25 Kubernetes Security Interview Questions (With Expert Answers)

Kubernetes security is now a must-have skill for DevOps engineers, SREs, platform engineers, and security professionals. Whether you’re interviewing at a cloud-native startup or a Fortune 500 enterprise, these questions come up regularly — and the depth of your answers separates senior from junior candidates.

This guide covers 25 questions organized by security domain, with expert-level answers that demonstrate both theoretical knowledge and practical experience.

Pod Security (Questions 1-5)

Q1: What are Pod Security Standards (PSS) and how do they replace PodSecurityPolicies?

Answer: Pod Security Standards define three security levels — Privileged (unrestricted), Baseline (prevents known privilege escalations), and Restricted (hardened best practices). They replaced the deprecated PodSecurityPolicy (PSP) admission controller starting in Kubernetes 1.25.

PSS is enforced via the built-in Pod Security Admission (PSA) controller using namespace labels:

apiVersion: v1
kind: Namespace
metadata:
  name: production
  labels:
    pod-security.kubernetes.io/enforce: restricted
    pod-security.kubernetes.io/warn: restricted

The key difference from PSPs: PSS is a namespace-level control (not a cluster-level policy bound to service accounts), making it simpler to configure and reason about. The enforcement modes are:

• enforce — rejects non-compliant pods
• warn — allows but prints warnings
• audit — allows but logs to the audit log

Best practice: Use restricted in production, baseline in staging, and warn everywhere to catch violations before they hit production.

Q2: Explain the security implications of running containers as root. How do you prevent it?

Answer: Running as root (UID 0) inside a container is dangerous because:

1. If the container escapes (e.g., via a kernel vulnerability like CVE-2022-0185), the attacker lands on the host as root
2. Root can write to sensitive paths even with read-only filesystem off
3. Setuid binaries (sudo, su, pkexec) work, enabling privilege escalation

Prevention requires a defense-in-depth approach:

spec:
  securityContext:
    runAsNonRoot: true          # Pod-level: prevents any container from starting as root
    runAsUser: 10001            # Explicit non-root UID
    runAsGroup: 10001
  containers:
    - securityContext:
        allowPrivilegeEscalation: false  # Blocks setuid/capabilities escalation
        capabilities:
          drop: ["ALL"]                   # Remove all Linux capabilities

At the namespace level, enforce restricted PSS. At the cluster level, use a policy engine (Kyverno or OPA/Gatekeeper) to reject pods without runAsNonRoot: true.

Q3: What is a seccomp profile and why should every production workload use one?

Answer: Seccomp (Secure Computing Mode) restricts which Linux syscalls a container can make. This is critical because most container escape exploits (like the runc CVE-2019-5736 and the cgroup escape CVE-2022-0492) rely on specific syscalls that normal applications never need — unshare, mount, ptrace, keyctl, bpf.

Kubernetes 1.27+ enables the RuntimeDefault seccomp profile by default, which blocks approximately 44 dangerous syscalls. For sensitive workloads, you can create custom profiles that allow only the specific syscalls your application needs:

securityContext:
  seccompProfile:
    type: RuntimeDefault  # Baseline protection

For custom profiles, use the Security Profiles Operator (SPO) to manage profile distribution across nodes, or place the JSON profile at /var/lib/kubelet/seccomp/profiles/ on each node.

Interview bonus: Mention that you can record syscalls with strace or SPO’s recording mode to build a minimal profile for your application.

Q4: What does readOnlyRootFilesystem: true do and why is it important?

Answer: It makes the container’s root filesystem immutable. After the container starts, no files can be written to the image filesystem. This prevents:

• Attackers from downloading and executing malware
• Modifying system binaries (trojanized /bin/sh)
• Writing persistence mechanisms (cron jobs, shell profiles)
• Tampering with application code at runtime

Applications that need writable directories use emptyDir volume mounts for specific paths:

containers:
  - securityContext:
      readOnlyRootFilesystem: true
    volumeMounts:
      - name: tmp
        mountPath: /tmp
      - name: cache
        mountPath: /var/cache
volumes:
  - name: tmp
    emptyDir:
      sizeLimit: "64Mi"
  - name: cache
    emptyDir: {}

This is part of the Restricted PSS standard and should be enforced on all production workloads.

Q5: How do you drop all Linux capabilities from a container? What is the one capability you might need to add back?

