Device For Detection And Administration Of Software program Invoice Of Supplies (SBOM) And Vulnerabilities Of Container Pictures And Filesystems




KubeClarity is a instrument for detection and administration of Software program Invoice Of Supplies (SBOM) and vulnerabilities of container photographs and filesystems. It scans each runtime K8s clusters and CI/CD pipelines for enhanced software program provide chain safety.

  • Efficient vulnerability scanning requires an correct Software program Invoice Of Supplies (SBOM) detection:
    • Numerous programming languages and package deal managers
    • Numerous OS distributions
    • Package deal dependency data is normally stripped upon construct
  • Which one is the very best scanner/SBOM analyzer?
  • What ought to we scan: Git repos, builds, container photographs or runtime?
  • Every scanner/analyzer has its personal format – examine the outcomes?
  • Learn how to handle the found SBOM and vulnerabilities?
  • How are my functions affected by a newly found vulnerability?

Resolution

  • Separate vulnerability scanning into 2 phases:
    • Content material evaluation to generate SBOM
    • Scan the SBOM for vulnerabilities
  • Create a pluggable infrastructure to:
  • Scan and merge outcomes between completely different CI levels utilizing KubeClarity CLI
  • Runtime K8s scan to detect vulnerabilities found post-deployment
  • Group scanned assets (photographs/directories) underneath outlined functions to navigate the thing tree dependencies (functions, assets, packages, vulnerabilities)

Options

  • Dashboard
    • Fixable vulnerabilities per severity
    • Prime 5 susceptible parts (functions, assets, packages)
    • New vulnerabilities tendencies
    • Package deal depend per license kind
    • Package deal depend per programming language
    • Common counters
  • Purposes
    • Computerized software detection in K8s runtime
    • Create/edit/delete functions
    • Per software, navigation to associated:
      • Sources (photographs/directories)
      • Packages
      • Vulnerabilities
      • Licenses in use by the assets
  • Software Sources (photographs/directories)
    • Per useful resource, navigation to associated:
      • Purposes
      • Packages
      • Vulnerabilities
  • Packages
    • Per package deal, navigation to associated:
      • Purposes
      • Linkable record of assets and the detecting SBOM analyzers
      • Vulnerabilities
  • Vulnerabilities
    • Per vulnerability, navigation to associated:
      • Purposes
      • Sources
      • Listing of detecting scanners
  • K8s Runtime scan
    • Computerized detection of goal namespaces
    • Scan progress and outcome navigation per affected factor (functions, assets, packages, vulnerabilities)
  • CLI (CI/CD)
    • SBOM technology utilizing a number of built-in content material analyzers (Syft, cyclonedx-gomod)
    • SBOM/picture/listing vulnerability scanning utilizing a number of built-in scanners (Grype, Dependency-track)
    • Merging of SBOM and vulnerabilities throughout completely different CI/CD levels
    • Export outcomes to KubeClarity backend
  • API
    • The API for KubeClarity may be discovered here

Excessive stage structure

Getting began

Integration with SBOM mills and vulnerability scanners

KubeClarity content material analyzer integrates with the next SBOM mills:

KubeClarity vulnerability scanner integrates with the next scanners:

The integrations with the SBOM mills may be discovered here, and the integrations with the vulnerability scanners may be discovered right here here. To allow and configure the supported SBOM mills and vulnerability scanners, please verify the “analyzer” and “scanner” config underneath the “vulnerability-scanner” part in Helm values.

Contributions of integrations with extra instruments are greater than welcome!

Set up KubeClarity in a K8s cluster utilizing Helm:

  1. Add Helm repo

    helm repo add kubeclarity https://openclarity.github.io/kubeclarity
  2. Save KubeClarity default chart values

    helm present values kubeclarity/kubeclarity > values.yaml
  3. Examine the configuration in values.yaml and replace the required values if wanted

  4. Deploy KubeClarity with Helm

    helm set up --values values.yaml --create-namespace kubeclarity kubeclarity/kubeclarity -n kubeclarity

    or for OpenShift Restricted SCC suitable set up:

    helm set up --values values.yaml --create-namespace kubeclarity kubeclarity/kubeclarity -n kubeclarity --set international.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
  5. Port ahead to KubeClarity UI:

    kubectl port-forward -n kubeclarity svc/kubeclarity-kubeclarity 9999:8080
  6. Open KubeClarity UI within the browser: http://localhost:9999/

Required K8s permissions

  1. Learn secrets and techniques in cluster scope. That is required for getting picture pull secrets and techniques for scanning non-public picture repositories.
  2. Learn config maps in cluster scope. That is required for getting the configured template of the scanner job.
  3. Listing pods in cluster scope. That is required for calculating the goal pods that should be scanned.
  4. Listing namespaces. That is required for fetching the goal namespaces to scan in K8s runtime scan UI.
  5. Create & delete jobs in cluster scope. That is required for managing the roles that can scan the goal pods of their namespaces.

