kubei: A Go repository from arin-pang

Kubei is a vulnerabilities scanning tool that allows users to get an accurate and immediate risk assessment of their kubernetes clusters. Kubei scans all images that are being used in a Kubernetes cluster, including images of application pods and system pods. It doesn’t scan the entire image registries and doesn’t require preliminary integration with CI/CD pipelines.

It is a configurable tool which allows users to define the scope of the scan (target namespaces), the speed, and the vulnerabilities level of interest.

It provides a graphical UI which allows the viewer to identify where and what should be replaced, in order to mitigate the discovered vulnerabilities.

Prerequisites

A Kubernetes cluster is ready, and kubeconfig ( ~/.kube/config) is properly configured for the target cluster.

Required permissions

Read secrets in cluster scope. This is required for getting image pull secrets for scanning private image repositories.
List pods in cluster scope. This is required for calculating the target pods that need to be scanned.
Create jobs in cluster scope. This is required for creating the jobs that will scan the target pods in their namespaces.

Configurations

The file deploy/kubei.yaml is used to deploy and configure Kubei on your cluster.

Set the scan scope. Set the IGNORE_NAMESPACES env variable to ignore specific namespaces. Set TARGET_NAMESPACE to scan a specific namespace, or leave empty to scan all namespaces.
Set the scan speed. Expedite scanning by running parallel scanners. Set the MAX_PARALLELISM env variable for the maximum number of simultaneous scanners.
Set severity level threshold. Vulnerabilities with severity level higher than or equal to SEVERITY_THRESHOLD threshold will be reported. Supported levels are Unknown, Negligible, Low, Medium, High, Critical, Defcon1. Default is Medium.
Set the delete job policy. Set the DELETE_JOB_POLICY env variable to define whether or not to delete completed scanner jobs. Supported values are:
- All - All jobs will be deleted.
- Successful - Only successful jobs will be deleted (default).
- Never - Jobs will never be deleted.

Usage

Run the following command to deploy Kubei on the cluster:

kubectl apply -f https://raw.githubusercontent.com/Portshift/kubei/master/deploy/kubei.yaml
Run the following command to verify that Kubei is up and running:

kubectl -n kubei get pod -lapp=kubei
Then, port forwarding into the Kubei webapp via the following command:

kubectl -n kubei port-forward $(kubectl -n kubei get pods -lapp=kubei -o jsonpath='{.items[0].metadata.name}') 8080
In your browser, navigate to http://localhost:8080/view/ , and then click 'GO' to run a scan.
To check the state of Kubei, and the progress of ongoing scans, run the following command:

kubectl -n kubei logs $(kubectl -n kubei get pods -lapp=kubei -o jsonpath='{.items[0].metadata.name}')
Refresh the page (http://localhost:8080/view/) to update the results.

Running Kubei with an external HTTP/HTTPS proxy

Uncomment and configure the proxy env variables for the Clair and Kubei deployments in deploy/kubei.yaml.

Amazon ECR support

Create an AWS IAM user with AmazonEC2ContainerRegistryFullAccess permissions.

Use the user credentials (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION) to create the following secret:

cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: Secret
metadata:
  name: ecr-sa
  namespace: kubei
type: Opaque
data:
  AWS_ACCESS_KEY_ID: $(echo -n 'XXXX'| base64 -w0)
  AWS_SECRET_ACCESS_KEY: $(echo -n 'XXXX'| base64 -w0)
  AWS_DEFAULT_REGION: $(echo -n 'XXXX'| base64 -w0)
EOF

Note:

Secret name must be ecr-sa
Secret data keys must be set to AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY and AWS_DEFAULT_REGION

Google GCR support

Create a Google service account with Artifact Registry Reader permissions.

Use the service account json file to create the following secret

kubectl -n kubei create secret generic --from-file=sa.json gcr-sa