Kubeclarity : Tool For Detection And Management Of Software Bill Of Materials

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KubeClarity is a tool for detection and management of Software Bill Of Materials (SBOM) and vulnerabilities of container images and filesystems. It scans both runtime K8s clusters and CI/CD pipelines for enhanced software supply chain security.

SBOM & vulnerability detection challenges

  • Effective vulnerability scanning requires an accurate Software Bill Of Materials (SBOM) detection:
    • Various programming languages and package managers
    • Various OS distributions
    • Package dependency information is usually stripped upon build
  • Which one is the best scanner/SBOM analyzer?
  • What should we scan: Git repos, builds, container images or runtime?
  • Each scanner/analyzer has its own format – how to compare the results?
  • How to manage the discovered SBOM and vulnerabilities?
  • How are my applications affected by a newly discovered vulnerability?

Solution

  • Separate vulnerability scanning into 2 phases:
    • Content analysis to generate SBOM
    • Scan the SBOM for vulnerabilities
  • Create a pluggable infrastructure to:
    • Run several content analyzers in parallel
    • Run several vulnerability scanners in parallel
  • Scan and merge results between different CI stages using KubeClarity CLI
  • Runtime K8s scan to detect vulnerabilities discovered post-deployment
  • Group scanned resources (images/directories) under defined applications to navigate the object tree dependencies (applications, resources, packages, vulnerabilities)

Features

  • Dashboard
    • Fixable vulnerabilities per severity
    • Top 5 vulnerable elements (applications, resources, packages)
    • New vulnerabilities trends
    • Package count per license type
    • Package count per programming language
    • General counters
  • Applications
    • Automatic application detection in K8s runtime
    • Create/edit/delete applications
    • Per application, navigation to related:
      • Resources (images/directories)
      • Packages
      • Vulnerabilities
      • Licenses in use by the resources
  • Application Resources (images/directories)
    • Per resource, navigation to related:
      • Applications
      • Packages
      • Vulnerabilities
  • Packages
    • Per package, navigation to related:
      • Applications
      • Linkable list of resources and the detecting SBOM analyzers
      • Vulnerabilities
  • Vulnerabilities
    • Per vulnerability, navigation to related:
      • Applications
      • Resources
      • List of detecting scanners
  • K8s Runtime scan
    • On-demand or scheduled scanning
    • Automatic detection of target namespaces
    • Scan progress and result navigation per affected element (applications, resources, packages, vulnerabilities)
    • CIS Docker benchmark
  • CLI (CI/CD)
    • SBOM generation using multiple integrated content analyzers (Syft, cyclonedx-gomod)
    • SBOM/image/directory vulnerability scanning using multiple integrated scanners (Grype, Dependency-track)
    • Merging of SBOM and vulnerabilities across different CI/CD stages
    • Export results to KubeClarity backend
  • API
    • The API for KubeClarity can be found here

High level architecture

Getting started

Integration with SBOM generators and vulnerability scanners

KubeClarity content analyzer integrates with the following SBOM generators:

  • Syft
  • Cyclonedx-gomod

KubeClarity vulnerability scanner integrates with the following scanners:

  • Grype
  • Dependency-Track

The integrations with the SBOM generators can be found here, and the integrations with the vulnerability scanners can be found here here. To enable and configure the supported SBOM generators and vulnerability scanners, please check the “analyzer” and “scanner” config under the “vulnerability-scanner” section in Helm values.

Contributions of integrations with additional tools are more than welcome!

