Individual skill
implementing-cloud-dlp-for-data-protection
Implement cloud DLP using Amazon Macie, Google Cloud DLP API, Microsoft Purview, Azure Information Protection, and Nightfall AI to discover, classify, label, de-identify, and protect sensitive data (PII, PHI, financial data) across cloud storage, databases, and pipelines. Use for GDPR/HIPAA/PCI DSS data-discovery, cloud data governance, or CI/CD DLP scanning; not for endpoint, email, or network-level DLP.
skills/implementing-cloud-dlp-for-data-protection/SKILL.md
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- Last checked
- Nov 9, 2026
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- Aug 31, 2026
- License
- Apache-2.0
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- ai-agents Repository topic
- claude-code Repository topic
- cybersecurity Repository topic
- incident-response Repository topic
- mitre-attack Repository topic
- penetration-testing Repository topic
- red-team Repository topic
- security Repository topic
- cloud-security Repository topic
- malware-analysis Repository topic
- cloud-security Declared skill tag
- dlp Declared skill tag
- data-protection Declared skill tag
- macie Declared skill tag
- data-classification Declared skill tag
- privacy Declared skill tag
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# Implementing Cloud DLP for Data Protection
## When to Use
- When compliance frameworks (GDPR, HIPAA, PCI DSS) require automated sensitive data discovery and protection
- When building data governance programs that classify and label data across cloud storage
- When implementing data loss prevention controls for cloud-based data pipelines
- When auditing cloud environments for unprotected sensitive data (PII, PHI, financial data)
- When integrating DLP scanning into CI/CD pipelines to prevent sensitive data from reaching production
**Do not use** for endpoint DLP (use Microsoft Purview or Symantec DLP agents), for email DLP (use Microsoft 365 DLP or Google Workspace DLP), or for network-level data exfiltration prevention (use VPC endpoint policies and network firewalls).
## Prerequisites
