Lead Image © Corina Rosu, 123rf.com

Lead Image © Corina Rosu, 123rf.com

CRI-O and Kubernetes Security

Critical Tool

Article from ADMIN 60/2020
The crictl troubleshooting tool and runc container runtime pair up to help identify and diagnose issues with Kubernetes Pods and clusters.

Container runtimes continue to evolve at a fast rate, and Red Hat has shifted their focus in the direction of their own Podman container runtime in favor of Docker. Red Hat's open source contributions to Kubernetes also means that CRI-O has been adopted by their OpenShift enterprise platform as the runtime, and Red Hat Enterprise Linux will offer Podman for user interaction with containers in the future.

Although Docker still continues to be used as the universal container runtime, the popular Kubernetes container orchestrator moved over to CRI-O as a lightweight default runtime alternative a number of versions ago. CRI-O (Container Runtime Interface) began life at Red Hat in 2016 and was passed on to Kubernetes in 2019. Red Hat described the runtime when it was launched as benefiting from a "narrow focus [that] drives stability, performance and security features down the stack, allowing the cloud native ecosystem to reliably focus at the Kubernetes layer and above" [1].

Because CRI-O is likely to be entrenched in Kubernetes for the foreseeable future, learning about this relatively nascent and critical component is a useful exercise. For further information on alternative Kubernetes runtimes, you can refer to a document about container runtimes on the Kubernetes website [2].

In this article, I look at CRI-O in more detail and how the use of a troubleshooting tool in combination with an unexpected debugging companion enables developers to access Kubernetes resources without having to make changes directly to the Kubernetes cluster itself.

Jigsaw Puzzle

The precise definition of a container runtime is surrounded by confusion and ambiguity. The CRI-O runtime [3] is an Open Container Initiative (OCI)-compliant container runtime. Both runC and Kata Containers are currently supported and effectively sit on top of CRI-O to provide the necessary functionality required to run Pods. Both components are often referred to as runtimes. One of the key benefits for Kubernetes when it comes to CRI-O is that its development cycle is tied closely to both the major and minor releases of Kubernetes itself, which makes upgrade compatibility much cleaner.

The components that comprise CRI-O include:

  • OCI-compatible runtime
  • Storage
  • Image
  • Networking
  • Container monitoring

All have their own GitHub repositories [4]. The CRI-O site has more information on these repositories, as well.

To keep CRI-O minimal in size, you cannot interact with it directly in the same way you might with Docker. A number of applications (Table 1) interface with CRI-O to build images, for example, or run Pods.

Table 1

CRI-O Container Tools

Tool Capability
runC Run containers. You might be familiar with this binary because it is used in many container runtimes and usually is the last component in the runtime chain.
Podman Stop, start, attach, enter, and run containers. Daemonless by design, no container engine is needed to use Podman to run Pods or containers.
Buildah Build, push, and sign images.
Skopeo Copy, remove, inspect, or sign images.

Red Hat resources [5] [6] can help you understand fully how CRI-O is used within Kubernetes and OpenShift. Note the useful graphics that explain the difference between a user interacting with containers and how Kubernetes introduces CRI-O into the mix, looking out for the ubiquitous runC in both examples. The "Standing Alone" box explains how to install CRI-O as a standalone installation.

Standing Alone

CRI-O is pretty easy to install as a standalone test installation with minikube [7] instead of Kubernetes. My installation was v1.17 on Ubuntu 18.04 (with Linux Mint 19 on top):

$ . /etc/os-release

Because I'm using Linux Mint and avoiding Ubuntu naming clashes, I manually add a line to the /etc/apt/sources.list.d/devel\:kubic\:libcontainers\:stable.list file:

deb http://download.opensuse.org/ repositories/devel:/kubic:/ libcontainers:/stable/xUbuntu_18.04/ /

Next, you need to trust the package repository just added to the Apt package manager:

$ wget https://download.opensuse.org/ repositories/devel:/kubic:/ libcontainers:/stable/xUbuntu_18.04/ Release.key -O- | sudo apt-key add -

The OK response is all you need to know that it has been added successfully. Next, update your packages and install the CRI-O package (abbreviated output follows):

$ apt update
$ apt install cri-o-${CRIO_VERSION}
The following NEW packages will be installed
0 to upgrade, 1 to newly install, 0 to remove and 0 not to upgrade.
Need to get 17.3 MB of archives.
After this operation, 86.0 MB of additional disk space will be used.

