Files
Anthropic-Cybersecurity-Skills/skills/benchmarking-kubernetes-with-kube-bench/SKILL.md
T
Mahipal 6972fe933e docs(skills): rewrite container-security descriptions to a uniform standard
All 33 container-security skills now carry what it does, an explicit
"Use when" trigger, keywords, and a negative trigger naming the nearest
neighbour. Six collision clusters resolved by differentiating scope
rather than merging, so no skill is removed:

- kube-bench: running the tool vs interpreting findings into an audit
- Calico: portable upstream NetworkPolicy vs Calico-as-CNI vs Calico-only
  CRDs (GlobalNetworkPolicy, HostEndpoint, DNS egress)
- Falco: deploying and operating it vs authoring escape rules
- container escape: tool-agnostic runtime signals vs Falco rule syntax vs
  static posture audit vs offensive breakout
- Trivy: all-target platform and operator vs single-image scan
- Docker: images and Dockerfiles vs daemon.json vs the CIS audit script

Also replaces the templated "When to Use" boilerplate in these files,
including bullets that only restated the skill's own name.

Worst pair (Pod Security Standards vs Pod Security Admission) drops from
0.77 cosine to below the 0.45 threshold. Repo-wide: colliding pairs
60 -> 56, skills involved 105 -> 94.
2026-08-23 17:15:30 +02:00

9.1 KiB

name, description, domain, subdomain, tags, version, author, license, nist_csf, mitre_attack
name description domain subdomain tags version author license nist_csf mitre_attack
benchmarking-kubernetes-with-kube-bench Installs and runs the kube-bench tool against a Kubernetes cluster as a Job, DaemonSet, or standalone binary, selecting the correct benchmark version and targets (control plane, etcd, kubelet, worker nodes) and emitting JSON or JUnit output for pipelines. Use when setting kube-bench up for the first time, choosing which benchmark version and node targets to run, wiring it into CI, or troubleshooting skipped or misdetected checks. Keywords: kube-bench, DaemonSet, --benchmark, --targets, JSON output, JUnit, CI integration. Do not use for interpreting the findings or producing an audit report - use performing-kubernetes-cis-benchmark-with-kube-bench. cybersecurity container-security
kubernetes
kube-bench
cis-benchmark
container-security
hardening
compliance
cluster-security
1.0 mahipal Apache-2.0
PR.PS-01
T1610

Benchmarking Kubernetes with kube-bench

Overview

kube-bench (by Aqua Security) is an open-source tool that checks whether a Kubernetes cluster is deployed securely by running the checks documented in the CIS Kubernetes Benchmark. It inspects the control-plane components (API server, controller manager, scheduler, etcd), the kubelet and worker-node configuration, and cluster-wide policy settings, then reports each check as PASS, FAIL, WARN, or INFO with a remediation recommendation drawn directly from the CIS guidance. Tests are configuration-driven YAML files, so kube-bench tracks new Kubernetes versions and benchmark revisions and supports managed distributions (EKS, GKE, AKS, ACK, OpenShift, RKE, k3s).

Hardening a cluster against the CIS Benchmark directly reduces the attack surface for T1610 (Deploy Container), where an adversary deploys a container to execute code or evade defenses — for example by abusing privileged containers, host namespaces, anonymous API access, or insecure kubelet settings that an unhardened cluster leaves exposed.

kube-bench can run as a standalone binary on a node, inside a container, or — most commonly — as a Kubernetes Job whose pod has the host filesystem mounted so it can read the relevant config files. Output is available as human-readable text, JSON, JUnit, or AWS Security Finding Format (ASFF) and can be pushed to a PostgreSQL database for trend tracking.

When to Use

  • When establishing a security baseline for a new Kubernetes cluster against the CIS Kubernetes Benchmark.
  • When performing periodic compliance audits of control-plane and node hardening.
  • When validating remediation after applying hardening changes (re-run to confirm checks now PASS).
  • When integrating cluster compliance scanning into CI/CD or a continuous monitoring pipeline.
  • When preparing evidence for SOC 2, PCI DSS, or internal hardening compliance.

Prerequisites

  • Access to the cluster: either SSH access to a control-plane/worker node (binary mode) or kubectl with permission to create Jobs (in-cluster mode).
  • Knowledge of the cluster's Kubernetes version (kube-bench auto-detects, or specify with --version / --benchmark).
  • Install kube-bench (Aqua Security official methods):
# Binary release (Linux)
KB_VERSION=0.10.7
curl -L -o kube-bench.tgz \
  "https://github.com/aquasecurity/kube-bench/releases/download/v${KB_VERSION}/kube-bench_${KB_VERSION}_linux_amd64.tar.gz"
tar -xzf kube-bench.tgz
sudo mv kube-bench /usr/local/bin/
sudo cp -R cfg /etc/kube-bench/cfg

# Via Go install
go install github.com/aquasecurity/kube-bench@latest

# Run as a one-off container directly on a node (mounts host config)
docker run --rm --pid=host \
  -v /etc:/etc:ro -v /var:/var:ro \
  -t docker.io/aquasec/kube-bench:latest run --targets node

# Verify
kube-bench version

Objectives

  • Run kube-bench against the appropriate benchmark for the cluster's Kubernetes version.
  • Scan control-plane (master), node, etcd, control-plane policies, and managed-service targets.
  • Produce machine-readable JSON/JUnit output for pipelines and dashboards.
  • Triage FAIL and WARN results and apply CIS remediation guidance.
  • Re-run to validate that remediations now PASS.

