kube-bench is a Go application that checks whether Kubernetes is deployed securely by running the checks documented in the CIS Kubernetes Benchmark.

Note that it is impossible to inspect the master nodes of managed clusters, e.g. GKE, EKS and AKS, using kube-bench as one does not have access to such nodes, although it is still possible to use kube-bench to check worker node configuration in these environments.

Tests are configured with YAML files, making this tool easy to update as test specifications evolve.

Table of Contents

• Table of Contents
  • CIS Kubernetes Benchmark support
  • Installation
  • Running kube-bench
    • Running inside a container
    • Running in a Kubernetes cluster
    • Running in an EKS cluster
    • Installing from a container
    • Installing from sources
  • Running on OpenShift
  • Output
  • Configuration
  • Test config YAML representation
    • Omitting checks
  • Roadmap
  • Testing locally with kind
  • Contributing
    • Bugs
    • Features
    • Pull Requests

CIS Kubernetes Benchmark support

kube-bench supports the tests for Kubernetes as defined in the CIS Benchmarks 1.3.0 to 1.5.0 respectively.

CIS Kubernetes Benchmark	kube-bench config	Kubernetes versions
1.3.0	cis-1.3	1.11-1.12
1.4.1	cis-1.4	1.13-1.14
1.5.0	cis-1.5	1.15-

By default, kube-bench will determine the test set to run based on the Kubernetes version running on the machine.

There is also preliminary support for Red Hat's OpenShift Hardening Guide for 3.10 and 3.11. Please note that kube-bench does not automatically detect OpenShift - see below.

Installation

You can choose to

• run kube-bench from inside a container (sharing PID namespace with the host)
• run a container that installs kube-bench on the host, and then run kube-bench directly on the host
• install the latest binaries from the Releases page,
• compile it from source.

Running kube-bench

If you run kube-bench directly from the command line you may need to be root / sudo to have access to all the config files.

kube-bench automatically selects which controls to use based on the detected node type and the version of Kubernetes a cluster is running. This behavior can be overridden by specifying the master or node subcommand and the --version flag on the command line.

The Kubernetes version can also be set with the KUBE_BENCH_VERSION environment variable. The value of --version takes precedence over the value of KUBE_BENCH_VERSION.

For example, run kube-bench against a master with version auto-detection:

kube-bench master

Or run kube-bench against a worker node using the tests for Kubernetes version 1.13:

kube-bench node --version 1.13

kube-bench will map the --version to the corresponding CIS Benchmark version as indicated by the mapping table above. For example, if you specify --version 1.13, this is mapped to CIS Benchmark version cis-1.14.

Alternatively, you can specify --benchmark to run a specific CIS Benchmark version:

kube-bench node --benchmark cis-1.4

If you want to target specific CIS Benchmark target (i.e master, node, etcd, etc...) you can use the run --targets subcommand.

kube-bench --benchmark cis-1.4 run --targets master,node

or

kube-bench --benchmark cis-1.5 run --targets master,node,etcd,policies

The following table shows the valid targets based on the CIS Benchmark version.

CIS Benchmark	Targets
cis-1.3	master, node
cis-1.4	master, node
cis-1.5	master, controlplane, node, etcd, policies

If no targets are specified, kube-bench will determine the appropriate targets based on the CIS Benchmark version.

controls for the various versions of CIS Benchmark can be found in directories with same name as the CIS Benchmark versions under cfg/, for example cfg/cis-1.4.

Note: It is an error to specify both --version and --benchmark flags together

Running inside a container

You can avoid installing kube-bench on the host by running it inside a container using the host PID namespace and mounting the /etc and /var directories where the configuration and other files are located on the host so that kube-bench can check their existence and permissions.

docker run --pid=host -v /etc:/etc:ro -v /var:/var:ro -t aquasec/kube-bench:latest [master|node] --version 1.13

Note: the tests require either the kubelet or kubectl binary in the path in order to auto-detect the Kubernetes version. You can pass -v $(which kubectl):/usr/bin/kubectl to resolve this. You will also need to pass in kubeconfig credentials. For example:

docker run --pid=host -v /etc:/etc:ro -v /var:/var:ro -v $(which kubectl):/usr/bin/kubectl -v ~/.kube:/.kube -e KUBECONFIG=/.kube/config -t aquasec/kube-bench:latest [master|node] 