As the output demonstrates, you are only adding 86MB of disk footprint when installing CRI-O. As mentioned, however, you are not going to get much mileage out of the runtime on its own. The status command reveals that it's not running:

$ crio-status info
Get http://%2Fvar%2Frun%2Fcrio%2Fcrio.sock/info: dial unix /var/run/crio/crio.sock: connect: no such file or directory

Also, systemd shows the service is disabled:

$ systemctl status -l crio
* crio.service - Container Runtime Interface for OCI (CRI-O)
   Loaded: loaded (/usr/lib/systemd/system/crio.service; disabled; vendor preset: enabled)
   Active: inactive (dead)
     Docs: https://github.com/cri-o/cri-o

The crio --help command output describes the implementation:

$ crio --help
crio is meant to provide an integration path between OCI conformant runtimes
and the kubelet. Specifically, it implements the Kubelet Container Runtime
Interface (CRI) using OCI conformant runtimes. The scope of crio is tied to the
scope of the CRI.
1. Support multiple image formats including the existing Docker and OCI image formats.
2. Support for multiple means to download images including trust & image verification.
3. Container image management (managing image layers, overlay filesystems, etc).
4. Container process lifecycle management.
5. Monitoring and logging required to satisfy the CRI.
6. Resource isolation as required by the CRI.


Instead of continuing with CRI-O locally, I will look at it in action in an exceedingly sophisticated browser-based laboratory environment that saves creating a potentially complex Kubernetes cluster. Once you have made sure that your environment is running, you can use the helpful crictl tool to test CRI-O Pods running in the cluster to get a better idea of how to debug Pods.

The lab cluster comes courtesy of the clever Katacoda website [8] run by O'Reilly. You might need to add an email address and password to access the Getting Started with Kubeadm Crio scenario. Do so now, if required. The scenario is described as offering the ability to "Learn how to deploy a CRI-O based Kubeadm cluster."

To proceed, click the Start Scenario button on the first screen and follow the prompts throughout the tutorial to spin up a Kubernetes cluster with Kubeadm. Then, you can query the CRI-O runtime directly with the clever crictl tool.

Figure 1 is the first screen asking for commands to execute in the lab. Katacoda offers a genuinely exceptional interface in which to run tests (or, by design, to learn greatly from). Not only can you type into the command-line interface (CLI) in the right window, but you also can click the suggested commands in the tutorial in the left window to execute those commands without having to cut and paste them into the CLI.

Figure 1: Katacoda has a learning scenario in which you can enter commands. Source: katacoda.com [8].

In the left pane, the note under Task explains that you need to restart the CRI-O runtime to fix a bug with the command:

$ systemctl restart crio

After you click that command or enter it manually in the CLI, the next task, again courtesy of Katacoda's documentation, is to initialize the cluster again to get started:

$ kubeadm init --cri-socket=/var/run/crio/crio.sock --kubernetes-version $(kubeadm version -o short)

Some comments appear in the screen output from the cluster initialization. You are interested in using the debugging tool, but to interact in a sane way with the cluster, make sure you enter the three commands in the initialization output so you can access the cluster and interact properly. To see if any Docker containers are running, enter:

$ docker ps

As suspected no containers are visible to Docker Engine. Now, try the crictl help command to see what you can do with the tool (Listing 1). If you require debugging output, add -D to the command. Before continuing, make sure you can access the running Pods in the cluster with the command:

$ kubectl get pods --all-namespaces

Listing 1

Abbreviated crictl Help Output

     attach        Attach to a running container
     create        Create a new container
     exec          Run a command in a running container
     version       Display runtime version information
     images        List images
     inspect       Display the status of a container
     inspecti      Return the status of an image
     inspectp      Display the status of a pod sandbox
     logs          Fetch the logs of a container
     port-forward  Forward local port to a pod sandbox
     ps            List containers
     pull          Pull an image from a registry
     runp          Run a new pod sandbox
     rm            Remove a container
     rmi           Remove an image
     rmp           Remove a pod sandbox
     pods          List pod sandboxes
     start         Start a created container
     info          Display information of the container runtime
     stop          Stop a running container
     stopp         Stop a running pod sandbox
     update        Update a running container
     config        Get and set crictl options
     stats         List container(s) resource usage statistics
     completion    Output bash shell completion code
     help, h       Show a list of commands or help for one command

You should be able to see Pods running for all the usual suspects: Etcd to store your configuration, the API server with which kubectl interacts, the controller, the proxy, the DNS, and the scheduler that allocates Pods to nodes with spare capacity when they are spun up.

