Amazon Macie uses machine learning to do its work and helps you discover and analyze sensitive data stored in Amazon S3 buckets, including personal identifiable information, or PII, such as names, addresses, credit card numbers, API Keys, and access credentials among many others. Macie scans S3 buckets and recognizes critical private information. It also automatically tracks changes to buckets and only evaluates new or modified objects in future scans. That way, it doesn't have to review objects that have not changed and makes the discovery job significantly more efficient and scalable. You can run one-time or automated data discovery and display the results to AWS Security Hub.

Amazon Macie provides a list of findings where the severity and finding type are clearly displayed. In this case, we created a bucket called academy-ca-macie and uploaded a file with disabled user keys, an RDS SQL Query, a credit card list in CSV format, and a few other files. Notice the severity as medium or high. Also, notice the finding type for the S3 objects include Personal, Financial, and Credentials. It also points to the resource that is affected. Finally, it shows when the object was last scanned. In the future, unless there is a change, these objects will not be re-evaluated.