AWS Unstructured Data Detection

Learn how to detect unstructured data in AWS environments. Follow step-by-step guidance for GDPR compliance and data security.

shadow data

GDPR

aws

Why It Matters

The core goal is to identify every location where unstructured data is stored within your AWS environment, so you can remediate unintended exposures before they become breaches. Scanning for unstructured data in AWS is a priority for organizations subject to GDPR, as it helps you prove you've discovered and accounted for all sensitive data assets—mitigating the risk of shadow data proliferation across your cloud infrastructure.

Primary Risk: Shadow data proliferation across cloud infrastructure

Relevant Regulation: GDPR General Data Protection Regulation

A thorough scan delivers immediate visibility into your unstructured data landscape, laying the foundation for automated policy enforcement and ongoing compliance.

Prerequisites

Permissions & Roles

  • AWS IAM admin or power user
  • S3:ListBucket, S3:GetObject privileges
  • Ability to deploy CloudFormation or Terraform

External Tools

  • AWS CLI
  • Cyera DSPM account
  • API credentials

Prior Setup

  • AWS account configured
  • S3 buckets accessible
  • CLI authenticated
  • Cross-region access configured

Introducing Cyera

Cyera is a modern Data Security Posture Management (DSPM) platform that discovers, classifies, and continuously monitors your sensitive data across cloud services. Using advanced AI and Natural Language Processing (NLP) techniques, Cyera automatically identifies and classifies unstructured data in AWS S3 buckets, documents, logs, and files—ensuring you stay ahead of shadow data risks and meet GDPR data discovery requirements in real time.

Step-by-Step Guide

1
Configure your AWS environment

Set up cross-account IAM roles with the minimum required privileges for S3 access. Ensure proper bucket policies are in place for scanning operations.

aws configure set region us-east-1

2
Enable scanning workflows

In the Cyera portal, navigate to Integrations → DSPM → Add new. Select AWS, provide your account ID and IAM role ARN, then define the scan scope across your S3 buckets and regions.

3
Integrate with third-party tools

Configure webhooks or streaming exports to push scan results into your SIEM or Security Hub. Link findings to existing ticketing systems like Jira or ServiceNow for remediation workflows.

4
Validate results and tune policies

Review the initial detection report, prioritize buckets with large volumes of unstructured sensitive data, and adjust detection rules to reduce false positives. Schedule recurring scans to maintain visibility.

Architecture & Workflow

AWS S3 Storage

Source of unstructured files and documents

Cyera Connector

Pulls metadata and samples files for classification

Cyera AI Engine

Applies NLP models and content analysis

Reporting & Remediation

Dashboards, alerts, and playbooks

Data Flow Summary

Enumerate Buckets → Send to Cyera → Apply AI Detection → Route Findings

Best Practices & Tips

Performance Considerations

  • Start with incremental or region-scoped scans
  • Use intelligent sampling for large file sets
  • Tune scan frequency for cost optimization

Tuning Detection Rules

  • Maintain allowlists for test environments
  • Adjust confidence thresholds per file type
  • Match rules to your data classification policy

Common Pitfalls

  • Forgetting cross-account bucket permissions
  • Over-scanning archived or backup buckets
  • Neglecting to monitor scan costs and quotas

References & Further Reading

Next Steps

🛡️ Prevent: Set up controls to prevent unstructured data exposure 🔧 Fix: Review and remediate exposed unstructured data