reCAPTCHA v3 implementation with fraud status dashboard

[luiggilamela]

Hi community,

I’m looking to implement Google reCAPTCHA v3 in a production system, and I’d like to know if there is any official or community-recommended documentation that includes:

A step-by-step guide for a complete reCAPTCHA v3 integration (frontend + backend)

Guidance on how to log and visualize request statuses (e.g., accepted, rejected, or flagged as fraud)

Examples or recommendations for building a dashboard that allows my clients/users to view the status of their own requests, including:

• Successful submissions
• Rejected attempts (due to low scores)
• Suspected fraud or bot interactions

What I’ve already tried:
I’ve reviewed the official documentation, but it mostly focuses on the integration and scoring mechanism.

I’ve successfully set up the token generation and validation parts using my own backend.

Problems:
There’s no clear documentation (that I’ve found) on logging the score evaluations, nor how to associate requests to specific users to later show them via a dashboard.

I’m unsure if Google’s Admin Console exposes this kind of per-user data, or if I need to handle all the logic and storage myself.

If anyone has done something similar, or if there's a boilerplate, open-source example, or architecture recommendation to achieve this, I’d greatly appreciate your guidance.

Thanks in advance!

[Joy_S]

Hi @luiggilamela,

Welcome to Google Cloud Community!

Based on your initial description, your current setup likely has some limitations that prevent you from achieving this advanced monitoring. The default Google reCAPTCHA Admin Console gives you a general overview of traffic and score trends, but it doesn’t show detailed info for each user or request. So, if you want a dashboard that tracks things like individual request results per user, you’ll need to set that up separately. Also, the default Google reCAPTCHA Admin Console gives you a general overview of traffic and score trends, but it doesn’t show detailed info for each user or request. So, if you want a dashboard that tracks things like individual request results per user, you’ll need to set that up separately.

To get around these limitations and build the kind of monitoring and dashboard you need, here are some steps you can follow:

1. Turn on Platform Logs in Google Cloud:
   To capture detailed scores from reCAPTCHA v3, make sure Platform Logs are enabled for the reCAPTCHA Enterprise v1 API in Google Cloud Logging.
2. Send Logs to BigQuery:
   For easier analysis and to handle large amounts of log data, export the logs to a partitioned BigQuery dataset. This makes it much more efficient to query and use in a dashboard later.
3. Update Your Backend Logic:
   You'll need to tweak your backend to:
   • Accept the reCAPTCHA token from your frontend.
   • Verify the token using the reCAPTCHA API to get the score.
   • Save that score, the timestamp, and a user ID in your database so you can track who did what.
     
     

4. Create a Custom Dashboard in Looker Studio:
   Use Google Looker Studio to build an interactive dashboard based on your BigQuery logs. It’s great for visualizing things like pass/fail rates or suspicious activity. You can even check if there’s a pre-made reCAPTCHA dashboard template to save time.
5. Add Score-Based Decision Logic:
    In your backend, set parameters based on reCAPTCHA scores—like passing high scores, flagging medium ones for review or MFA, and blocking low scores. You can store this request status with each score in your database.
6. Keep an Eye on Trends:
   Regularly review your score data in both the Google Cloud console and your dashboard. This helps you fine-tune your thresholds to keep bots out without frustrating real users.
7. Stay Secure and Compliant:
   Make sure your database is locked down and access to your dashboards is restricted. And if you're dealing with user data, follow privacy rules like GDPR or CCPA.
8. Use reCAPTCHA "Actions":
    When setting up reCAPTCHA v3 on the frontend, use named actions in grecaptcha.execute. This gives more context to the system and improves the quality of the analysis in your dashboards and in Google Cloud.

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