gke-metadata-server

README

gke-metadata-server

A GKE Metadata Server emulator for making it easier to use GCP Workload Identity Federation inside non-GKE Kubernetes clusters, e.g. KinD, on-prem, managed Kubernetes from other clouds, etc. This implementation tries to mimic the gke-metadata-server DaemonSet deployed automatically by Google in the kube-system namespace of GKE clusters that have the feature Workload Identity Federation for GKE enabled. See how the GKE Metadata Server works.

Usage

Steps:

1. Install cert-manager in the cluster. This dependency is used for bootstrapping self-signed CA and TLS certificates for a MutatingWebhook that adds the required networking configuration to the user Pods.
2. Configure GCP Workload Identity Federation for Kubernetes.
3. Deploy gke-metadata-server in the cluster using the Workload Identity Provider full name, obtained after step 2.
4. See ./k8s/test-pod.yaml for an example of how to configure your Pods and their ServiceAccounts.
5. (Optional but highly recommended) Verify gke-metadata-server's artifact signatures to make sure you are deploying authentic artifacts distributed by this project.

If you don't want to depend on cert-manager and want to deploy the MutatingWebhook in a different way, the Helm Chart or Timoni Module offered here is not for you (but please feel free to copy and modify).

Configure GCP Workload Identity Federation for Kubernetes

Steps:

1. Create a Workload Identity Pool and Provider pair for the cluster.
2. Grant Kubernetes ServiceAccounts permission to impersonate Google Service Accounts.

Official docs and examples are here.

More examples for all the configuration described in this section are available here: ./terraform/test.tf. This is where we provision the infrastructure required for testing this project in CI and development.

Create a Workload Identity Pool and Provider pair for the cluster

Before granting ServiceAccounts of a Kubernetes cluster permission to impersonate Google Service Accounts, a Workload Identity Pool and Provider pair must be created for the cluster in Google Cloud Platform.

A Pool is a namespace for Subjects and Providers, where Subjects represent the identities to whom permission to impersonate Google Service Accounts are granted, i.e. the Kubernetes ServiceAccounts in this case.

A Provider stores the OpenID Connect configuration parameters retrieved from the cluster for allowing Google to verify ServiceAccount Tokens issued by the cluster. Specifically for the creation of a Provider, see an example in the ./Makefile, target create-or-update-provider.

The ServiceAccount Tokens issued by Kubernetes are JWT tokens. Each such token is exchanged for an OAuth 2.0 Access Token that impersonates a Google Service Account. During a token exchange, the Subject is mapped from the sub claim of the JWT (achieved in the Makefile example by --attribute-mapping=google.subject=assertion.sub). In this case the Subject has the following format:

system:serviceaccount:{k8s_namespace}:{k8s_sa_name}

The Subject total length cannot exceed 127 characters (docs).

Attention 1: If you update the private keys of the ServiceAccount Issuer of the cluster you must update the Provider with the new OpenID Connect configuration, otherwise service will be disrupted.

Attention 2: Please make sure not to specify any audiences when creating the Provider. The emulator uses the default audience when issuing the ServiceAccount Tokens. The default audience contains the full name of the Provider, which is a strong restriction:

//iam.googleapis.com/{provider_full_name}

where {provider_full_name} has the form:

{pool_full_name}/providers/{provider_short_name}

and {pool_full_name} has the form:

projects/{gcp_project_number}/locations/global/workloadIdentityPools/{pool_short_name}

Grant Kubernetes ServiceAccounts permission to impersonate Google Service Accounts

For allowing the Kubernetes ServiceAccount {k8s_sa_name} from the namespace {k8s_namespace} to impersonate the Google Service Account {gcp_service_account}@{gcp_project_id}.iam.gserviceaccount.com, grant the IAM Role roles/iam.workloadIdentityUser on this Service Account to the following principal:

principal://iam.googleapis.com/{pool_full_name}/subject/system:serviceaccount:{k8s_namespace}:{k8s_sa_name}

This principal will be reflected as a Subject in the Google Cloud Console webpage of the Pool.

