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gke-metadata-server

release release

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. Configure GCP Workload Identity Federation for Kubernetes.
  2. Deploy gke-metadata-server in the cluster using the Workload Identity Provider full name, obtained after step 1.
  3. Add the label iam.gke.io/gke-metadata-server-enabled: "true" to the Nodes you want to have the emulator Pods running on. Only Pods running on these Nodes will be able to use the emulator. The most recommended way to do this is by using Node pooling/grouping features from your Kubernetes provider.
  4. See ./testdata/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.

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 emulator uses the client IP address reported in the HTTP request to uniquely 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 share the IP address of the Node where they are running on, i.e their IP is not unique, and therefore they cannot be uniquely identified by the emulator through the client IP address reported in the HTTP request (like mentioned in the previous section).

If your use case requires, Pods running on the host network are allowed to use a shared Kubernetes ServiceAccount configured through annotations/labels on the Node:

gke-metadata-server.matheuscscp.io/hostNetworkServiceAccountName: <k8s service account name>
gke-metadata-server.matheuscscp.io/hostNetworkServiceAccountNamespace: <k8s service account namespace>

Annotations are preferred over labels because they are less impactful to etcd since they are not indexed. Labels are also supported because not all Kubernetes providers support configuring annotations on Node pools/groups. KinD, for example, does not (see testdata/kind.yaml).

Remember to add appropriate Node selectors/tolerations to your Pods so they are scheduled on the Nodes where the shared ServiceAccount is configured. There are many different ways to achieve this depending on your use case, so please refer to the Kubernetes documentation for more information.

Be careful when sharing identities between too many workloads! Please assess your security requirements and the risks of sharing identities between workloads in your cluster.

eBPF magic 🐝

Attention: The emulator Pod installs an eBPF hook in the kernel of the Node it runs on. This hook modifies the input to connect() syscalls to target the emulator address when the original destination is 169.254.169.254:80. This is the address hard-coded inside the Google libraries for fetching the temporary tokens for apps. This is how traffic from the client Pods reaches the emulator, and is also how we ensure the unencrypted communication between the emulator and a client Pod to never leave the Node they are both running on. In other words, an emulator Pod only serves a client Pod if they are both running on the same Node. GKE has this same guarantee.

If you are using similar tools or workload identity features of managed Kubernetes services from other clouds, this configuration may have a direct conflict with other such tools or features. It's a recurrent practice among cloud providers using this hard-coded IP address and port to implement workload identity. If your use case requires, the recommended solution is to use Node pooling/grouping features from your Kubernetes provider to isolate the workloads that need to use the emulator as mentioned in the Usage section (remember to add the label iam.gke.io/gke-metadata-server-enabled: "true" to such Nodes and appropriate Node selectors/tolerations to your Pods).

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 at most one 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.