidekick.enabled=true \
  --set falcosidekick.config.slack.webhookurl="https://hooks.slack.com/services/xxx"

# Run kube-bench for CIS Kubernetes Benchmark assessment
kubectl apply -f https://raw.githubusercontent.com/aquasecurity/kube-bench/main/job-eks.yaml
kubectl logs -l app=kube-bench

Key Concepts

TermDefinition
Pod Security StandardsThree profiles (Privileged, Baseline, Restricted) enforced via Pod Security Admission that control pod security context capabilities
Workload IdentityCloud-native mechanism binding Kubernetes service accounts to cloud IAM roles for credential-free cloud API access (IRSA, GKE WI, AKS MI)
Network PolicyKubernetes resource defining allowed ingress and egress traffic flows between pods, enforced by the CNI plugin
Admission ControllerKubernetes plugin that intercepts API requests before persistence to validate or mutate resources against security policies
RBACRole-Based Access Control in Kubernetes, defining what actions (verbs) identities can perform on which resources in which namespaces
Seccomp ProfileLinux kernel feature restricting the system calls a container process can make, reducing the kernel attack surface
Service MeshInfrastructure layer (Istio, Linkerd) providing mutual TLS, traffic policies, and observability for service-to-service communication
Show full SKILL.md (221 more words)Show less

Tools & Systems

  • Falco: Open-source runtime security engine detecting anomalous behavior in containers using kernel-level system call monitoring
  • Kyverno: Kubernetes-native policy engine for admission control, mutation, and generation of resources based on security policies
  • kube-bench: CIS Kubernetes Benchmark assessment tool checking cluster configuration against security best practices
  • Trivy: Vulnerability scanner for container images, file systems, and Kubernetes resources with SBOM generation
  • Calico/Cilium: CNI plugins providing network policy enforcement and advanced network security features including eBPF-based monitoring

Common Scenarios

Scenario: Cryptominer Deployed via Compromised Container Image

Context: GuardDuty Extended Threat Detection generates an AttackSequence:EKS/CompromisedCluster finding. A developer pulled a public Docker image containing an embedded XMRig cryptominer that executes at container startup.

Approach:

  1. Isolate the affected pod by applying a deny-all network policy targeting its labels
  2. Capture the container image digest and scan it with Trivy to identify the embedded binary
  3. Review Kubernetes audit logs to identify who deployed the compromised image and when
  4. Deploy Kyverno ClusterPolicy requiring images from approved private registries only
  5. Enable image digest pinning to prevent tag mutation attacks
  6. Deploy Falco with rules detecting crypto mining process signatures (/usr/bin/xmrig, stratum+tcp connections)

Pitfalls: Deleting the pod before capturing the image digest and audit logs destroys forensic evidence. Blocking only the specific image tag allows the attacker to re-push with a different tag.

Output Format

Kubernetes Security Assessment Report
=======================================
Cluster: production-cluster (EKS 1.29)
Provider: AWS (us-east-1)
Assessment Date: 2025-02-23
Tool: kube-bench v0.8.0 + manual review

CIS KUBERNETES BENCHMARK RESULTS:
  Total Controls: 124
  Passed: 98 (79%)
  Failed: 18 (15%)
  Warnings: 8 (6%)

CRITICAL FINDINGS:
  [K8S-001] 3 namespaces lack Pod Security Standards enforcement
    Namespaces: monitoring, logging, default
    Remediation: Apply restricted PSA labels

  [K8S-002] Default service account tokens auto-mounted in 12 deployments
    Risk: Credential theft if container is compromised
    Remediation: Set automountServiceAccountToken: false

  [K8S-003] No network policies in production namespace
    Risk: Unrestricted lateral movement between all pods
    Remediation: Deploy default-deny policy with explicit allow rules

HIGH FINDINGS:
  [K8S-004] 5 pods running as root with privileged security context
  [K8S-005] Images deployed using mutable tags (:latest) in 8 deployments
  [K8S-006] RBAC ClusterRoleBinding grants cluster-admin to developers group

© mukul975, 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, references) in skills/securing-kubernetes-on-cloud of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

Compare with similar skills

Securing Kubernetes On Cloud 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.

Securing Kubernetes On Cloud compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Securing Kubernetes On Cloud this skillmukul975/Anthropic-Cybersecurity-Skills34k—~3.3kAutomated safety check: PassApache-2.0
Defending Kubernetestrilwu/secskills157—~2.2kAutomated safety check: PassMIT
Mirrord Operatoraiskillstore/marketplace433—~4.6kAutomated safety check: PassNone
Gke Workload Identitygoogle/skills21k—~4.4kAutomated safety check: PassApache-2.0
Operate Kubernetes Toolchaincyberful/cyberful135—~898Automated safety check: PassAGPL-3.0
KubeShark for KubernetesLukasNiessen/kubernetes-skill446—~1.2kAutomated safety check: PassMIT

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Questions about Securing Kubernetes On Cloud

What does Securing Kubernetes On Cloud do?

Hardens managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity (IRSA for EKS, Workload Identity for GKE, Managed Identities for…. Securing Kubernetes On Cloud is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Hardens managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity (IRSA for EKS, Workload Identity for GKE, Managed Identities for AKS), RBAC scoping, image admission controls, and runtime security monitoring.

When should I use Securing Kubernetes On Cloud?

Securing Kubernetes On Cloud fits situations like: deploying a new managed Kubernetes cluster with security requirements; hardening an existing EKS; GKE cluster after an audit; pentest finding.

How do I install Securing Kubernetes On Cloud in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill securing-kubernetes-on-cloud -a claude-code`. Or copy the skill folder (skills/securing-kubernetes-on-cloud in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/securing-kubernetes-on-cloud in your project. Claude Code loads it when a task matches its description.

How do I install Securing Kubernetes On Cloud in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill securing-kubernetes-on-cloud -a codex`. Or copy the skill folder (skills/securing-kubernetes-on-cloud in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/securing-kubernetes-on-cloud in your project. Codex loads it when a task matches its description.

Can I use Securing Kubernetes On Cloud 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 mukul975/Anthropic-Cybersecurity-Skills --skill securing-kubernetes-on-cloud -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/securing-kubernetes-on-cloud, .gemini/skills/securing-kubernetes-on-cloud, .github/skills/securing-kubernetes-on-cloud and .opencode/skills/securing-kubernetes-on-cloud in your project.

What does Securing Kubernetes On Cloud need to run?

Going by SKILL.md and its folder, Securing Kubernetes On Cloud needs Python for the scripts in its folder and the command-line tools its instructions call (kubectl, az, gcloud and helm). Our summary lists: Python 3; Docker.

Does Securing Kubernetes On Cloud access the network?

SKILL.md names 3 domains. In commands or code: falcosecurity.github.io, hooks.slack.com and raw.githubusercontent.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Securing Kubernetes On Cloud 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 Securing Kubernetes On Cloud use?

Securing Kubernetes On Cloud is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Securing Kubernetes On Cloud use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 569 tokens, read only when the agent opens those files.

What are the alternatives to Securing Kubernetes On Cloud?

Skills that share tags, products or a category with Securing Kubernetes On Cloud: Defending Kubernetes (trilwu/secskills, 157 stars), Mirrord Operator (aiskillstore/marketplace, 433 stars), Gke Workload Identity (google/skills, 21k stars) and Operate Kubernetes Toolchain (cyberful/cyberful, 135 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Securing Kubernetes On Cloud?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.