/auditing-kubernetes-cluster-rbac

name: auditing-kubernetes-cluster-rbac
description: 'Auditing Kubernetes cluster RBAC configurations to identify overly permissive roles, wildcard permissions, dangerous
  ClusterRoleBindings, service account abuse, and privilege escalation paths using kubectl, rbac-tool, KubiScan, and Kubeaudit.

  '
domain: cybersecurity
subdomain: cloud-security
tags:
- cloud-security
- kubernetes
- rbac
- access-control
- eks
- gke
- aks
version: '1.0'
author: mahipal
license: Apache-2.0
nist_csf:
- PR.IR-01
- ID.AM-08
- GV.SC-06
- DE.CM-01

Auditing Kubernetes Cluster RBAC

When to Use

• When performing security assessments of Kubernetes clusters (EKS, GKE, AKS, or self-managed)
• When validating that RBAC policies enforce least privilege for users and service accounts
• When investigating potential lateral movement or privilege escalation within a Kubernetes cluster
• When compliance audits require documentation of access controls and permissions
• When onboarding new teams to a shared cluster and defining appropriate RBAC policies

**Do not use** for network policy auditing (use Cilium or Calico network policy tools), for container image scanning (use Trivy or Grype), or for runtime security monitoring (use Falco or Sysdig Secure).

Prerequisites

• kubectl configured with cluster-admin or equivalent read permissions to the target cluster
• rbac-tool installed (`kubectl krew install rbac-tool` or binary from GitHub)
• KubiScan installed (`pip install kubiscan`)
• Kubeaudit installed (`brew install kubeaudit` or from GitHub releases)
• Access to the cluster's audit logs for correlating RBAC findings with actual API access

Workflow

Step 1: Enumerate ClusterRoles and Roles with Dangerous Permissions

Identify roles with wildcard permissions, secret access, pod exec, or escalation capabilities.

# List all ClusterRoles with wildcard verb access
kubectl get clusterroles -o json | python3 -c "
import json, sys
data = json.load(sys.stdin)
for role in data['items']:
    name = role['metadata']['name']
    for rule in role.get('rules', []):
        verbs = rule.get('verbs', [])
        resources = rule.get('resources', [])
        if '*' in verbs or '*' in resources:
            print(f'ClusterRole: {name}')
            print(f'  Verbs: {verbs}')
            print(f'  Resources: {resources}')
            print(f'  API Groups: {rule.get(\"apiGroups\", [])}')
            print()
"

# Find roles that can read secrets
kubectl get clusterroles -o json | python3 -c "
import json, sys
data = json.load(sys.stdin)
for role in data['items']:
    name = role['metadata']['name']
    for rule in role.get('rules', []):
        resources = rule.get('resources', [])
        verbs = rule.get('verbs', [])
        if ('secrets' in resources or '*' in resources) and ('get' in verbs or 'list' in verbs or '*' in verbs):
            if not name.startswith('system:'):
                print(f'ClusterRole: {name} -> can access secrets (verbs: {verbs})')
"

# Find roles with pod/exec permissions (container escape risk)
kubectl get clusterroles -o json | python3 -c "
import json, sys
data = json.load(sys.stdin)
for role in data['items']:
    name = role['metadata']['name']
    for rule in role.get('rules', []):
        resources = rule.get('resources', [])
        if 'pods/exec' in resources or 'pods/*' in resources:
            print(f'ClusterRole: {name} -> has pods/exec access')
"

Step 2: Audit ClusterRoleBindings and RoleBindings

Review bindings to identify who has elevated access and detect overly broad group assignments.

# List all ClusterRoleBindings with the subjects
kubectl get clusterrolebindings -o json | python3 -c "
import json, sys
data = json.load(sys.stdin)
for binding in data['items']:
    name = binding['metadata']['name']
    role = binding['roleRef']['name']
    subjects = binding.get('subjects', [])
    for subject in subjects:
        kind = subject.get('kind', '')
        subj_name = subject.get('name', '')
        ns = subject.get('namespace', 'cluster-wide')
        print(f'{name} -> Role: {role} | {kind}: {subj_name} ({ns})')
" | sort

# Find bindings to cluster-admin
kubectl get clusterrolebindings -o json | python3 -c "
import json, sys
data = json.load(sys.stdin)
for binding in data['items']:
    if binding['roleRef']['name'] == 'cluster-admin':
        print(f\"Binding: {binding['metadata']['name']}\")
        for subject in binding.get('subjects', []):
            print(f\"  {subject.get('kind')}: {subject.get('name')} (ns: {subject.get('namespace', 'N/A')})\")
"

# Find bindings granting access to all authenticated users
kubectl get clusterrolebindings -o json | python3 -c "
import json, sys
data = json.load(sys.stdin)
for binding in data['items']:
    for subject in binding.get('subjects', []):
        if subject.get('name') in ['system:authenticated', 'system:unauthenticated']:
            print(f\"WARNING: {binding['metadata']['name']} grants {binding['roleRef']['name']} to {subject['name']}\")
"

Step 3: Scan with rbac-tool for Comprehensive Analysis

Use rbac-tool for automated RBAC analysis including who-can queries and policy generation.

# Who can get secrets across all namespaces
kubectl rbac-tool who-can get secrets

# Who can create pods (potential for container escape)
kubectl rbac-tool who-can create pods

# Who can exec into pods
kubectl rbac-tool who-can create pods/exec

# Who can escalate privileges (bind/escalate verbs)
kubectl rbac-tool who-can bind clusterroles
kubectl rbac-tool who-can escalate clusterroles

# Generate RBAC policy report
kubectl rbac-tool analysis

# Visualize RBAC relationships
kubectl rbac-tool viz --outformat dot > rbac-graph.dot
dot -Tpng rbac-graph.dot -o rbac-graph.png

Step 4: Run KubiScan for Risky Permissions Detection

Use KubiScan to automatically identify risky service accounts, pods, and RBAC configurations.

# Run KubiScan to find risky roles
python3 -m kubiscan -rrol