Learning Environment

Integrations built on the Falco core in a learning environment

minikube

The easiest way to use Falco on Kubernetes in a local environment is on Minikube.

When running minikube with one of the following drivers virtualbox, qemu, kvm2, it creates a VM that runs the various Kubernetes services and a container framework to run Pods, etc. Generally, it's not possible to build the Falco kernel module directly on the minikube VM, as the VM doesn't include the kernel headers for the running kernel.

To address this, starting with Falco 0.33.0 prebuilt kernel modules and bpf probes for the last 3 minikube major versions, including minor versions, are available at https://download.falco.org/?prefix=driver/. This allows the download fallback step to succeed with a loadable driver. New versions of minikube are automatically discovered by the kernel-crawler and periodically built by test-infra. The supported versions can be found at https://falcosecurity.github.io/kernel-crawler/?target=Minikube&arch=x86_64. Falco currently retains previously-built kernel modules for download and continues to provide limited historical support as well.

You can follow the official Get Started! guide to install.

View minikube Get Started! Guide

Note: Ensure that you have installed kubectl.

Falco with syscall source

In order to install Falco with the kernel module or the bpf probe:

Create the cluster with Minikube using a VM driver, in this case, Virtualbox:
```
minikube start --driver=virtualbox
```
Check that all pods are running:
```
kubectl get pods --all-namespaces
```

Add the Falco Helm repository and update the local Helm repository cache:

 helm repo add falcosecurity https://falcosecurity.github.io/charts
 helm repo update

Install Falco using Helm:

helm install falco \
     --set driver.kind=modern_ebpf \
     --set tty=true \
     falcosecurity/falco

The output is similar to:

NAME: falco
LAST DEPLOYED: Wed Apr 17 08:19:53 2024
NAMESPACE: default
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
Falco agents are spinning up on each node in your cluster. After a few
seconds, they are going to start monitoring your containers looking for
security issues.


No further action should be required.


Tip:
You can easily forward Falco events to Slack, Kafka, AWS Lambda and more with falcosidekick.
Full list of outputs: https://github.com/falcosecurity/charts/tree/master/charts/falcosidekick.
You can enable its deployment with `--set falcosidekick.enabled=true` or in your values.yaml.
See: https://github.com/falcosecurity/charts/blob/master/charts/falcosidekick/values.yaml for configuration values.

Check the logs to ensure that Falco is running:

kubectl logs -l app.kubernetes.io/name=falco --all-containers

The output is similar to:

{"level":"INFO","msg":"Resolving dependencies ...","timestamp":"2024-04-17 06:19:49"}
{"level":"INFO","msg":"Installing artifacts","refs":["ghcr.io/falcosecurity/rules/falco-rules:3"],"timestamp":"2024-04-17 06:19:51"}
{"level":"INFO","msg":"Preparing to pull artifact","ref":"ghcr.io/falcosecurity/rules/falco-rules:3","timestamp":"2024-04-17 06:19:51"}
{"level":"INFO","msg":"Pulling layer 1e72f9c4d8fe","timestamp":"2024-04-17 06:19:52"}
{"level":"INFO","msg":"Pulling layer 2e91799fee49","timestamp":"2024-04-17 06:19:52"}
{"level":"INFO","msg":"Pulling layer d4c03e000273","timestamp":"2024-04-17 06:19:52"}
{"digest":"ghcr.io/falcosecurity/rules/falco-rules@sha256:d4c03e000273a0168ee3d9b3dfb2174e667b93c9bfedf399b298ed70f37d623b","level":"INFO","msg":"Verifying signature for artifact","timestamp":"2024-04-17 06:19:52"}
{"level":"INFO","msg":"Signature successfully verified!","timestamp":"2024-04-17 06:19:53"}
{"file":"falco_rules.yaml.tar.gz","level":"INFO","msg":"Extracting and installing artifact","timestamp":"2024-04-17 06:19:53","type":"rulesfile"}
{"digest":"sha256:d4c03e000273a0168ee3d9b3dfb2174e667b93c9bfedf399b298ed70f37d623b","directory":"/rulesfiles","level":"INFO","msg":"Artifact successfully installed","name":"ghcr.io/falcosecurity/rules/falco-rules:3","timestamp":"2024-04-17 06:19:53","type":"rulesfile"}
Wed Apr 17 06:19:54 2024: Falco initialized with configuration file: /etc/falco/falco.yaml
Wed Apr 17 06:19:54 2024: System info: Linux version 5.10.57 (jenkins@ubuntu-iso) (x86_64-minikube-linux-gnu-gcc.br_real (Buildroot 2021.02.12-1-gb75713b-dirty) 9.4.0, GNU ld (GNU Binutils) 2.35.2) #1 SMP Tue Nov 7 06:51:54 UTC 2023
Wed Apr 17 06:19:54 2024: Loading rules from file /etc/falco/falco_rules.yaml
Wed Apr 17 06:19:54 2024: Hostname value has been overridden via environment variable to: minikube
Wed Apr 17 06:19:54 2024: The chosen syscall buffer dimension is: 8388608 bytes (8 MBs)
Wed Apr 17 06:19:54 2024: Starting health webserver with threadiness 4, listening on 0.0.0.0:8765
Wed Apr 17 06:19:54 2024: Loaded event sources: syscall
Wed Apr 17 06:19:54 2024: Enabled event sources: syscall
Wed Apr 17 06:19:54 2024: Opening 'syscall' source with modern BPF probe.
Wed Apr 17 06:19:54 2024: One ring buffer every '2' CPUs.