You can use your own configs by mounting them over the default ones in /opt/kube-bench/cfg/

docker run --pid=host -v /etc:/etc:ro -v /var:/var:ro -t -v path/to/my-config.yaml:/opt/kube-bench/cfg/config.yam -v $(which kubectl):/usr/bin/kubectl -v ~/.kube:/.kube -e KUBECONFIG=/.kube/config aquasec/kube-bench:latest [master|node]

Running in a Kubernetes cluster

You can run kube-bench inside a pod, but it will need access to the host's PID namespace in order to check the running processes, as well as access to some directories on the host where config files and other files are stored.

Master nodes are automatically detected by kube-bench and will run master checks when possible. The detection is done by verifying that mandatory components for master, as defined in the config files, are running (see Configuration).

The supplied job.yaml file can be applied to run the tests as a job. For example:

$ kubectl apply -f job.yaml
job.batch/kube-bench created

$ kubectl get pods
NAME                      READY   STATUS              RESTARTS   AGE
kube-bench-j76s9   0/1     ContainerCreating   0          3s

# Wait for a few seconds for the job to complete
$ kubectl get pods
NAME                      READY   STATUS      RESTARTS   AGE
kube-bench-j76s9   0/1     Completed   0          11s

# The results are held in the pod's logs
kubectl logs kube-bench-j76s9
[INFO] 1 Master Node Security Configuration
[INFO] 1.1 API Server
...

You can still force to run specific master or node checks using respectively job-master.yaml and job-node.yaml.

To run the tests on the master node, the pod needs to be scheduled on that node. This involves setting a nodeSelector and tolerations in the pod spec.

The default labels applied to master nodes has changed since Kubernetes 1.11, so if you are using an older version you may need to modify the nodeSelector and tolerations to run the job on the master node.

Running in an EKS cluster

There is a job-eks.yaml file for running the kube-bench node checks on an EKS cluster. The significant difference on EKS is that it's not possible to schedule jobs onto the master node, so master checks can't be performed

1. To create an EKS Cluster refer to Getting Started with Amazon EKS in the Amazon EKS User Guide

• Information on configuring eksctl, kubectl and the AWS CLI is within

2. Create an Amazon Elastic Container Registry (ECR) repository to host the kube-bench container image

aws ecr create-repository --repository-name k8s/kube-bench --image-tag-mutability MUTABLE

3. Download, build and push the kube-bench container image to your ECR repo

git clone https://github.com/aquasecurity/kube-bench.git
$(aws ecr get-login --no-include-email --region <AWS_REGION>)
docker build -t k8s/kube-bench .
docker tag k8s/kube-bench:latest <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest
docker tag k8s/kube-bench:latest <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest
docker push <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest

4. Copy the URI of your pushed image, the URI format is like this: <AWS_ACCT_NUMBER>.dkr.ecr.<AWS_REGION>.amazonaws.com/k8s/kube-bench:latest
5. Replace the image value in job-eks.yaml with the URI from Step 4
6. Run the kube-bench job on a Pod in your Cluster: kubectl apply -f job-eks.yaml
7. Find the Pod that was created, it should be in the default namespace: kubectl get pods --all-namespaces
8. Retrieve the value of this Pod and output the report, note the Pod name will vary: kubectl logs kube-bench-<value>

• You can save the report for later reference: kubectl logs kube-bench-<value> > kube-bench-report.txt

Installing from a container

This command copies the kube-bench binary and configuration files to your host from the Docker container: ** binaries compiled for linux-x86-64 only (so they won't run on macOS or Windows) **

docker run --rm -v `pwd`:/host aquasec/kube-bench:latest install

You can then run ./kube-bench [master|node].

Installing from sources

If Go is installed on the target machines, you can simply clone this repository and run as follows (assuming your GOPATH is set):

go get github.com/aquasecurity/kube-bench
go get github.com/golang/dep/cmd/dep
cd $GOPATH/src/github.com/aquasecurity/kube-bench
$GOPATH/bin/dep ensure -vendor-only
go build -o kube-bench .