Answer: Drop all capabilities with:

securityContext:
  capabilities:
    drop: ["ALL"]

Linux capabilities are a fine-grained breakdown of root privileges (35+ capabilities). The most commonly re-added one is NET_BIND_SERVICE — which allows binding to ports below 1024 (e.g., port 80/443 for web servers):

capabilities:
  drop: ["ALL"]
  add: ["NET_BIND_SERVICE"]

However, the best practice is to configure your application to listen on a high port (8080, 8443) and use a Service or Ingress to expose it on 80/443, eliminating the need for any capabilities at all.

Never add: SYS_ADMIN (nearly equivalent to full root), NET_RAW (packet sniffing), SYS_PTRACE (process inspection/injection), or DAC_OVERRIDE (bypass file permissions).

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Network Security (Questions 6-10)

Q6: What happens if you don’t have any NetworkPolicies in a namespace?

Answer: All traffic is allowed. By default, Kubernetes has a completely flat network — every pod can communicate with every other pod in every namespace, on any port. This means a compromised pod in the dev namespace can freely attack production databases.

The critical first step is deploying a default deny policy:

apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: default-deny-all
  namespace: production
spec:
  podSelector: {}    # Selects ALL pods
  policyTypes:
    - Ingress
    - Egress
  # No ingress/egress rules = deny everything

After this, you explicitly allow only the traffic your application needs. NetworkPolicies are additive — the deny policy plus specific allow policies creates a whitelist model.

Important caveat: NetworkPolicies require a CNI that supports them (Calico, Cilium, Antrea). The default kubenet does NOT enforce policies — they’re silently ignored.

Q7: How do you prevent pods from accessing the cloud metadata endpoint (169.254.169.254)?

Answer: This is one of the most commonly exploited attack paths in cloud environments. The IMDS (Instance Metadata Service) at 169.254.169.254 returns IAM credentials, instance identity, and configuration data. An SSRF vulnerability in any pod can steal cloud credentials.

Block it with a NetworkPolicy that excludes the link-local range from egress:

apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: deny-cloud-metadata
spec:
  podSelector: {}
  policyTypes:
    - Egress
  egress:
    - to:
        - ipBlock:
            cidr: 0.0.0.0/0
            except:
              - 169.254.0.0/16

Additionally:

• On AWS EKS, enforce IMDSv2 (requires hop limit = 1 at the instance level, which prevents pods from reaching IMDS)
• On GKE, use Workload Identity instead of node-level service accounts
• Consider also blocking the AWS IPv6 metadata endpoint (fd00:ec2::254)

Q8: Explain the difference between ingress and egress network policies. Why is egress just as important?

Answer: Ingress controls what traffic can reach a pod (incoming). Egress controls what traffic a pod can send (outgoing).

Egress is equally important because a compromised pod can:

• Connect to a Command & Control (C2) server for remote access
• Exfiltrate data to external endpoints
• Download additional malware or cryptominers
• Reach cloud metadata to steal IAM credentials
• Scan internal networks for lateral movement

A defense-in-depth network policy strategy includes both:

1. Default deny ingress AND egress
2. Allow DNS egress to kube-dns (port 53 UDP/TCP)
3. Allow specific ingress from frontend to backend
4. Allow specific egress from backend to database
5. Block all egress from database tier (except DNS)

Without egress controls, your ingress policies provide only half the protection.

Q9: What is namespace isolation and how do you implement it?

Answer: Namespace isolation prevents pods in one namespace from communicating with pods in another. This contains the blast radius of a compromise to a single namespace — a critical security boundary for multi-tenant clusters or environment separation (dev/staging/prod).

Implementation requires multiple NetworkPolicies:

1. Default deny all ingress in the namespace
2. Allow intra-namespace traffic (pods within the same namespace can talk)
3. Allow from ingress controller (so external traffic can reach the app)
4. Allow from monitoring (so Prometheus can scrape metrics)
5. Default deny egress + allow DNS

The intra-namespace allow uses the automatic namespace label:

ingress:
  - from:
      - namespaceSelector:
          matchLabels:
            kubernetes.io/metadata.name: production

This label is automatically set on all namespaces in Kubernetes 1.22+.

Q10: How does a service mesh (like Istio) enhance Kubernetes network security beyond NetworkPolicies?

Answer: A service mesh adds several layers that NetworkPolicies cannot provide:

1. mTLS (mutual TLS) — Encrypts all pod-to-pod traffic and verifies identity. NetworkPolicies filter traffic but don’t encrypt it. Without mTLS, any pod on the same node can sniff network traffic.