Falco with multiple sources

Here we run Falco in minikube cluster with multiple sources: syscall and k8s_audit. The next steps show how to start a minikube cluster with the audit logs enabled and deploy Falco with the kernel module and the k8saudit plugin:

First, we need to create a new folder under the configuration folder of minikube:
```
mkdir -p ~/.minikube/files/etc/ssl/certs
```
We are assuming that the minikube configuration folder lives in your home folder otherwise, adjust the command according to your environment.

Let's create the needed configuration files to enable the audit logs. We are going to create a new file under ~/.minikube/files/etc/ssl/certs named audit-policy.yaml and copy the required config into it. Copy the following snippet into your terminal shell:

cat << EOF > ~/.minikube/files/etc/ssl/certs/audit-policy.yaml
apiVersion: audit.k8s.io/v1 # This is required.
kind: Policy
# Don't generate audit events for all requests in RequestReceived stage.
omitStages:
  - "RequestReceived"
rules:
  # Log pod changes at RequestResponse level
  - level: RequestResponse
    resources:
    - group: ""
      # Resource "pods" doesn't match requests to any subresource of pods,
      # which is consistent with the RBAC policy.
      resources: ["pods", "deployments"]

  - level: RequestResponse
    resources:
    - group: "rbac.authorization.k8s.io"
      # Resource "pods" doesn't match requests to any subresource of pods,
      # which is consistent with the RBAC policy.
      resources: ["clusterroles", "clusterrolebindings"]

  # Log "pods/log", "pods/status" at Metadata level
  - level: Metadata
    resources:
    - group: ""
      resources: ["pods/log", "pods/status"]

  # Don't log requests to a configmap called "controller-leader"
  - level: None
    resources:
    - group: ""
      resources: ["configmaps"]
      resourceNames: ["controller-leader"]

  # Don't log watch requests by the "system:kube-proxy" on endpoints or services
  - level: None
    users: ["system:kube-proxy"]
    verbs: ["watch"]
    resources:
    - group: "" # core API group
      resources: ["endpoints", "services"]

  # Don't log authenticated requests to certain non-resource URL paths.
  - level: None
    userGroups: ["system:authenticated"]
    nonResourceURLs:
    - "/api*" # Wildcard matching.
    - "/version"

  # Log the request body of configmap changes in kube-system.
  - level: Request
    resources:
    - group: "" # core API group
      resources: ["configmaps"]
    # This rule only applies to resources in the "kube-system" namespace.
    # The empty string "" can be used to select non-namespaced resources.
    namespaces: ["kube-system"]

  # Log configmap changes in all other namespaces at the RequestResponse level.
  - level: RequestResponse
    resources:
    - group: "" # core API group
      resources: ["configmaps"]

  # Log secret changes in all other namespaces at the Metadata level.
  - level: Metadata
    resources:
    - group: "" # core API group
      resources: ["secrets"]

  # Log all other resources in core and extensions at the Request level.
  - level: Request
    resources:
    - group: "" # core API group
    - group: "extensions" # Version of group should NOT be included.

