Amazon Macie

A service that helps identify and protect sensitive data in AWS, particularly in S3 environments, using machine learning and pattern matching.

AWS Proprietary Cloud Service Only
Category Data Security & Encryption
This page updated 22 days ago
Pricing Details Free tier available with 1 GB of data discovery per month; additional usage billed based on data processed.
Target Audience Organizations using AWS that need to protect sensitive data.

Amazon Macie manages identifying and protecting sensitive data within Amazon Web Services (AWS), particularly in Amazon S3 environments. This service leverages machine learning and pattern matching to automatically discover, classify, and protect sensitive data, such as personally identifiable information (PII), credit card numbers, and other sensitive identifiers.

The technical architecture of Macie involves integrating with AWS services to monitor and analyze S3 buckets. Upon activation, Macie generates a comprehensive inventory of S3 buckets, detailing their security and access controls, including public accessibility, encryption status, and sharing configurations. It uses managed and custom data identifiers to detect sensitive data, with the ability to define custom rules using regular expressions to cater to specific organizational needs.

Operationally, Macie is designed for ease of use, allowing administrators to enable the service with a single click in the AWS Management Console or via an API call. It supports multi-account setups through AWS Organizations, enabling centralized management across up to 5,000 accounts. Macie automates the discovery process, scheduling jobs to run periodically or on-demand, and integrates findings with AWS Security Hub, Amazon CloudWatch Events, and Amazon EventBridge for seamless workflow integration and remediation actions.

Key considerations include the service's current limitation to S3 buckets, although support for other AWS data stores is planned. The cost structure includes a free tier with 1 GB of free data discovery per month, and additional usage is billed based on the amount of data processed. This makes it cost-effective for discovering sensitive data at scale, but it can incur significant costs if not managed properly, especially in large and complex S3 environments.

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