using Macie to identify sensitive data stored in S3
AWS Macie detects sensitive data in S3 buckets, such as credentials, financial info, PII, and PHI. You can also create custom identifiers for specific needs.
Published Jan 12, 2025
Yashvi and Mishi's Mission: Protecting Guj Gov Vehicle and License Data
Yashvi and Mishi, enthusiastic devsecops team members at an IT company, are tasked with ensuring the security of govt data. They learn about Macie, a powerful AWS service that automatically scans S3 buckets for sensitive information.
The Challenge: Identifying Hidden Risks
The company stores various data in S3 buckets, including text files containing customer information. However, there's a concern that some files might contain sensitive data like credit card details, employee records, and even vehicle license plates (specific to Gujarat in their case). Manually identifying such data is time-consuming and error-prone.
Macie: The Automated Data Detective
Yashvi and Mishi discover Macie can be their hero. Here's how they go with Macie:
- Enabling Macie: They activate Macie, granting it access to their S3 bucket named "data-yk-us-ea-1."
- Creating a Data Discovery Job: They create a job specifically for this bucket. They choose a "daily" frequency to ensure regular scans for new uploads. They opt for a "One-time Job" to start, focusing on newly uploaded objects.
- Defining What's Sensitive: Macie offers various data identifiers to detect sensitive information. Yashvi and Mishi can choose to:
- Include All: Detect all categories of sensitive data.
- Exclude Specific Types: Focus on specific data like credit cards and personal details.
- Include Specific Types: Define custom data identifiers like Gujarat license plate formats.
- Customizing for Gujarat License Plates: They create a custom data identifier (pattern known example GJ01 ) to recognize license plates in the specific format used in Gujarat.
- Setting Up Alerts: They configure Macie to send notifications via SNS (Simple Notification Service) to a designated email address whenever sensitive data is found. This email could be Yashvi or Mishi's address, or a shared team inbox.
- EventBridge Integration: They leverage Amazon EventBridge to automate actions when Macie identifies sensitive data. For example, EventBridge could trigger actions like:
- Sending notifications to security teams.
- Moving sensitive data to a more secure S3 bucket.
- Encrypting sensitive data.
Running the Job and Seeing Results:
Yashvi and Mishi initiate the job. After completion, they receive an email notification (in JSON format for illustration purposes) detailing the findings. They can also access the results within Macie, which might reveal:
- Personal Data: Citizen names, addresses, etc.
- Credentials: Access keys, secrets, and tokens.
- Credit Card Information: Card numbers, expiry dates, etc.
- Gujarat License Plates: Vehicle registration details.
Taking Action:
Based on the findings, Yashvi and Mishi can take appropriate actions:
- Secure Sensitive Data: Move sensitive data to a more secure S3 bucket with stricter access controls.
- Remediate Issues: Address any immediate security risks identified by Macie.
- Set Up Regular Scans: Configure Macie to run regular jobs to continuously monitor for sensitive data.
Mission Accomplished!
Yashvi and Mishi have enhanced the security govt S3 data. They can now rest assured that sensitive information is automatically identified and addressed, protecting customer privacy and ensuring regulatory compliance.
Remember: This is a simplified fictional example,not real govt intern. In a real-world scenario, the specific data identifiers and actions taken would depend on the company's security policies and regulations.(Sensitive information types)
AWS Macie can identify a wide range of sensitive information types within your Amazon S3 data.
- Credentials:
- AWS Secret Access Keys
- Private keys
- Other AWS credentials
- Credentials for other cloud services
- Passwords
- Financial Information:
- Credit card numbers
- Bank account numbers
- Social Security numbers
- Taxpayer identification numbers
- Personally Identifiable Information (PII):
- Names
- Addresses
- Phone numbers
- Email addresses
- Passport numbers
- Driver's license numbers
- Personal Health Information (PHI):
- Medical records
- Health insurance information
- Intellectual Property:
- Trade secrets
- Source code
- Proprietary information
Custom Data Identifiers:
In addition to the pre-defined types, you can create custom data identifiers to detect specific types of sensitive information relevant to your organization. For example, you could create a custom identifier to detect:
- Employee IDs
- Customer IDs
- Internal company documents
- Specific product names
Key Considerations:
- Accuracy: While Macie is highly accurate, it's important to review the findings and potentially fine-tune the detection rules to minimize false positives.
- Regulatory Compliance: The specific types of sensitive data that need to be identified and protected will vary depending on the industry and applicable regulations (e.g., GDPR, HIPAA, PCI DSS).
- Data Classification: Macie's findings can be used to classify data based on its sensitivity level, which can help with data governance and security policies.
organizations can proactively identify and protect sensitive data stored in their S3 buckets, reducing the risk of data breaches and ensuring compliance with relevant regulations.
Disclaimer: This information is for general knowledge and informational purposes only. For the most up-to-date and accurate information, please refer to the official AWS documentation.
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