2. L7 policy — NetworkPolicies operate at L3/L4 (IP and port). A service mesh can enforce L7 rules like “allow GET /health but deny POST /admin”.

3. Identity-based auth — Traffic is authorized based on service identity (SPIFFE), not just IP labels that can be spoofed.

4. Observability — Full request-level metrics, distributed tracing, and traffic flow visualization.

The trade-off is complexity. NetworkPolicies are native and free. A service mesh adds operational overhead (control plane, sidecar injection, certificate management). Start with NetworkPolicies as the baseline, add a service mesh when you need encryption, L7 policy, or observability.

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RBAC & Access Control (Questions 11-15)

Q11: What is the principle of least privilege in RBAC, and what is the most dangerous RBAC misconfiguration?

Answer: Least privilege means granting only the exact permissions a workload needs to function. In practice: no wildcards (*), namespace-scoped roles instead of cluster-wide, one service account per application.

The most dangerous misconfiguration is a ClusterRoleBinding to cluster-admin on a service account:

# NEVER do this
subjects:
  - kind: ServiceAccount
    name: my-app
    namespace: default
roleRef:
  kind: ClusterRole
  name: cluster-admin

This gives my-app full control over every resource in every namespace. If the pod is compromised, the attacker owns the entire cluster. Audit with:

kubectl get clusterrolebindings -o json | \
  jq '.items[] | select(.roleRef.name=="cluster-admin") | .subjects[]'

Also dangerous: roles with escalate, bind, or impersonate verbs, which allow creating new privileged roles.

Q12: Explain the difference between Role/RoleBinding and ClusterRole/ClusterRoleBinding.

Answer:

	Scope	Use case
Role + RoleBinding	Single namespace	Application workloads — “app can read configmaps in production namespace”
ClusterRole + ClusterRoleBinding	Cluster-wide	Admin tasks, node management, cross-namespace read access
ClusterRole + RoleBinding	Single namespace (reusable template)	Common pattern: define once as ClusterRole, bind per-namespace

Security guidance: Default to namespace-scoped Role + RoleBinding. Only use ClusterRole + ClusterRoleBinding when the operation genuinely requires cluster-wide scope (e.g., viewing nodes, managing CRDs). The combination of ClusterRole + RoleBinding is a useful pattern for reusable role templates that are still restricted to individual namespaces.

Q13: Why should you disable automountServiceAccountToken, and when do you need to leave it enabled?

Answer: By default, every pod gets a service account token mounted at /var/run/secrets/kubernetes.io/serviceaccount/token. This token can authenticate to the Kubernetes API server. If an attacker compromises the pod, they immediately have API access.

Most application pods never need API access. Disable it at the ServiceAccount level:

apiVersion: v1
kind: ServiceAccount
metadata:
  name: my-app-sa
automountServiceAccountToken: false

Leave it enabled only for:

• Custom controllers/operators that watch Kubernetes resources
• Sidecar containers that interact with the API (e.g., Vault agent, cert-manager)
• CI/CD runners that deploy to the cluster

When you DO need API access, use projected tokens (time-limited, audience-bound) instead of the default long-lived token:

volumes:
  - name: api-token
    projected:
      sources:
        - serviceAccountToken:
            expirationSeconds: 3600
            audience: "https://kubernetes.default.svc"

Q14: How do you audit who has cluster-admin access in a Kubernetes cluster?

Answer: Query all ClusterRoleBindings that reference the cluster-admin ClusterRole:

# Find all cluster-admin bindings
kubectl get clusterrolebindings -o json | \
  jq -r '.items[] | select(.roleRef.name=="cluster-admin") |
  "\(.metadata.name): \(.subjects[])"'

# Check for wildcard roles (nearly as dangerous)
kubectl get clusterroles -o json | \
  jq '.items[] | select(.rules[]?.verbs[] == "*") |
  .metadata.name'

A comprehensive RBAC audit also checks:

• Roles with escalate, bind, or impersonate verbs
• Service accounts with ClusterRoleBindings (should be rare)
• RoleBindings in kube-system that grant write access
• Groups with broad permissions (system:masters)

The Kubernetes audit log (configured via audit policy) records every API call, so you can also analyze actual usage patterns to identify over-privileged accounts.

Q15: What is workload identity and how does it eliminate static cloud credentials?

