A security engineer uses Amazon Macie to scan a company ' s Amazon S3 buckets...

Amazon Macie’sautomated sensitive data discoveryis designed for exactly this: at scale, Macie continuously evaluates andsamplesobjects across S3 buckets to identify where sensitive data (PII, financial data, credentials, etc.) is likely present. This gives the security engineer a low-touch way toidentify which buckets contain sensitive datawithout having to orchestrate per-bucket scanning workflows. Once Macie flags buckets with sensitive data findings, the engineer can then prioritize and runadditional, more targeted scanning(for example, deeper classification jobs on those specific buckets) rather than scanning everything exhaustively all the time.

The other options increase operational burden significantly. CRR to another Region (A) doubles storage/transfer complexity and is not needed for discovery. An event-driven Lambda scan per object (B) is expensive and complex at high object volumes and is not how Macie classification is intended to be orchestrated. Aggregating results into DynamoDB (D) adds an extra system to maintain when Macie already provides centralized findings, dashboards, and integrations.

Therefore, enabling Macie automated discovery and then performing deeper scans only on buckets where Macie detects sensitive data provides the least administrative overhead.