implementing-pod-security-admission-controller▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Implement Kubernetes Pod Security Admission to enforce baseline and restricted security profiles at namespace level using built-in admission controller.
| name | implementing-pod-security-admission-controller |
| description | Implement Kubernetes Pod Security Admission to enforce baseline and restricted security profiles at namespace level using built-in admission controller. |
| domain | cybersecurity |
| subdomain | container-security |
| tags | - kubernetes - pod-security-admission - psa - pod-security-standards - admission-controller |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - PR.PS-01 - PR.IR-01 - ID.AM-08 - DE.CM-01 |
Implementing Pod Security Admission Controller
Overview
Pod Security Admission (PSA) is a built-in Kubernetes admission controller (stable since v1.25) that enforces Pod Security Standards at the namespace level. It replaces the deprecated PodSecurityPolicy (PSP) and provides three security profiles: Privileged, Baseline, and Restricted, with three enforcement modes: enforce, audit, and warn.
When to Use
- When deploying or configuring implementing pod security admission controller 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 v1.25+ (PSA is stable/GA)
- kubectl with cluster-admin access
- No dependency on external tools - PSA is built into kube-apiserver
Pod Security Standards
Privileged Profile
- Unrestricted - No restrictions applied
- Use case: System-level pods (kube-system, monitoring)
Baseline Profile
- Minimally restrictive - Prevents known privilege escalation
- Blocks: privileged containers, hostPID, hostIPC, hostNetwork, hostPorts, certain volume types, adding capabilities beyond runtime defaults
Restricted Profile
- Heavily restricted - Follows security best practices
- Requires: non-root, drop ALL capabilities, seccomp RuntimeDefault, read-only root filesystem considerations
- Blocks: Everything in Baseline plus running as root, privilege escalation, non-approved volume types
Enforcement Modes
| Mode | Behavior | Use Case |
|---|---|---|
| enforce | Reject pods violating policy | Production enforcement |
| audit | Log violations to audit log | Pre-enforcement assessment |
| warn | Show warnings to user | Developer feedback |
Implementation
Apply to Namespace via Labels
# Restricted enforcement with audit and warn
apiVersion: v1
kind: Namespace
metadata:
name: production
labels:
pod-security.kubernetes.io/enforce: restricted
pod-security.kubernetes.io/enforce-version: v1.28
pod-security.kubernetes.io/audit: restricted
pod-security.kubernetes.io/audit-version: v1.28
pod-security.kubernetes.io/warn: restricted
pod-security.kubernetes.io/warn-version: v1.28
# Baseline enforcement for staging
apiVersion: v1
kind: Namespace
metadata:
name: staging
labels:
pod-security.kubernetes.io/enforce: baseline
pod-security.kubernetes.io/enforce-version: v1.28
pod-security.kubernetes.io/audit: restricted
pod-security.kubernetes.io/audit-version: v1.28
pod-security.kubernetes.io/warn: restricted
pod-security.kubernetes.io/warn-version: v1.28
# Privileged for system namespaces
apiVersion: v1
kind: Namespace
metadata:
name: kube-system
labels:
pod-security.kubernetes.io/enforce: privileged
Apply Labels with kubectl
# Set restricted enforcement
kubectl label namespace production \
pod-security.kubernetes.io/enforce=restricted \
pod-security.kubernetes.io/enforce-version=v1.28 \
pod-security.kubernetes.io/audit=restricted \
pod-security.kubernetes.io/warn=restricted
# Set baseline enforcement
kubectl label namespace staging \
pod-security.kubernetes.io/enforce=baseline \
pod-security.kubernetes.io/audit=restricted \
pod-security.kubernetes.io/warn=restricted
# Check current labels
kubectl get namespace production -o jsonpath='{.metadata.labels}' | jq .