Answer: Workload identity maps a Kubernetes ServiceAccount to a cloud IAM role, eliminating the need for static access keys stored as Secrets.

On AWS EKS (IRSA):

apiVersion: v1
kind: ServiceAccount
metadata:
  name: my-app
  annotations:
    eks.amazonaws.com/role-arn: "arn:aws:iam::123456789012:role/my-app-role"

On GCP GKE:

annotations:
  iam.gke.io/gcp-service-account: "my-app@project.iam.gserviceaccount.com"

The flow: the pod gets a short-lived OIDC token projected into it, which is exchanged for temporary cloud credentials via STS. No static keys exist anywhere in the cluster.

This eliminates the risk of credential leakage through Git repos, ConfigMaps, environment variables, or compromised pods. It also provides automatic rotation and CloudTrail/audit logging of every credential use.

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Secrets & Supply Chain (Questions 16-20)

Q16: Why are Kubernetes Secrets not actually secret? What should you use instead?

Answer: Kubernetes Secrets are base64-encoded, not encrypted. By default:

• They’re stored in etcd in plaintext (unless encryption at rest is configured)
• Anyone with read access to Secrets in a namespace can decode them
• They appear in pod environment variables (visible in /proc, crash dumps, and logs)
• They’re stored in Git if you version your manifests

Better alternatives:

1. External Secrets Operator (ESO) — Syncs secrets from AWS Secrets Manager, HashiCorp Vault, GCP Secret Manager, or Azure Key Vault into K8s Secrets at runtime
2. HashiCorp Vault with the CSI provider — Injects secrets directly into pods without K8s Secrets
3. Sealed Secrets — Encrypts secrets for safe Git storage; only the controller can decrypt
4. SOPS + Age/KMS — Encrypt secret files in Git; decrypt during CI/CD

Always enable etcd encryption at rest via the API server’s --encryption-provider-config flag, and mount secrets as files instead of environment variables.

Q17: Explain the image supply chain attack surface. How do you secure it?

Answer: The supply chain attack surface includes:

1. Base images — Vulnerabilities in the OS layer (Alpine, Debian, etc.)
2. Dependencies — Compromised libraries (e.g., the event-stream npm incident)
3. Build environment — Compromised CI/CD pipelines injecting malicious code
4. Registry — Pulling from untrusted or compromised registries
5. Deployment — Running unverified or tampered images in production

Defense layers:

• Image scanning — Trivy, Snyk, or Grype in CI/CD to catch CVEs before deployment
• Image signing — Cosign (Sigstore) to verify images haven’t been tampered with
• Admission policies — Kyverno or Gatekeeper to reject unsigned images or images with critical CVEs
• Private registry — Only pull from your own registry, never directly from Docker Hub in production
• Disallow :latest tag — Use immutable tags or digest pinning (image@sha256:...)
• Minimal base images — Use distroless or scratch images to reduce the vulnerability surface

Q18: What is the :latest tag problem and how do policy engines prevent it?

Answer: The :latest tag is mutable — it can point to different images over time. This means:

• Deploying the same manifest twice can produce different pods
• Rollbacks don’t work (the same tag now points to the broken image)
• There’s no audit trail of what’s actually running
• An attacker who pushes a malicious image to the same tag gets instant deployment

Policy engines enforce immutable tagging:

# Kyverno policy
apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: disallow-latest-tag
spec:
  validationFailureAction: enforce
  rules:
    - name: validate-image-tag
      match:
        any:
          - resources:
              kinds: ["Pod"]
      validate:
        message: "The ':latest' tag is not allowed."
        pattern:
          spec:
            containers:
              - image: "!*:latest"

Even better: enforce digest pinning (image@sha256:abc123...) which is truly immutable and verifiable.

Q19: How does External Secrets Operator (ESO) work and why should you use it?

Answer: ESO runs as a controller that synchronizes secrets from external providers into native Kubernetes Secrets. The architecture has three components:

1. SecretStore — Defines the connection to an external provider (AWS Secrets Manager, Vault, etc.)
2. ExternalSecret — Declares what secret to fetch and how to map it into a K8s Secret
3. Controller — Periodically fetches values and creates/updates K8s Secrets

Benefits:

• No secrets in Git — Source of truth is the external provider
• Automatic rotation — ESO re-fetches on a configurable interval
• Audit trail — Every access is logged in the cloud provider (CloudTrail, etc.)
• Encryption at rest — Cloud providers encrypt secrets with KMS
• Fine-grained access — IAM policies control which workloads can read which secrets

The ESO approach means your Kubernetes manifests contain only references (secret names/paths), never actual secret values.