The lab cluster looks happy, so you can now proceed with your troubleshooting tool: Check the CRI-O configuration settings in this file,

$ cat /etc/crictl.yaml
runtime-endpoint: /var/run/crio/crio.sock

and perform the simple query command to check for Pods (Figure 2):

Figure 2: The crictl output style when listing CRI-O Pods.
$ crictl pods

In the STATE column, you can see that each Pod is shown as being SANDBOX_READY . A really useful GitHub crib sheet [9] can assist with other commands if you want to learn more. The page shows how to list and inspect images with the crictl images command. The relatively familiar Dockeresque output lists the name, tag, and hash ID.

To display any running containers (not just Pods), the usual command applies Docker-style by using the ps rather than the pods command (see Listing 1):

$ crictl ps

Appending -a at the end of the command will show stopped containers, as well. You can see how the tool is configured with the info command (Listing 2).

Listing 2

crictl info

01 $ crictl info
02 {
03   "status": {
04     "conditions": [
05       {
06         "type": "RuntimeReady",
07         "status": true,
08         "reason": "",
09         "message": ""
10       },
11       {
12         "type": "NetworkReady",
13         "status": true,
14         "reason": "",
15         "message": ""
16       }
17     ]
18   }
19 }

To check the current version, use:

$ crictl version
Version:  0.1.0
RuntimeName:  cri-o
RuntimeVersion:  1.9.10-dev
RuntimeApiVersion:  v1alpha1

Back with Katacoda, you carry on through page 4 of 6 within the learning scenario by clicking the commands in the left window to set up your Kubernetes cluster. However, when you get to page 4, I found a glitch in the docs. (I reported it to Katacoda like a good citizen, so it may be fixed.) The command you should run is:

$ kubectl apply -f /opt/weave-kube

In other words, you should not use /opt/weave-kube.yaml, as was originally suggested. Running the correct command sets up Weave networking [10] to complete the cluster build.

Now you want to create a sandbox Pod starting with a similar example shown in the Kubernetes documentation [11] (Listing 3).

Listing 3

Sample Sandbox Pod Config

01 {
02     "metadata": {
03         "name": "debug-sandbox-pod",
04         "namespace": "default",
05         "attempt": 1,
06         "uid": "hdishd83djaidwnduwk28bcsb"
07     },
08     "logDirectory": "/tmp",
09     "linux": {
10     }
11 }

By saving the content shown in Listing 3 in a file called debug.json, you can now run the command to create a sandbox Pod, so you can test from inside the cluster with that Pod:

$ crictl runp debug.json

The hash ID of the sandbox Pod is returned, denoting success. Note that eventually Kubernetes will apparently delete this Pod after some housekeeping.

One advantage of crictl when troubleshooting is that you can even query a container with the runc companion tool when CRI-O is stopped:

$ runc ps 4ecc5504f0453fa8dbd3f5990de980fa67d56ef629063a6ab4d47de05a2905a7

The runc runtime command lists the running processes inside the sandbox container and can be used on other containers, as well.

A Red Hat CRI-O guide [12] encourages you to switch off the crio systemd service to see if you can still query potential Pod issues:

$ systemctl stop crio

When you check the service's status (Listing 4), you can see the service is "dead" or "inactive," as it was when it was installed locally and didn't start it up.

