GCP Workload Identity Federation Explained

In the traditional cloud security model, the standard mechanism for authenticating external workloads to Google Cloud Platform (GCP) was the service account key. These long-lived JSON files were a perpetual source of anxiety for security teams. If leaked, they provided permanent access until manually revoked, often leading to significant data breaches. As organizations adopt multi-cloud and hybrid architectures, the management of these "static secrets" becomes an operational bottleneck and a critical security vulnerability.

GCP Workload Identity Federation (WIF) represents a paradigm shift in how we handle cross-provider authentication. Instead of relying on static credentials, WIF allows you to extend GCP’s native identity management to workloads running outside of Google Cloud—be it on AWS, Azure, GitHub Actions, or on-premises Kubernetes clusters. By establishing a trust relationship between GCP and an external Identity Provider (IdP), you enable workloads to exchange their native identity tokens for short-lived GCP access tokens. This "keyless" approach effectively eliminates the risk associated with credential leakage and simplifies the lifecycle management of service identities.

Architecture

The architecture of Workload Identity Federation centers on three main components: the Workload Identity Pool, the Workload Identity Provider, and the Security Token Service (STS). A Pool is a logical container for managing external identities, while the Provider defines the relationship between GCP and the external IdP (using OIDC or SAML).

In this architecture, GCP acts as the Relying Party. When a workload in AWS needs to access BigQuery, it doesn't use a GCP key. Instead, it uses its AWS IAM identity to request a signed token from AWS. This token is sent to the GCP STS, which validates it against the configured Workload Identity Provider. Once validated, the STS issues a short-lived federated token, which the workload then uses to impersonate a specific GCP Service Account.

Implementation

To implement WIF, you typically use the google-auth library, which supports "Pluggable Auth" via a credential configuration file. This file tells the library how to fetch the external token and where to exchange it.

The following Python example demonstrates how an external workload (e.g., running on an on-premises server with an OIDC provider) can authenticate to GCP to query a BigQuery dataset without using a static JSON key.

from google.cloud import bigquery
from google.auth import credentials
import google.auth

# The configuration file generated by the gcloud CLI 
# (gcloud iam workload-identity-pools create-cred-config)
# This file contains the instructions for the SDK to perform the exchange.
CREDENTIAL_CONFIG_PATH = "/var/run/secrets/gcp/config.json"

def query_bigquery_federated(project_id, dataset_id):
    """Queries BigQuery using Workload Identity Federation."""
    
    # The SDK automatically detects the credential configuration
    # It handles the token exchange with STS and Service Account impersonation
    scoped_credentials, project = google.auth.load_credentials_from_file(
        CREDENTIAL_CONFIG_PATH,
        scopes=["https://www.googleapis.com/auth/cloud-platform"]
    )

    client = bigquery.Client(credentials=scoped_credentials, project=project_id)

    query = f"SELECT * FROM `{project_id}.{dataset_id}.telemetry` LIMIT 10"
    query_job = client.query(query)

    print("Successfully authenticated via WIF. Results:")
    for row in query_job:
        print(row)

if __name__ == "__main__":
    query_bigquery_federated("my-production-project", "iot_data")

This code is "environment-aware." Because the SDK handles the heavy lifting of the STS exchange, the application logic remains identical whether it's running on-premises, on AWS, or natively on GCE.

Service Comparison Table

Data Flow and Token Exchange

The security of WIF relies on a multi-step exchange process that ensures the identity is verified at every stage before access to GCP resources like Spanner or Vertex AI is granted.

This flow ensures that the external workload never possesses a credential that is valid for more than a few minutes. If the external workload is compromised, the attacker only gains access to the short-lived token, significantly reducing the blast radius.

Best Practices

When designing your WIF strategy, the focus should be on narrowing the scope of who can assume which identity. Using the "Attribute Mapping" feature is critical here. You shouldn't just trust "all of AWS"; you should trust a specific AWS Role or a specific GitHub Repository.

1. Attribute Mapping and Conditions: Use Common Expression Language (CEL) to restrict access. For example, only allow a GitHub Action to authenticate if assertion.repository == 'my-org/my-repo' and assertion.ref == 'refs/heads/main'.
2. Service Account Isolation: Do not use a single service account for all federated workloads. Create granular service accounts for specific tasks, such as wif-bq-reader or wif-vertex-deployer.
3. Pool Per Environment: Create separate Workload Identity Pools for development, staging, and production to prevent lateral movement across environments.

Conclusion

Workload Identity Federation is the modern standard for securing multi-cloud and hybrid cloud environments on GCP. By moving away from static service account keys and embracing short-lived, identity-based tokens, organizations can significantly harden their security posture. The ability to map external identity attributes directly to GCP IAM policies allows for a level of granular control that was previously impossible. As Google Cloud continues to integrate WIF across its ecosystem—from BigQuery to the latest Vertex AI models—mastering this "keyless" architecture is no longer optional for cloud architects; it is a fundamental requirement for building resilient and secure cloud-native systems.

References:

• https://cloud.google.com/iam/docs/workload-identity-federation
• https://cloud.google.com/blog/products/identity-security/get-short-lived-credentials-for-external-workloads-via-workload-identity-federation
• https://cloud.google.com/docs/authentication/restricting-identities-within-a-pool