Recently, while managing a Google Cloud Platform (GCP) deployment, I ran into an issue where a service account was failing with a cryptic 403 permissionDenied error when trying to access a Google Cloud Storage bucket. At first, the problem seemed like a simple missing permission, but the root cause turned out to be a subtle configuration issue involving IAM role chaining and indirect permissions. The experience highlighted the importance of fully understanding how IAM roles are inherited and granted, especially when you’re relying heavily on automation or job orchestration.
TL;DR
A GCP service account was returning 403 permissionDenied errors when trying to read from a Cloud Storage bucket. Although it had what appeared to be the correct permissions, the actual problem stemmed from missing transitive role grants in an IAM trust chain. By correctly assigning roles and ensuring the service account had permission to act-as other roles in its process, we were able to restore functionality. This issue illustrates the deeper complexities of GCP IAM and the need to trace permission paths carefully.
Understanding the Problem
The issue occurred in a relatively well-structured GCP environment. A Dataflow job, run by a service account we’ll call dataflow-sa@project-id.iam.gserviceaccount.com, was responsible for reading files from a Cloud Storage bucket and streaming them to BigQuery. Everything had been working flawlessly for months — until suddenly, new jobs started to fail with this error:
Error: permissionDenied - 403 The caller does not have permission
This error was surfaced in the logs of Dataflow jobs that previously ran without issue. Our initial instinct was that the Cloud Storage bucket’s permissions must have changed, but upon inspection, the bucket still had the correct IAM bindings, and the service account was a listed member of the roles/storage.objectViewer role.
Quick Checklist
When debugging IAM issues in GCP, it’s worth checking all the basics first. Here’s a list of what we reviewed:
- Does the service account exist and have no key or lifecycle issues?
- Is the service account explicitly assigned to the correct roles on the bucket?
- Did any VPC policies or organization-level restrictions block storage access?
- Are Conditional Role Bindings interfering with the expected default behavior?
All of these checked out, but the error persisted — cue the deep dive.
Diving Deeper: The Problem of Grant Chaining
After combing through IAM policies and logs, an overlooked detail came to light. The role was assigned—but not directly to the service account running the job. Instead, it was granted to a different identity via a cross-project setup that involved:
- A user account (used in initial testing)
- An intermediate service account with “impersonate” rights
- The Dataflow service account which actually ran the job
This pattern led to a situation where only the user account had roles/iam.serviceAccountTokenCreator permission to impersonate the intermediate service account, and the intermediate service account had the actual permissions to access the storage bucket. The job broke because the final service account lacked those same token creation permissions.
What is IAM Role Chaining or Trust Delegation?
IAM Role Chaining refers to the common GCP pattern where one identity grants another identity permission to “act as” it, typically using the roles/iam.serviceAccountUser or roles/iam.serviceAccountTokenCreator. This pattern is especially common in CI/CD pipelines, automated scripts, and service hand-offs between different parts of infrastructure.
When you set up trust delegation wrong, it breaks the call chain, and your service might be technically “authenticated,” but not “authorized” to act with the required context or role privileges. The Grant Chain was missing a crucial link: the Dataflow service account couldn’t legitimately assume the identity that actually had storage.objectViewer.
Restoring Functionality
Here are the steps I took to fix the issue:
- Verified the Intended Identity Flow: I mapped out exactly which identities were expected to call which resources. This included diagrams (mental and on-paper) to represent the access delegation flow.
- Adjusted IAM Bindings: I granted the Dataflow service account the
roles/iam.serviceAccountUserandroles/iam.serviceAccountTokenCreatorpermissions on the intermediate SA. This allowed legitimate impersonation down the trust chain. - Added Direct Role: For simplicity and to reduce confusion long-term, I ended up attaching the
roles/storage.objectViewerrole directly to the job-running service account on the bucket, eliminating ambiguity. - Validated with ‘Policy Troubleshooter’: GCP’s built-in IAM Policy Troubleshooter (policytroubleshooter) was invaluable in simulating access pathways.
Once I made these changes, the Dataflow jobs immediately started running correctly again. I also updated IAM documentation in our internal wiki to clarify how service accounts delegated authority across services and environments.
Best Practices Moving Forward
This whole adventure reminded me of the importance of clarity in cloud IAM configurations. Here are some lessons and best practices I took away:
- Minimize Role Chaining if It Isn’t Needed: Where possible, assign the necessary permissions directly to the consuming service account instead of jumping through multiple levels of abstraction.
- Document Every Service Account’s Purpose and Permissions: This helps prevent future confusion if roles change or team members rotate out.
- Use Policy Simulator and Troubleshooter Tools: These can save hours of guesswork by explicitly outlining why access is being denied.
- Audit Roles Regularly: Sometimes roles change unintentionally, especially in dynamic teams or across merging infrastructures.
Conclusion
The cloud, especially platforms like GCP, offers immense flexibility and security—but with that comes complexity. IAM is one of the most powerful but also most frequently misunderstood components. The 403 permissionDenied errors can be frustrating because they often mask the true source of the access denial. In this case, it was all about IAM role chaining and the permissions required to act on behalf of another service account.
By carefully tracing the path of identity and permission, validating role grants, and reducing reliance on implicit chaining, I was able to restore the Dataflow jobs and ensure a more stable environment. Hopefully, by sharing this, you won’t have to unravel the same knot I did!