If you plan to use the GET /computeMetadata/v1/instance/service-accounts/default/identity API for issuing Google OpenID Connect Identity Tokens to use in external systems, you must also grant the IAM Role roles/iam.serviceAccountOpenIdTokenCreator on the Google Service Account to the Google Service Account itself, i.e. the following principal:

serviceAccount:{gcp_service_account}@{gcp_project_id}.iam.gserviceaccount.com

This "self-impersonation" permission is necessary because the gke-metadata-server emulator retrieves the Google OpenID Connect Identity Token in a 2-step process: first it retrieves the Google Service Account OAuth 2.0 Access Token using the Kubernetes ServiceAccount Token, and then it retrieves the Google OpenID Connect Token using the Google Service Account OAuth 2.0 Access Token.

Alternatively, grant direct resource access to the Kubernetes ServiceAccount

Workload Identity Federation for Kubernetes allows you to directly grant Kubernetes ServiceAccounts access to Google resources, without the need to impersonate a Google Service Account. This is done by granting the given IAM Roles directly to principals of the form described above for impersonation. See docs.

Some specific GCP services do not support this method. See docs.

The GET /computeMetadata/v1/instance/service-accounts/default/identity API is not supported by this method. If you plan to use this API, you must use the impersonation method described above.

Deploy gke-metadata-server in your cluster

Using the Helm Chart

A Helm Chart is available in the following Helm OCI Repository:

ghcr.io/matheuscscp/gke-metadata-server-helm:{helm_version} (GitHub Container Registry)

Here {helm_version} is a Helm Chart version, i.e. the field .helm in the file ./versions.yaml. Check available releases in the GitHub Releases Page.

See the Helm Values API in the file ./helm/gke-metadata-server/values.yaml. Make sure to specify at least the full name of the Workload Identity Provider.

Using the Timoni Module

If you prefer something newer and strongly typed, a Timoni Module is available in the following Timoni OCI Repository:

ghcr.io/matheuscscp/gke-metadata-server-timoni:{timoni_version} (GitHub Container Registry)

Here {timoni_version} is a Timoni Module version, i.e. the field .timoni in the file ./versions.yaml. Check available releases in the GitHub Releases Page.

See the Timoni Values API in the files ./timoni/gke-metadata-server/templates/config.tpl.cue and ./timoni/gke-metadata-server/templates/settings.cue. Make sure to specify at least the full name of the Workload Identity Provider.

Using only the container image (with your own Kubernetes manifests)

Alternatively, you can write your own Kubernetes manifests and consume only the container image:

ghcr.io/matheuscscp/gke-metadata-server:{container_version} (GitHub Container Registry)

Here {container_version} is an app container version, i.e. the field .container in the file ./versions.yaml. Check available releases in the GitHub Releases Page.

Verify the image signatures

For verifying the images above use the cosign CLI tool.

Verify the container image

For verifying the image of a given Container GitHub Release (tags v{container_version}), download the digest file container-digest.txt attached to the Github Release and use it with cosign:

cosign verify ghcr.io/matheuscscp/gke-metadata-server@$(cat container-digest.txt) \
  --certificate-oidc-issuer=https://token.actions.githubusercontent.com \
  --certificate-identity=https://github.com/matheuscscp/gke-metadata-server/.github/workflows/release.yml@refs/heads/main

Automatic verification

If you are using Sigstore's Policy Controller for enforcing policies you can automate the image verification using Keyless Authorities.

If you are using Kyverno for enforcing policies you can automate the image verification using Keyless Verification.

Verify the Helm Chart image

For verifying the image of a given Helm Chart GitHub Release (tags helm-v{helm_version}), download the digest file helm-digest.txt attached to the Github Release and use it with cosign:

cosign verify ghcr.io/matheuscscp/gke-metadata-server-helm@$(cat helm-digest.txt) \
  --certificate-oidc-issuer=https://token.actions.githubusercontent.com \
  --certificate-identity=https://github.com/matheuscscp/gke-metadata-server/.github/workflows/release.yml@refs/heads/main

Automatic verification

If you are using Flux for deploying Helm Charts you can automate the image verification using Keyless Verification.

Verify the Timoni Module image

For verifying the image of a given Timoni Module GitHub Release (tags timoni-v{timoni_version}), download the digest file timoni-digest.txt attached to the Github Release and use it with cosign:

cosign verify ghcr.io/matheuscscp/gke-metadata-server-timoni@$(cat timoni-digest.txt) \
  --certificate-oidc-issuer=https://token.actions.githubusercontent.com \
  --certificate-identity=https://github.com/matheuscscp/gke-metadata-server/.github/workflows/release.yml@refs/heads/main

Automatic verification

If you are using the Timoni CLI to deploy Modules/Bundles you can automate the image verification using Keyless Verification. (Timoni will have a Flux controller in the future.)