Listing 4

systemctl status crio

$ systemctl status crio
* crio.service - Open Container Initiative Daemon
   Loaded: loaded (/usr/local/lib/systemd/system/crio.service; enabled; vendor preset: enabled)
   Active: inactive (dead) since Sun 2020-09-20 17:01:22 UTC; 14s ago
     Docs: https://github.com/kubernetes-incubator/cri-o
  Process: 4786 ExecStart=/usr/local/bin/crio $CRIO_STORAGE_OPTIONS $CRIO_NETWORK_OPTIONS (code=exited, status=0/S
 Main PID: 4786 (code=exited, status=0/SUCCESS)

Now you can query another Pod, even without the CRI-O runtime being active. Scroll back up Katacoda's terminal history, choose another Pod (e.g., this time the kube-proxy Pod), and paste its hash into the command (Listing 5). You have confirmed that CRI-O is unavailable. To check the runc perspective, enter the command in Listing 6.

Listing 5

crictl ps

$ crictl ps | grep 37366ad82a73d
2020/09/20 17:09:58 grpc: addrConn.resetTransport failed to create client transport: connection error: desc = "transport: dial unix /var/run/crio/crio.sock: connect: no such file or directory"; Reconnecting to {/var/run/crio/crio.sock <nil>}
FATA[0000] listing containers failed: rpc error: code = Unavailable desc = grpc: the connection is unavailable

Listing 6

runc list

$ runc list | grep 37366ad82a73d
37366ad82a73d4158b1c7f99762b185ee1296f1aebd30861ca790401fe4c281a   5643        running     /run/containers/storage/overlay-containers/37366ad82a73d4158b1c7f99762b185ee1296f1aebd30861ca790401fe4c281a/userdata   2020-09-20T16:27:27.618813008Z   root

Now that you've identified the storage location of your kube-proxy Pod from the output (userdata ), you can interrogate its configuration with the command:

$ ls -al /run/containers/storage/overlay-containers/37366ad82a73d4158b1c7f99762b185ee1296f1aebd30861ca790401fe4c281a/userdata

Listing 7 shows the contents of that directory. Only one file, config.json, is worth investigating (the others are empty, barring the PID placeholder). Listing 8 is the heavily abbreviated output for the kube-proxy Pod that shows some of the environment variables held internally, among other configuration settings, for the Pod's service, which could be useful for troubleshooting.

Listing 7

Content of userdata

total 40
drwx------ 2 root root   120 Sep 20 16:27 .
drwx------ 3 root root    60 Sep 20 16:27 ..
srwx------ 1 root root     0 Sep 20 16:27 attach
-rw-r--r-- 1 root root 33708 Sep 20 16:27 config.json
prw-r--r-- 1 root root     0 Sep 20 16:27 ctl
-rw-r--r-- 1 root root     4 Sep 20 16:27 pidfile

Listing 8

config.json File Content

01 {
02   "ociVersion": "1.0.0",
03   "process": {
04     "user": {
05       "uid": 0,
06       "gid": 0
07     },
08     "args": [
09       "/usr/local/bin/kube-proxy",
10       "--config=/var/lib/kube-proxy/config.conf"
11     ],
12     "env": [
13       "PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
14       "TERM=xterm",
15       "HOSTNAME=master01",
16       "KUBE_DNS_PORT_53_TCP_PROTO=tcp",
17       "KUBE_DNS_PORT_53_TCP_PORT=53",
19       "KUBERNETES_PORT_443_TCP=tcp://",
20       "KUBERNETES_PORT_443_TCP_PROTO=tcp",
22       "KUBE_DNS_PORT_53_UDP=udp://",

If the content shown in Listing 8 had not been abbreviated, you would see seemingly endless information about what the Pod knows about Kubernetes and vice versa.

The End Is Nigh

I have barely scratched the surface of the CRI-O runtime and the way it interacts with Kubernetes. Under usual circumstances, you might be hard-pressed to find someone who works with technology that can coherently explain all of the nuances of the container runtimes available today, but it is worth learning the basics, at the very least.

Exploring the options in the useful crictl tool and looking at how runc can be used to diagnose issues is a valuable exercise in itself. In your next hour of need, when a Pod or a cluster is misbehaving, turn to these applications.

The Author

Chris Binnie's latest book, Linux Server Security: Hack and Defend, shows how hackers launch sophisticated attacks to compromise servers, steal data, and crack complex passwords, so you can learn how to defend against such attacks. In the book, he also shows you how to make your servers invisible, perform penetration testing, and mitigate unwelcome attacks. You can find out more about DevOps, DevSecOps, Containers, and Linux security on his website: https://www.devsecops.cc.

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