TEST 2

ExpiredTokenException During Rekognition Batch Processing with Temporary Credentials

Category: IAM & Permission Boundaries

Problem

Your application processes images in batches using Amazon Rekognition.

The first several requests succeed.

Then the job fails mid-run with:

bash

ExpiredTokenException: The security token included in the request is expired
  

Rekognition permissions are correct.
IAM policies are valid.
Nothing changed.

Yet the process stops halfway through.
Clarifying the Issue

Your application is using temporary credentials.

These are issued by:

• sts:AssumeRole
• Federated login
• AWS SSO
• IAM Roles for EC2 or Lambda

Temporary credentials include:

• Access key
• Secret key
• Session token
• Expiration timestamp

Once the expiration time is reached, all API calls fail — even if permissions are correct.

Rekognition is not denying access.

The token itself is no longer valid.

Why It Matters

This failure is common in:

• Long-running batch jobs
• Asynchronous processing pipelines
• Containerized workloads
• Local scripts using assumed roles
• CI/CD jobs

If your batch runs longer than the session duration (often 1 hour by default), the credentials expire mid-execution.

The failure appears random.

It isn’t.

This is a credential-lifecycle issue — not a Rekognition issue.

Key Terms

• Temporary Credentials – Short-lived credentials issued by STS.
• Session Duration – The time limit before temporary credentials expire.
• sts:AssumeRole – API used to obtain temporary credentials.
• Session Token – The third credential required for temporary access.

Steps at a Glance

1. Confirm the workload is using temporary credentials.
2. Identify the session expiration timestamp.
3. Check the role’s maximum session duration setting.
4. Determine whether the batch job exceeds session duration.
5. Implement credential refresh logic or extend session duration.
6. Retest with renewed credentials.

Detailed Steps

Step 1: Confirm Credential Type

Check how the application authenticates.

If using:

aws sts assume-role


SSO login


IAM role attached to EC2


Lambda execution role

You are using temporary credentials.

Look for environment variables such as:AWS_SESSION_TOKEN


If present, credentials are temporary.

Step 2: Identify Expiration Timestamp

Temporary credentials include an expiration time.

If obtained via CLI:aws sts assume-role ...


The response includes:"Expiration": "2026-02-25T02:15:43Z"


Compare this timestamp to when the failure occurs.

If they align, the token expired mid-process.

Step 3: Check Maximum Session Duration

In IAM → Roles → Select role → Maximum session duration.

Default is often 1 hour.

It can be extended up to 12 hours (if permitted by policy).

If the role’s maximum duration is 1 hour, tokens cannot exceed that.
Step 4: Compare Job Runtime to Session Duration

Measure:

Total batch runtime


Time between credential acquisition and failure

If the job exceeds the session duration, expiration is guaranteed.

This is common in image-heavy Rekognition workloads.
Step 5: Implement Credential Refresh or Extend Duration

You have three options:

Increase the role’s maximum session duration


Re-assume the role before expiration


Use an IAM role attached to compute (EC2/Lambda) that auto-rotates credentials

Modern SDKs automatically refresh credentials when properly configured.

Custom scripts often do not.
Step 6: Retest with Renewed Credentials

Re-run the batch with:

Fresh credentials


Extended session duration


Or auto-refresh enabled

If the failure disappears, the issue was purely token expiration.
Pro Tips

Always log credential expiration time during batch jobs.


Do not hard-code assumed role credentials for long-running tasks.


Use AWS SDK credential providers that auto-refresh.


Lambda functions have a maximum runtime of 15 minutes. In most cases, a Lambda will timeout before temporary credentials expire. Long-running containers (ECS/Fargate), EC2 batch jobs, and local scripts are far more likely to hit token expiration.


Rare but real: Clock skew can cause premature ExpiredTokenException. If the system time on your server or container is incorrect, AWS may reject otherwise valid credentials. Ensure NTP time synchronization is functioning correctly.


Expired tokens produce immediate failures — not throttling behavior.

If Rekognition fails mid-run without permission changes, suspect token expiration first.
Conclusion

ExpiredTokenException during Rekognition batch processing is not a permissions issue.

It is a temporary credential lifecycle issue.

When using STS or assumed roles, your session has a clock.

If the job runs longer than the session duration, the token expires — and Rekognition stops.

This is a credential-boundary issue — not a Rekognition issue.

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