Security Risks and Limitations

Pod identification by IP address

The server uses the client IP address reported in the HTTP request to identify the requesting Pod in the Kubernetes API (just like in the native GKE implementation).

If an attacker can easily perform IP address impersonation attacks in your cluster, e.g. ARP spoofing, then they will most likely exploit this design choice to steal your credentials. Please evaluate the risk of such attacks in your cluster before choosing this tool.

(Please also note that the attack explained in the link above requires Pods configured with very high privileges, which should normally not be allowed in sensitive/production clusters. If the security of your cluster is really important, then you should be enforcing restrictions for preventing Pods from being created with such high privileges in the majority of cases.)

Pods running on the host network

In a cluster there may also be Pods running on the host network, i.e. Pods with the field spec.hostNetwork set to true. Such Pods do not fork a new network namespace, i.e. they share the network namespace of the Kubernetes Node where they are running on.

The emulator Pods themselves, for example, need to run on the host network in order to listen to TCP/IP connections coming from Pods running on the same Kubernetes Node, which are the ones this emulator Pod will serve. Just like in the GKE implementation, this design choice makes it such that the (unencrypted) communication between the emulator and a client Pod never leaves the Node.

Because Pods running on the host network use a shared IP address, i.e. the IP address of the Node itself where they are running on, they cannot be uniquely identified by the server using the client IP address reported in the HTTP request. This is a limitation of the Kubernetes API, which does not provide a way to identify Pods running on the host network by IP address.

To work around this limitation, Pods running on the host network are allowed to use a shared Kubernetes ServiceAccount associated with the Node where they are running on. This ServiceAccount can be configured in the annotations or labels of the Node, and it defaults to the ServiceAccount of the emulator (or to a ServiceAccount specified in the emulator CLI flags if not using the official Helm Chart or Timoni Module distributed here). The syntax is:

annotations: # or labels
  gke-metadata-server.matheuscscp.io/serviceAccountName: <k8s_sa_name>
  gke-metadata-server.matheuscscp.io/serviceAccountNamespace: <k8s_namespace>

Prefer using annotations since they are less impactful than labels to the cluster. Unfortunately, as of July 2024, most cloud providers support customizing only labels in node pool templates, and some don't even support this kind of customization at all. It's up to you how you annotate/label your Nodes.

You may also simply assign a Google Service Account to the Kubernetes ServiceAccount of the emulator and use it for all the Pods of the cluster that are running on the host network. This can be done through the Helm Chart value config.defaultNodeServiceAccount, or the Timoni Module value values.settings.defaultNodeServiceAccount.

Be careful and try to avoid using shared identities! This is obviously dangerous!

The iptables rules

Attention: The iptables rules installed in the network namespace of mutated Pods will redirect outbound traffic targeting 169.254.169.254:80 to the emulator port on the Node. If you are using similar tools or equivalent workload identity features of managed Kubernetes from other clouds, this configuration may have a direct conflict with other such tools or features. It's a common practice among cloud providers using this endpoint to implement such features. Especially when mutating Pods that will run on the host network, the rules will be installed on the network namespace of the Node! Please be sure to know what you are doing when using this tool inside complex environments.

Token Cache

When the emulator is configured to cache tokens, the issued Google OAuth 2.0 Access and OpenID Connect Identity Tokens are cached and returned to client Pods on every request until their expiration.

This means that even if you revoke the required permissions for the Kubernetes ServiceAccount to issue those tokens, the client Pods will still get those tokens from the emulator until they expire. This is a limitation of how the permissions are evaluated: they are evaluated only when the tokens are issued, which is what caching tries to avoid. If your use case requires immediate revocation of permissions, then you should not use token caching.

Tokens usually expire in 1 hour.

Disclaimer

This project was not created by Google. Enterprise support from Google is not available. Use this tool at your own risk. (But please do feel free to report bugs and CVEs, request help, new features and contribute.)

Furthermore, this tool is not necessary for using GCP Workload Identity Federation inside non-GKE Kubernetes clusters. This is just a facilitator. Kubernetes and GCP Workload Identity Federation work together by themselves. This tool just makes your Pods need much less configuration to use GCP Workload Identity Federation for Kubernetes, by making the configuration as close as possible to how Workload Identity Federation for GKE is configured.