Q20: What is etcd encryption at rest and why is it essential?

Answer: etcd is the key-value store that backs the Kubernetes API server. All cluster state — including Secrets — is stored in etcd. Without encryption at rest, Secrets are stored as base64-encoded plaintext. Anyone with access to etcd data (backups, disk snapshots, node access) can read every Secret.

Enable it by configuring the API server with --encryption-provider-config:

apiVersion: apiserver.config.k8s.io/v1
kind: EncryptionConfiguration
resources:
  - resources:
      - secrets
    providers:
      - aescbc:
          keys:
            - name: key1
              secret: <base64-encoded-key>
      - identity: {}  # Fallback for reading unencrypted data

Managed Kubernetes services (EKS, GKE, AKS) typically provide this as a configurable option. Always verify it’s enabled:

# Check if secrets are encrypted (look for "k8s:enc:aescbc:v1" prefix)
kubectl -n kube-system exec etcd-master -- etcdctl get /registry/secrets/default/my-secret | hexdump -C

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Runtime & Monitoring (Questions 21-25)

Q21: What is Falco and how does it detect runtime threats in Kubernetes?

Answer: Falco is an open-source runtime security tool that monitors kernel syscalls in real-time using eBPF or a kernel module. It detects malicious behavior that happens after deployment — the threats that admission policies and network policies cannot prevent.

Key detection capabilities:

• Shell in container — Detects bash, sh, or zsh spawned inside running containers
• Crypto mining — Detects known miner processes and connections to mining pool ports
• Sensitive file access — Detects reads of /etc/shadow, SA tokens, or PKI certs
• Container escape — Detects nsenter, chroot, or unshare inside containers
• Privilege escalation — Detects sudo, su, or setuid binary execution
• Network reconnaissance — Detects nmap, netcat, or tcpdump in containers
• Package installation — Detects apt, yum, or pip in running containers

Falco rules map to MITRE ATT&CK techniques, making them directly consumable by SOC teams and SIEM integrations.

Q22: Explain the Kubernetes audit log. What should you always log at RequestResponse level?

Answer: The Kubernetes audit log records every API server request, including who made it, what they did, when, and the outcome. It’s configured via an audit policy file mounted on the API server.

Always log at RequestResponse level (full request + response body):

• secrets — Detect unauthorized reads and bulk enumeration (MITRE T1552)
• roles, clusterroles, rolebindings, clusterrolebindings — Detect privilege escalation (MITRE T1078)
• pods/exec, pods/attach, pods/portforward — Detect interactive access (MITRE T1609)
• serviceaccounts/token — Detect token creation for lateral movement
• tokenreviews, subjectaccessreviews — Detect brute force and auth probing

Log at Metadata level (who/what/when, not body):

• Workload changes (deployments, daemonsets, jobs)
• Network policies and services
• Namespaces and configmaps
• Admission webhooks

Skip (None level):

• Health checks (/healthz, /readyz, /livez)
• API discovery endpoints
• kubelet node status updates

Send audit logs to a SIEM (Splunk, ELK, Datadog) for alerting and correlation.

Q23: How do you detect and prevent cryptomining in Kubernetes clusters?

Answer: Cryptomining (cryptojacking) is the most common outcome of Kubernetes compromises. Detection and prevention happen at multiple layers:

Prevention:

• Resource limits on all containers (prevent CPU exhaustion)
• Network policies blocking egress to mining pool ports (3333, 4444, 5555, 7777, 8888, 9999, 14433)
• Admission policies rejecting images from untrusted registries
• Read-only root filesystem (prevents downloading miners)
• Seccomp profiles (blocks syscalls needed for mining)

Detection:

• Falco rules for known mining process names (xmrig, minerd, etc.)
• Falco rules for outbound connections to mining pool ports
• Resource monitoring alerts (unexpected sustained high CPU)
• Network monitoring for Stratum protocol traffic

Response:

• Kill the compromised pod immediately
• Investigate how it was compromised (SSRF? stolen credentials? vulnerable image?)
• Rotate all credentials in the affected namespace
• Review audit logs for the attack timeline

Q24: What metrics and alerts should you configure for Kubernetes security monitoring?