Construct and run domestically with demo knowledge

  1. Construct UI & backend and begin the backend domestically (2 choices):

    1. Utilizing docker:
      1. Construct UI and backend (the picture tag is ready utilizing VERSION):
        VERSION=check make docker-backend
      2. Run the backend utilizing demo knowledge:
        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:check run
    2. Native construct:
      1. Construct UI and backend
      2. Copy the constructed web site:
      3. Run the backend domestically utilizing demo knowledge:
        FAKE_RUNTIME_SCANNER=true DATABASE_DRIVER=LOCAL FAKE_DATA=true ENABLE_DB_INFO_LOGS=true ./backend/bin/backend run
  2. Open KubeClarity UI within the browser: http://localhost:8080/

CLI

KubeClarity features a CLI that may be run domestically and particularly helpful for CI/CD pipelines. It permits to research photographs and directories to generate SBOM, and scan it for vulnerabilities. The outcomes may be exported to KubeClarity backend.

Binary Distribution

Obtain the discharge distribution in your OS from the releases page

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

Docker Picture

A Docker picture is obtainable at ghcr.io/openclarity/kubeclarity-cli with record of out there tags here.

Native Compilation

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

SBOM technology utilizing a number of built-in content material analyzers

# An inventory of the content material analyzers to make use of may be configured utilizing the ANALYZER_LIST env variable seperated by an area (e.g ANALYZER_LIST="syft gomod")  kubeclarity-cli analyze <picture/listing identify> --input-type <dir|file|picture(default)> -o <output file or stdout>    # For instance:  ANALYZER_LIST="syft" kubeclarity-cli analyze nginx:newest -o nginx.sbom  

Vulnerability scanning utilizing a number of built-in scanners

# An inventory of the vulnerability scanners to make use of may be configured utilizing the SCANNERS_LIST env variable seperated by an area (e.g SCANNERS_LIST="grype dependency-track")  kubeclarity-cli scan <picture/sbom/directoty/file identify> --input-type <sbom|dir|file|picture(default)> -f <output file>    # For instance:  SCANNERS_LIST="grype" kubeclarity-cli scan nginx.sbom --input-type sbom   

Export outcomes to KubeClarity backend

To export CLI outcomes to the KubeClarity backend, want to make use of an software ID as outlined by the KubeClarity backend. The appliance ID may be discovered within the Purposes display within the UI or utilizing the KubeClarity API.

Exporting SBOM:

# The SBOM may be exported to KubeClarity backend by setting the BACKEND_HOST env variable and the -e flag.  # Notice: Till TLS is supported, BACKEND_DISABLE_TLS=true needs to be set.  BACKEND_HOST=<KubeClarity backend deal with> BACKEND_DISABLE_TLS=true kubeclarity-cli analyze <picture> --application-id <software ID> -e -o <SBOM output file>    # For instance:  BACKEND_HOST=localhost:9999 BACKEND_DISABLE_TLS=true kubeclarity-cli analyze nginx:newest --application-id 23452f9c-6e31-5845-bf53-6566b81a2906 -e -o nginx.sbom  

Exporting vulnerability scan outcomes:

# The vulnerability scan outcome may be exported to KubeClarity backend by setting the BACKEND_HOST env variable and the -e flag.  # Notice: Till TLS is supported, BACKEND_DISABLE_TLS=true needs to be set.    BACKEND_HOST=<KubeClarity backend deal with> BACKEND_DISABLE_TLS=true kubeclarity-cli scan <picture> --application-id <software ID> -e    # For instance:  SCANNERS_LIST="grype" BACKEND_HOST=localhost:9999 BACKEND_DISABLE_TLS=true kubeclarity-cli scan nginx.sbom --input-type sbom  --application-id 23452f9c-6e31-5845-bf53-6566b81a2906 -e  

Merging of SBOM and vulnerabilities throughout completely different CI/CD levels

# Further SBOM will likely be berged into the ultimate outcomes when '--merge-sbom' is outlined throughout evaluation. The enter SBOM may be CycloneDX XML or CyclonDX json format.  # For instance:  ANALYZER_LIST="syft" kubeclarity-cli analyze nginx:newest -o nginx.sbom --merge-sbom inputsbom.xml  

Personal registries assist for K8s runtime scan

Amazon ECR

Create an AWS IAM user with AmazonEC2ContainerRegistryFullAccess permissions.

Use the person credentials (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION) to create the next secret:

cat <<EOF | kubectl apply -f -  apiVersion: v1  type: Secret  metadata:    identify: ecr-sa    namespace: kubeclarity  kind: Opaque  knowledge:    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  

Notice:

  1. Secret identify have to be ecr-sa
  2. Secret knowledge keys have to be set to AWS_ACCESS_KEY_ID, AWS_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 next secret

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

Notice:

  1. Secret identify have to be gcr-sa
  2. sa.json have to be the identify of the service account json file when producing the key
  3. KubeClarity is utilizing application default credentials. These solely work when working KubeClarity from GCP.

Limitations

  1. Helps Docker Picture Manifest V2, Schema 2 (https://docs.docker.com/registry/spec/manifest-v2-2/). It’ll fail to scan earlier variations.

Roadmap

  • Integration with extra content material analyzers (SBOM mills)
  • Integration with extra vulnerability scanners
  • CIS Docker benchmark in UI
  • Picture signing utilizing Cosign
  • CI/CD metadata signing and attestation utilizing Cosign and in-toto (provide chain safety)
  • System settings and person administration

Contributing

Pull requests and bug reviews are welcome.

For bigger modifications please create an Concern in GitHub first to debate your proposed modifications and attainable implications.

License

Apache License, Version 2.0



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