# See all supported options
./kube-bench --help

# Run all checks
./kube-bench

Running on OpenShift

OpenShift Hardening Guide	kube-bench config
ocp-3.10	rh-0.7
ocp-3.11	rh-0.7

kube-bench includes a set of test files for Red Hat's OpenShift hardening guide for OCP 3.10 and 3.11. To run this you will need to specify --benchmark rh-07, or --version ocp-3.10 or --version ocp-3.11

when you run the kube-bench command (either directly or through YAML).

Output

There are three output states:

• [PASS] and [FAIL] indicate that a test was run successfully, and it either passed or failed.
• [WARN] means this test needs further attention, for example it is a test that needs to be run manually.
• [INFO] is informational output that needs no further action.

Note:

• If the test is Manual, this always generates WARN (because the user has to run it manually)
• If the test is Scored, and kube-bench was unable to run the test, this generates FAIL (because the test has not been passed, and as a Scored test, if it doesn't pass then it must be considered a failure).
• If the test is Not Scored, and kube-bench was unable to run the test, this generates WARN.
• If the test is Scored, type is empty, and there are no test_items present, it generates a WARN.

Configuration

Kubernetes configuration and binary file locations and names can vary from installation to installation, so these are configurable in the cfg/config.yaml file.

Any settings in the version-specific config file cfg/<version>/config.yaml take precedence over settings in the main cfg/config.yaml file.

You can read more about kube-bench configuration in our documentation.

Test config YAML representation

The tests (or "controls") are represented as YAML documents (installed by default into ./cfg). There are different versions of these test YAML files reflecting different versions of the CIS Kubernetes Benchmark. You will find more information about the test file YAML definitions in our documentation.

Omitting checks

If you decide that a recommendation is not appropriate for your environment, you can choose to omit it by editing the test YAML file to give it the check type skip as in this example:

  checks:
  - id: 2.1.1
    text: "Ensure that the --allow-privileged argument is set to false (Scored)"
    type: "skip"
    scored: true

No tests will be run for this check and the output will be marked [INFO].

Roadmap

Going forward we plan to release updates to kube-bench to add support for new releases of the Benchmark, which in turn we can anticipate being made for each new Kubernetes release.

We welcome PRs and issue reports.

Testing locally with kind

Our makefile contains targets to test your current version of kube-bench inside a Kind cluster. This can be very handy if you don't want to run a real Kubernetes cluster for development purposes.

First, you'll need to create the cluster using make kind-test-cluster this will create a new cluster if it cannot be found on your machine. By default, the cluster is named kube-bench but you can change the name by using the environment variable KIND_PROFILE.

If kind cannot be found on your system the target will try to install it using go get

Next, you'll have to build the kube-bench docker image using make build-docker, then we will be able to push the docker image to the cluster using make kind-push.

Finally, we can use the make kind-run target to run the current version of kube-bench in the cluster and follow the logs of pods created. (Ctrl+C to exit)

Every time you want to test a change, you'll need to rebuild the docker image and push it to cluster before running it again. ( make build-docker kind-push kind-run )

Contributing

Bugs

If you think you have found a bug please follow the instructions below.

• Please spend a small amount of time giving due diligence to the issue tracker. Your issue might be a duplicate.
• Open a new issue if a duplicate doesn't already exist.
• Note the version of kube-bench you are running (from kube-bench version) and the command line options you are using.
• Note the version of Kubernetes you are running (from kubectl version or oc version for OpenShift).
• Set -v 10 command line option and save the log output. Please paste this into your issue.
• Remember users might be searching for your issue in the future, so please give it a meaningful title to help others.

Features

We also use the GitHub issue tracker to track feature requests. If you have an idea to make kube-bench even more awesome follow the steps below.

• Open a new issue.
• Remember users might be searching for your issue in the future, so please give it a meaningful title to helps others.
• Clearly define the use case, using concrete examples. For example, I type this and kube-bench does that.
• If you would like to include a technical design for your feature please feel free to do so.

Pull Requests

We welcome pull requests!

• Your PR is more likely to be accepted if it focuses on just one change.
• Please include a comment with the results before and after your change.
• Your PR is more likely to be accepted if it includes tests. (We have not historically been very strict about tests, but we would like to improve this!).
• You're welcome to submit a draft PR if you would like early feedback on an idea or an approach.
• Happy coding!