Dry-Run Testing
# Test what would happen with restricted policy on a namespace
kubectl label --dry-run=server --overwrite namespace staging \
pod-security.kubernetes.io/enforce=restricted
# Output shows existing pods that would violate the policy
# Warning: existing pods in namespace "staging" violate the new PodSecurity enforce level "restricted:latest"
Cluster-Wide Defaults (AdmissionConfiguration)
# /etc/kubernetes/psa-config.yaml
apiVersion: apiserver.config.k8s.io/v1
kind: AdmissionConfiguration
plugins:
- name: PodSecurity
configuration:
apiVersion: pod-security.admission.config.k8s.io/v1
kind: PodSecurityConfiguration
defaults:
enforce: baseline
enforce-version: latest
audit: restricted
audit-version: latest
warn: restricted
warn-version: latest
exemptions:
usernames: []
runtimeClasses: []
namespaces:
- kube-system
- kube-public
- kube-node-lease
- calico-system
- gatekeeper-system
- monitoring
- falco
Apply to API Server
# Add to kube-apiserver manifests
# /etc/kubernetes/manifests/kube-apiserver.yaml
spec:
containers:
- command:
- kube-apiserver
- --admission-control-config-file=/etc/kubernetes/psa-config.yaml
volumeMounts:
- name: psa-config
mountPath: /etc/kubernetes/psa-config.yaml
readOnly: true
volumes:
- name: psa-config
hostPath:
path: /etc/kubernetes/psa-config.yaml
type: File
Compliant Pod Examples
Restricted-Compliant Pod
apiVersion: v1
kind: Pod
metadata:
name: restricted-pod
namespace: production
spec:
securityContext:
runAsNonRoot: true
runAsUser: 1000
runAsGroup: 3000
fsGroup: 2000
seccompProfile:
type: RuntimeDefault
automountServiceAccountToken: false
containers:
- name: app
image: myregistry/myapp:v1.0.0
securityContext:
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
capabilities:
drop:
- ALL
resources:
limits:
cpu: 500m
memory: 256Mi
requests:
cpu: 100m
memory: 128Mi
volumeMounts:
- name: tmp
mountPath: /tmp
volumes:
- name: tmp
emptyDir: {}
Baseline-Compliant Pod
apiVersion: v1
kind: Pod
metadata:
name: baseline-pod
namespace: staging
spec:
containers:
- name: app
image: myregistry/myapp:v1.0.0
securityContext:
allowPrivilegeEscalation: false
resources:
limits:
cpu: 500m
memory: 256Mi
Migration from PodSecurityPolicy
Step 1: Audit Current State
# Check existing PSPs
kubectl get psp
# Check which service accounts use which PSP
kubectl get clusterrolebinding -o json | \
jq '.items[] | select(.roleRef.name | startswith("psp-")) | {name: .metadata.name, subjects: .subjects}'
Step 2: Map PSP to PSA Profiles
# For each namespace, determine required PSA level
for ns in $(kubectl get ns -o jsonpath='{.items[*].metadata.name}'); do
echo "Namespace: $ns"
kubectl label --dry-run=server namespace $ns \
pod-security.kubernetes.io/enforce=restricted 2>&1 | head -5
done
Step 3: Apply PSA Labels (Audit First)
# Start with audit mode
kubectl label namespace production \
pod-security.kubernetes.io/audit=restricted \
pod-security.kubernetes.io/warn=restricted
Step 4: Review and Fix Violations
# Check audit logs for violations
kubectl get events --field-selector reason=FailedCreate -A
Step 5: Enable Enforcement
kubectl label namespace production \
pod-security.kubernetes.io/enforce=restricted
Monitoring
# Check PSA violations in events
kubectl get events --all-namespaces --field-selector reason=FailedCreate
# Check audit logs
kubectl logs -n kube-system kube-apiserver-* | grep "pod-security.kubernetes.io"
# List namespace PSA labels
kubectl get namespaces -L pod-security.kubernetes.io/enforce
Best Practices
- Start with audit+warn before enforce to assess impact
- Use dry-run to test enforcement before applying
- Exempt system namespaces (kube-system, monitoring) in cluster defaults
- Pin version (enforce-version) for predictable behavior across upgrades
- Set cluster-wide baseline as default, then restrict specific namespaces
- Combine with Gatekeeper for additional custom policies beyond PSA
- Use restricted profile for all production workloads
- Document exemptions with clear justification
How to use implementing-pod-security-admission-controller 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 implementing-pod-security-admission-controller
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches implementing-pod-security-admission-controller 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 implementing-pod-security-admission-controller. Access the skill through slash commands (e.g., /implementing-pod-security-admission-controller) 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★★★★★61 reviews- ★★★★★Chaitanya Patil· Dec 20, 2024
Useful defaults in implementing-pod-security-admission-controller — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Tariq Park· Dec 20, 2024
implementing-pod-security-admission-controller is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Tariq Perez· Dec 16, 2024
Useful defaults in implementing-pod-security-admission-controller — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Fatima Choi· Dec 12, 2024
Registry listing for implementing-pod-security-admission-controller matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Evelyn Agarwal· Dec 8, 2024
Registry listing for implementing-pod-security-admission-controller matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Michael Kim· Dec 4, 2024
Solid pick for teams standardizing on skills: implementing-pod-security-admission-controller is focused, and the summary matches what you get after install.
- ★★★★★Diya Ramirez· Nov 23, 2024
I recommend implementing-pod-security-admission-controller for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Camila Mehta· Nov 15, 2024
implementing-pod-security-admission-controller reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Piyush G· Nov 11, 2024
implementing-pod-security-admission-controller has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Amina Chen· Nov 11, 2024
implementing-pod-security-admission-controller fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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