A company receives daily CSV files in S3 that contain customer interaction data used to retrain a model. Before retraining, credit card numbers in those files must be masked. Which solution accomplishes this with the least development effort?

The correct answer leverages AWS Glue's Sensitive Data Detection, which offers pre-built transformations to identify and mask sensitive data like credit card numbers with minimal development effort. Running this within an AWS Glue job is efficient for processing daily CSV files in S3. Creating a discovery job in Amazon Macie is incorrect because Macie is primarily for discovering and reporting sensitive data, not for directly masking it in a way that modifies the source files for downstream processing. While programming custom regex in an AWS Glue job or on an EC2 instance could work, it requires significant development effort to create and maintain accurate regex patterns for various credit card formats, making it less efficient than Glue's built-in functionality. Running on an EC2 instance also adds infrastructure management overhead compared to a fully managed Glue job.