A company stores tabular data in multiple S3 buckets. They received an alert that customer credit card data may have been exposed in a data table on a public application. A developer needs to find all possible exposures in the application environment. Which solution will identify these exposures?

Amazon Macie is a data security service that uses machine learning and pattern matching to discover, classify, and protect sensitive data in Amazon S3. It is specifically designed to identify personally identifiable information (PII) and other sensitive data, such as financial information. Running a Macie job on the S3 buckets and filtering by SensitiveData:S3Object/Financial will pinpoint credit card data exposures. Amazon Athena is an interactive query service for S3 data. While it can query data in S3, it does not inherently have the capability to classify or identify sensitive data types like credit card numbers without extensive, custom SQL queries and regular expressions, which would be less efficient and reliable than Macie. The finding types mentioned (SensitiveData:S3Object/Personal or SensitiveData:S3Object/Financial) are Macie-specific classifications, not Athena query filters. SensitiveData:S3Object/Personal would identify general PII, but SensitiveData:S3Object/Financial is more precise for credit card data.