MITRE ATT&CK Mapping

Technique ID Name Tactic Relevance
T1610 Deploy Container Execution / Defense Evasion CIS Benchmark hardening enforced by kube-bench restricts privileged/host-namespace deployments, anonymous API access, and insecure kubelet settings that adversaries abuse when deploying malicious containers.

Workflow

1. Run the default scan (auto-detect)

Run all applicable targets, letting kube-bench detect the Kubernetes version and benchmark:

sudo kube-bench

2. Run as a Kubernetes Job (in-cluster)

Apply the provided Job manifest from the kube-bench repo and read the results from the pod logs:

# General-purpose job
kubectl apply -f https://raw.githubusercontent.com/aquasecurity/kube-bench/main/job.yaml

# Wait, then retrieve results
kubectl get pods -l app=kube-bench
kubectl logs -l app=kube-bench

# Platform-specific jobs are available, e.g. EKS:
kubectl apply -f https://raw.githubusercontent.com/aquasecurity/kube-bench/main/job-eks.yaml

3. Target specific components

Use run --targets to scope the scan to particular component groups:

# Control-plane (API server, scheduler, controller manager)
sudo kube-bench run --targets master

# Worker node (kubelet, proxy)
sudo kube-bench run --targets node

# etcd datastore
sudo kube-bench run --targets etcd

# Cluster-wide policies (RBAC, pod security, network policy)
sudo kube-bench run --targets policies

# Combine multiple targets
sudo kube-bench run --targets master,node,etcd,policies

4. Pin a specific benchmark or Kubernetes version

When auto-detection is wrong or you must audit against a specific revision, pin the benchmark explicitly:

# Pin to a specific CIS benchmark revision
sudo kube-bench run --benchmark cis-1.8

# Or map by Kubernetes version
sudo kube-bench --version 1.27

# Managed/distribution-specific benchmarks
sudo kube-bench run --benchmark eks-1.5.0
sudo kube-bench run --benchmark gke-1.6.0
sudo kube-bench run --benchmark rke2-cis-1.7

5. Run or skip individual checks

Focus on or exclude specific check IDs during remediation cycles:

# Run only specific checks
sudo kube-bench run --targets master --check 1.2.1,1.2.2

# Skip noisy/known-accepted checks
sudo kube-bench run --targets node --skip 4.2.6

6. Produce machine-readable output

Emit JSON or JUnit for ingestion into pipelines, SIEM, or dashboards, and write to a file:

# JSON to a file
sudo kube-bench run --targets master,node --json --outputfile kube-bench-report.json

# JUnit (for CI test reporting)
sudo kube-bench --junit --outputfile kube-bench-junit.xml

# AWS Security Finding Format (for Security Hub)
sudo kube-bench run --targets node --asff

7. Triage and remediate FAIL/WARN findings

Each failing check prints a remediation. Apply the CIS-recommended fix on the node/manifest, for example tightening API server flags in the static pod manifest:

# Example remediation for a common control-plane FAIL:
# CIS 1.2.x — ensure anonymous-auth is disabled on the API server.
# Edit the static pod manifest and set the flag:
sudo vi /etc/kubernetes/manifests/kube-apiserver.yaml
#   - --anonymous-auth=false
# The kubelet restarts the static pod automatically.

# Example node remediation — kubelet config file permissions (CIS 4.1.x):
sudo chmod 600 /etc/kubernetes/kubelet/kubelet-config.json
sudo chown root:root /etc/kubernetes/kubelet/kubelet-config.json

8. Re-validate after remediation

Re-run the relevant target and confirm the previously failing checks now PASS, then track the score over time:

sudo kube-bench run --targets master --check 1.2.1 --json --outputfile recheck.json

# Optional: persist results to PostgreSQL for trend tracking
sudo kube-bench run --targets master,node --pgsql

Tools and Resources

Tool / Resource Purpose Link
kube-bench CIS Kubernetes Benchmark checker https://github.com/aquasecurity/kube-bench
kube-bench docs Running / platforms / flags https://aquasecurity.github.io/kube-bench/
CIS Kubernetes Benchmark Source hardening standard https://www.cisecurity.org/benchmark/kubernetes
Trivy Operator Continuous in-cluster compliance + vuln scanning https://github.com/aquasecurity/trivy-operator
kube-hunter Complementary penetration-testing tool https://github.com/aquasecurity/kube-hunter

Validation Criteria

  • kube-bench installed (kube-bench version) or running as a Job.
  • Scan run against the correct benchmark for the cluster's Kubernetes version.
  • master, node, etcd, and policies targets each scanned.
  • JSON/JUnit output produced for pipeline/dashboard ingestion.
  • FAIL and WARN findings triaged and prioritized.
  • CIS remediation applied to control-plane manifests and node configs.
  • Re-run confirms previously failing checks now PASS.
  • Results tracked over time (file archive or PostgreSQL).