Using managed data identifiers in Amazon Macie
Amazon Macie uses a combination of criteria and techniques, including machine learning and pattern matching, to detect sensitive data in Amazon Simple Storage Service (Amazon S3) objects. These criteria and techniques, collectively referred to as managed data identifiers, can detect a large and growing list of sensitive data types for many countries and regions, including multiple types of credentials data, financial information, personal health information (PHI), and personally identifiable information (PII). Each managed data identifier is designed to detect a specific type of sensitive data—for example, AWS secret access keys, credit card numbers, or passport numbers for a particular country or region.
Macie can detect the following categories of sensitive data by using managed data identifiers:
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Credentials, for credentials data such as private keys and AWS secret access keys.
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Financial information, for financial data such as credit card numbers and bank account numbers.
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Personal information, for PHI such as health insurance and medical identification numbers, and PII such as driver's license identification numbers and passport numbers.
Within each category, Macie can detect multiple types of sensitive data. The topics in this section list and describe each type and any relevant requirements for detecting it. For each type, they also indicate the unique identifier (ID) for the managed data identifier that's designed to detect the data. When you create a sensitive data discovery job or configure automated sensitive data discovery settings, you can use these IDs to specify which managed data identifiers you want Macie to use when it analyzes S3 objects.
For a list of managed data identifiers that we recommend for jobs, see Managed data identifiers recommended for sensitive data discovery jobs. For a list of managed data identifiers that we recommend and are used by default for automated sensitive data discovery, see Default settings for automated sensitive data discovery.
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