Answer: Essential security monitoring includes:

RBAC alerts:

• New ClusterRoleBinding created (especially to cluster-admin)
• Role or ClusterRole with wildcard permissions created
• ServiceAccount created in kube-system

Workload alerts:

• Pod running as root or privileged
• Pod with hostNetwork, hostPID, or hostIPC enabled
• Container with no resource limits
• Image pulled from external registry (not your private registry)
• Pod exec or attach event

Network alerts:

• Pod with no NetworkPolicy (unprotected)
• Egress to unexpected external IPs
• Connection to cloud metadata endpoint
• DNS queries to suspicious domains

Node alerts:

• Unauthorized process on node (not kubelet/containerd)
• Failed SSH attempts to nodes
• Node label changes (could redirect workloads)
• DaemonSet changes in kube-system

Prometheus + Alertmanager is the standard stack. Supplement with Falco for runtime detection and audit logs for API-level monitoring.

Q25: Walk through a Kubernetes security incident response plan.

Answer: A structured incident response plan for Kubernetes:

1. Detection — Alert fires (Falco, audit log, monitoring)

• Identify the affected pod, namespace, node, and service account
• Determine the alert type (compromise, lateral movement, exfiltration)

2. Containment (minutes)

• Apply a NetworkPolicy to block all egress from the affected namespace
• Delete the compromised pod: kubectl delete pod <name> -n <namespace>
• Scale down the deployment to 0 if needed
• Revoke the service account token: delete and recreate the SA
• If node-level compromise: cordon and drain the node

3. Investigation (hours)

• Pull audit logs for the affected namespace and time window
• Check Falco alerts for the sequence of events
• Examine container logs: kubectl logs <pod> -n <ns> --previous
• Review the image scan results for the compromised container
• Check RBAC bindings for the compromised service account
• Analyze network flow logs for data exfiltration indicators

4. Eradication

• Rotate all secrets in the affected namespace
• Rotate cloud credentials (IAM roles, service account keys)
• Rebuild and redeploy the affected application from a verified source
• Patch the vulnerability that allowed initial access

5. Recovery and Lessons Learned

• Verify the fix with penetration testing
• Update policies (network, admission, RBAC) to prevent recurrence
• Document the timeline and root cause
• Add new Falco rules or alerts for the specific attack pattern

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Prepare for Your Interview

The key to acing Kubernetes security interviews is demonstrating that you understand both the why (threat model, attack scenarios) and the how (specific configurations, kubectl commands, policy syntax). Interviewers are looking for candidates who:

1. Think in terms of defense-in-depth — no single control is sufficient
2. Can reference specific frameworks (CIS Benchmark, MITRE ATT&CK, NIST)
3. Know the practical implementation (YAML, kubectl, policy engines)
4. Understand trade-offs (security vs. developer experience vs. operational complexity)

Practice deploying the configurations mentioned in this guide in a test cluster. Hands-on experience with NetworkPolicies, RBAC, and admission policies will give you confidence that no amount of theoretical study can match.

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Related Templates

Implement what you’ve learned with these production-ready YAML templates:

• Template 01: Default Deny Network Policy — Zero-trust baseline that blocks all traffic by default.
• Template 02: Restricted PSS Namespace — Pod Security Standards at the Restricted level.
• Template 03: Hardened Pod Security Context — Non-root, read-only FS, all capabilities dropped.
• Template 04: Least Privilege RBAC — Namespace-scoped Role and RoleBinding.
• Template 05: Secure Service Account — Disabled auto-mount, projected tokens, workload identity.
• Template 12: Falco Runtime Security — 7 runtime detection rules with MITRE ATT&CK tags.
• Template 14: Namespace Isolation — Complete namespace isolation with monitoring exceptions.
• Template 18: External Secrets — AWS Secrets Manager integration via ESO.

Related Articles

• Kubernetes Network Policies: The Complete Guide to Zero Trust Networking — Deep dive into NetworkPolicy implementation and testing.
• Kubernetes RBAC Best Practices: Least Privilege Done Right — Comprehensive guide to RBAC hardening.
• Kubernetes Pod Security Standards: From PSP to PSS Migration Guide — Migration path from PSP to the new PSS framework.
• Kubernetes Runtime Security with Falco: Complete Setup Guide — Detailed Falco deployment and rule customization.
• Kubernetes Audit Logging: Complete Setup and Monitoring Guide — Audit policy configuration and SIEM integration.