Install KubeClarity in a K8s cluster using Helm:

  • Add Helm repo

helm repo add kubeclarity https://openclarity.github.io/kubeclarity

  • Save KubeClarity default chart values

helm show values kubeclarity/kubeclarity > values.yaml

  • Check the configuration in values.yaml and update the required values if needed
  • Deploy KubeClarity with Helm

helm install –values values.yaml –create-namespace kubeclarity kubeclarity/kubeclarity -n kubeclarity

or for OpenShift Restricted SCC compatible install:

helm install –values values.yaml –create-namespace kubeclarity kubeclarity/kubeclarity -n kubeclarity –set global.openShiftRestricted=true \
–set kubeclarity-postgresql.securityContext.enabled=false –set kubeclarity-postgresql.containerSecurityContext.enabled=false \
–set kubeclarity-postgresql.volumePermissions.enabled=true –set kubeclarity-postgresql.volumePermissions.securityContext.runAsUser=”auto” \
–set kubeclarity-postgresql.shmVolume.chmod.enabled=false

  • Port forward to KubeClarity UI:

kubectl port-forward -n kubeclarity svc/kubeclarity-kubeclarity 9999:8080

  • Open KubeClarity UI in the browser: http://localhost:9999/

Required K8s permissions

  • Read secrets in cluster scope. This is required for getting image pull secrets for scanning private image repositories.
  • Read config maps in cluster scope. This is required for getting the configured template of the scanner job.
  • List pods in cluster scope. This is required for calculating the target pods that need to be scanned.
  • List namespaces. This is required for fetching the target namespaces to scan in K8s runtime scan UI.
  • Create & delete jobs in cluster scope. This is required for managing the jobs that will scan the target pods in their namespaces.

Build and run locally with demo data

  • Build UI & backend and start the backend locally (2 options):
    • Using docker:
      • Build UI and backend (the image tag is set using VERSION)

VERSION=test make docker-backend

  • Run the backend using demo data:

docker run -p 8080:8080 -e FAKE_RUNTIME_SCANNER=true -e FAKE_DATA=true -e ENABLE_DB_INFO_LOGS=true -e DATABASE_DRIVER=LOCAL ghcr.io/openclarity/kubeclarity:test run

Local build:

  • Build UI and backend

make ui && make backend

Open KubeClarity UI in the browser: http://localhost:8080/

CLI

KubeClarity includes a CLI that can be run locally and especially useful for CI/CD pipelines. It allows to analyze images and directories to generate SBOM, and scan it for vulnerabilities. The results can be exported to KubeClarity backend.

Binary Distribution

Download the release distribution for your OS from the releases page

Unpack the kubeclarity-cli binary, add it to your PATH, and you are good to go!

Docker Image

A Docker image is available at ghcr.io/openclarity/kubeclarity-cli with list of available tags here.

Local Compilation

make cli

Copy ./cli/bin/cli to your PATH under kubeclarity-cli.

SBOM generation using multiple integrated content analyzers

A list of the content analyzers to use can be configured using the ANALYZER_LIST env variable seperated by a space (e.g ANALYZER_LIST=”syft gomod”)
kubeclarity-cli analyze –input-type -o
For example:
ANALYZER_LIST=”syft” kubeclarity-cli analyze nginx:latest -o nginx.sbom

Vulnerability scanning using multiple integrated scanners

A list of the vulnerability scanners to use can be configured using the SCANNERS_LIST env variable seperated by a space (e.g SCANNERS_LIST=”grype dependency-track”)
kubeclarity-cli scan –input-type -f
For example:
SCANNERS_LIST=”grype” kubeclarity-cli scan nginx.sbom –input-type sbom

Private registries support for K8s runtime scan

Amazon ECR

Create an AWS IAM user with AmazonEC2ContainerRegistryFullAccess permissions.

Use the user credentials (AWS_ACCESS_KEY_IDAWS_SECRET_ACCESS_KEYAWS_DEFAULT_REGION) to create the following secret:

cat <<EOF | kubectl apply -f –
apiVersion: v1
kind: Secret
metadata:
name: ecr-sa
namespace: kubeclarity
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_IDAWS_SECRET_ACCESS_KEY and AWS_DEFAULT_REGION

Google GCR

Create a Google service account with Artifact Registry Reader permissions.

Use the service account json file to create the following secret

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

Note:

  • Secret name must be gcr-sa
  • sa.json must be the name of the service account json file when generating the secret
  • KubeClarity is using application default credentials. These only work when running KubeClarity from GCP.

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