  # A catch-all rule to log all other requests at the Metadata level.
  - level: Metadata
    # Long-running requests like watches that fall under this rule will not
    # generate an audit event in RequestReceived.
    omitStages:
      - "RequestReceived"
  EOF

Create the file webhook-config.yaml and save the required configuration needed by the k8s api-server to send the audit logs to Falco:

cat << EOF > ~/.minikube/files/etc/ssl/certs/webhook-config.yaml
apiVersion: v1
kind: Config
clusters:
- name: falco
  cluster:
    # certificate-authority: /path/to/ca.crt # for https
    server: http://localhost:30007/k8s-audit
contexts:
- context:
    cluster: falco
    user: ""
  name: default-context
current-context: default-context
preferences: {}
users: []
EOF

Once the configuration files are in place we are ready to start the minikube cluster:

minikube start \
    --extra-config=apiserver.audit-policy-file=/etc/ssl/certs/audit-policy.yaml \
    --extra-config=apiserver.audit-log-path=- \
    --extra-config=apiserver.audit-webhook-config-file=/etc/ssl/certs/webhook-config.yaml \
    --extra-config=apiserver.audit-webhook-batch-max-size=10 \
    --extra-config=apiserver.audit-webhook-batch-max-wait=5s \
    --cpus=4 \
    --driver=virtualbox

 We need at least 4 CPUs for the VM to deploy Falco with multiple sources!

Add the Falco Helm repository and update the local Helm repository cache:

helm repo add falcosecurity https://falcosecurity.github.io/charts
helm repo update

Install Falco using the pre-set values file:

helm install falco \
    --set driver.kind=modern_ebpf \
    --set tty=true \
    --values=https://raw.githubusercontent.com/falcosecurity/charts/master/charts/falco/values-syscall-k8saudit.yaml \
    falcosecurity/falco

Check that the Falco pod is up and running:

kubectl get pods -l app.kubernetes.io/name=falco

Execute the following command and keep the terminal open:
```
kubectl logs -l app.kubernetes.io/name=falco -f
```
The command will follow the log stream of the Falco pod by printing the logs as soon as Falco emits them. And make sure that the following lines are present:
```
Mon Oct 24 15:24:06 2022: Opening capture with plugin 'k8saudit'
Mon Oct 24 15:24:06 2022: Opening 'syscall' source with modern BPF probe
```
It means that Falco is running with the configured sources.

Trigger some rules to check that Falco works as expected. Open a new terminal and make sure that your kubeconfig points to the minikube cluster. Then run:

Trigger a k8saudit rule:

kubectl create cm  myconfigmap --from-literal=username=admin --from-literal=password=123456

In the terminal that we opened in step 8 we should see a log line like this:

15:30:07.927586000: Warning K8s configmap with private credential (user=minikube-user verb=create resource=configmaps configmap=myconfigmap config={"password":"123456","username":"admin"})

Trigger a Falco rule:

kubectl exec $(kubectl get pods -l app.kubernetes.io/name=falco -o name) -- touch /bin/test-bin

Check that a log similar to this one has been printed:

15:32:04.318689836: Error File below a known binary directory opened for writing (user=<NA> user_loginuid=-1 command=touch /bin/test-bin pid=20954 file=/bin/test-bin parent=<NA> pcmdline=<NA> gparent=<NA> container_id=38e44b926166 image=falcosecurity/falco-no-driver) k8s.ns=default k8s.pod=falco-bggd7 container=38e44b926166

kind

kind lets you run Kubernetes on your local computer. This tool requires that you have Docker installed and configured. Currently not working directly on Mac with Linuxkit, but these directions work on Linux guest OS running kind.

The kind Quick Start page shows you what you need to do to get up and running with kind.

View kind Quick Start Guide

To run Falco on a kind cluster is as follows:

Create a configuration file. For example: kind-config.yaml

Add the following to the file:

kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
nodes:
- role: control-plane
  extraMounts:
    # allow Falco to use devices provided by the kernel module
  - hostPath: /dev
    containerPath: /dev
    # allow Falco to use the Docker unix socket
  - hostPath: /var/run/docker.sock
    containerPath: /var/run/docker.sock

Create the cluster by specifying the configuration file:
```
kind create cluster --config=./kind-config.yaml
```
Install Falco on a node in the kind cluster. To install Falco as a daemonset on a Kubernetes cluster use Helm. For more information about the configuration of Falco charts, see https://github.com/falcosecurity/charts/tree/master/charts/falco.

MicroK8s

MicroK8s is the smallest, fastest multi-node Kubernetes. Single-package fully conformant lightweight Kubernetes that works on Linux, Windows and Mac. Perfect for: Developer workstations, IoT, Edge, CI/CD.

You can follow the official Getting Started guide to install.

View MicroK8s Getting Started Guide

To run Falco on MicroK8s:

Install Falco on a node in the MicroK8s cluster. To install Falco as a daemonset on a Kubernetes cluster use Helm. For more information about the configuration of Falco charts, see https://github.com/falcosecurity/charts/tree/master/charts/falco.

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Last modified Apr 17, 2024: update(learning/minikube): update minikube tutorial (d7a6c25)