implementing-kubernetes-pod-security-standards
Pod Security Standards (PSS) define three levels of security policies -- Privileged, Baseline, and Restricted -- enforced by the Pod Security Admission (PSA) controller built into Kubernetes 1.25+. PS
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How to use implementing-kubernetes-pod-security-standards on Cursor
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Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
implementing-kubernetes-pod-security-standards
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches implementing-kubernetes-pod-security-standards from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
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Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate implementing-kubernetes-pod-security-standards. Access via /implementing-kubernetes-pod-security-standards in your agent's command palette.
Security 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 environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
| name | implementing-kubernetes-pod-security-standards |
| description | Pod Security Standards (PSS) define three levels of security policies -- Privileged, Baseline, and Restricted -- enforced by the Pod Security Admission (PSA) controller built into Kubernetes 1.25+. PS |
| domain | cybersecurity |
| subdomain | container-security |
| tags | - containers - kubernetes - security - pod-security - PSA |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - PR.PS-01 - PR.IR-01 - ID.AM-08 - DE.CM-01 |
Implementing Kubernetes Pod Security Standards
Overview
Pod Security Standards (PSS) define three levels of security policies -- Privileged, Baseline, and Restricted -- enforced by the Pod Security Admission (PSA) controller built into Kubernetes 1.25+. PSA replaces the deprecated PodSecurityPolicy and provides namespace-level enforcement with three modes: enforce, audit, and warn.
When to Use
- When deploying or configuring implementing kubernetes pod security standards capabilities in your environment
- When establishing security controls aligned to compliance requirements
- When building or improving security architecture for this domain
- When conducting security assessments that require this implementation
Prerequisites
- Kubernetes cluster 1.25+ (PSA GA)
- kubectl configured with cluster-admin access
- Understanding of Linux capabilities and security contexts
Core Concepts
Three Security Profiles
| Profile | Purpose | Restrictions |
|---|---|---|
| Privileged | Unrestricted, system workloads | None |
| Baseline | Prevents known escalations | No hostNetwork, hostPID, hostIPC, privileged containers, dangerous capabilities |
| Restricted | Hardened best practices | Non-root, drop ALL caps, seccomp required, read-only rootfs recommended |
Three Enforcement Modes
| Mode | Behavior |
|---|---|
| enforce | Rejects pods that violate the policy |
| audit | Logs violations in audit log but allows pod |
| warn | Returns warning to user but allows pod |
Workflow
Step 1: Label Namespaces for PSA
# Restricted namespace - production workloads
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/audit-version: latest
pod-security.kubernetes.io/warn: restricted
pod-security.kubernetes.io/warn-version: latest
# Baseline namespace - general workloads
apiVersion: v1
kind: Namespace
metadata:
name: staging
labels:
pod-security.kubernetes.io/enforce: baseline
pod-security.kubernetes.io/enforce-version: latest
pod-security.kubernetes.io/audit: restricted
pod-security.kubernetes.io/audit-version: latest
pod-security.kubernetes.io/warn: restricted
pod-security.kubernetes.io/warn-version: latest
# Privileged namespace - system components only
apiVersion: v1
kind: Namespace
metadata:
name: kube-system
labels:
pod-security.kubernetes.io/enforce: privileged
pod-security.kubernetes.io/enforce-version: latest
Step 2: Apply Labels to Existing Namespaces
# Apply restricted enforcement to production
kubectl label namespace production \
pod-security.kubernetes.io/enforce=restricted \
pod-security.kubernetes.io/audit=restricted \
pod-security.kubernetes.io/warn=restricted \
--overwrite
# Apply baseline to staging with restricted warnings
kubectl label namespace staging \
pod-security.kubernetes.io/enforce=baseline \
pod-security.kubernetes.io/audit=restricted \
pod-security.kubernetes.io/warn=restricted \
--overwrite
# Check labels on all namespaces
kubectl get namespaces -L pod-security.kubernetes.io/enforce
Step 3: Create Compliant Pod Specs
# Restricted-compliant deployment
apiVersion: apps/v1
kind: Deployment
metadata:
name: secure-app
namespace: production
spec:
replicas: 3
selector:
matchLabels:
app: secure-app
template:
metadata:
labels:
app: secure-app
spec:
automountServiceAccountToken: false
securityContext:
runAsNonRoot: true
runAsUser: 65534
runAsGroup: 65534
fsGroup: 65534
seccompProfile:
type: RuntimeDefault
containers:
- name: app
image: myregistry.com/myapp:v1.0.0@sha256:abc123
ports:
- containerPort: 8080
protocol: TCP
securityContext:
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
capabilities:
drop:
- ALL
runAsNonRoot: true
runAsUser: 65534
resources:
requests:
memory: "64Mi"
cpu: "100m"
limits:
memory: "256Mi"
cpu: "500m"
volumeMounts:
- name: tmp
mountPath: /tmp
- name: cache
mountPath: /var/cache
volumes:
- name: tmp
emptyDir:
sizeLimit: 100Mi
- name: cache
emptyDir:
sizeLimit: 50Mi
Step 4: Gradual Migration Strategy
# Phase 1: Audit mode - discover violations without blocking
kubectl label namespace my-namespace \
pod-security.kubernetes.io/audit=restricted \
pod-security.kubernetes.io/warn=restricted
# Check audit logs for violations
kubectl logs -n kube-system -l component=kube-apiserver | grep "pod-security"
# Phase 2: Enforce baseline, warn on restricted
kubectl label namespace my-namespace \
pod-security.kubernetes.io/enforce=baseline \
pod-security.kubernetes.io/warn=restricted \
--overwrite
# Phase 3: Full restricted enforcement
kubectl label namespace my-namespace \
pod-security.kubernetes.io/enforce=restricted \
--overwrite
Step 5: Dry-Run Enforcement Testing
# Test what would happen with restricted enforcement
kubectl label --dry-run=server --overwrite namespace my-namespace \
pod-security.kubernetes.io/enforce=restricted
# Example output:
# Warning: existing pods in namespace "my-namespace" violate the new
# PodSecurity enforce level "restricted:latest"
# Warning: nginx-xxx: allowPrivilegeEscalation != false,
# unrestricted capabilities, runAsNonRoot != true, seccompProfile
Baseline Profile Restrictions
| Control | Restricted | Requirement |
|---|---|---|
| HostProcess | Must not set | Pods cannot use Windows HostProcess |
| Host Namespaces | Must not set | No hostNetwork, hostPID, hostIPC |
| Privileged | Must not set | No privileged: true |
| Capabilities | Baseline list only | Only NET_BIND_SERVICE, drop ALL for restricted |
| HostPath Volumes | Must not use | No hostPath volume mounts |
| Host Ports | Must not use | No hostPort in container spec |
| AppArmor | Default/runtime | Cannot set to unconfined |
| SELinux | Limited types | Only container_t, container_init_t, container_kvm_t |
| /proc Mount Type | Default only | Must use Default proc mount |
| Seccomp | RuntimeDefault or Localhost | Must specify seccomp profile (restricted) |
| Sysctls | Safe set only | Limited to safe sysctls |
Validation Commands
# Verify namespace labels
kubectl get ns --show-labels | grep pod-security
# Test pod creation against policy
kubectl run test-pod --image=nginx --namespace=production --dry-run=server
# Check for violations in audit logs
kubectl get events --field-selector reason=FailedCreate -A
# Scan with Kubescape for PSS compliance
kubescape scan framework nsa --namespace production
References
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Review drafts, suggest improvements, catch errors
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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
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate 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
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Reviews
- MMateo Srinivasan★★★★★Dec 20, 2024
Registry listing for implementing-kubernetes-pod-security-standards matched our evaluation — installs cleanly and behaves as described in the markdown.
- DDev Thompson★★★★★Dec 20, 2024
implementing-kubernetes-pod-security-standards reduced setup friction for our internal harness; good balance of opinion and flexibility.
- JJames Harris★★★★★Dec 12, 2024
Solid pick for teams standardizing on skills: implementing-kubernetes-pod-security-standards is focused, and the summary matches what you get after install.
- AAlexander Huang★★★★★Dec 8, 2024
Useful defaults in implementing-kubernetes-pod-security-standards — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- IIsabella Malhotra★★★★★Dec 8, 2024
I recommend implementing-kubernetes-pod-security-standards for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- NNoor Menon★★★★★Nov 27, 2024
Solid pick for teams standardizing on skills: implementing-kubernetes-pod-security-standards is focused, and the summary matches what you get after install.
- EEmma Srinivasan★★★★★Nov 23, 2024
Registry listing for implementing-kubernetes-pod-security-standards matched our evaluation — installs cleanly and behaves as described in the markdown.
- IIsabella Sethi★★★★★Nov 19, 2024
Useful defaults in implementing-kubernetes-pod-security-standards — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- JJames Gupta★★★★★Nov 11, 2024
implementing-kubernetes-pod-security-standards has been reliable in day-to-day use. Documentation quality is above average for community skills.
- YYusuf Martinez★★★★★Nov 3, 2024
I recommend implementing-kubernetes-pod-security-standards for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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