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sica-fondt/knowledge/cyber-skills/skills/implementing-aws-macie-for-data-classification/references/standards.md
Claude 24f816b6a3
Consolidate 22 sibling repos into layered organism structure 
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):

- brain/        LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
                dispatch, A51 channels, and the OSINT cluster
- knowledge/    LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
                MITRE ATT&CK data
- reference/    defensive threat-reference (C3, shhbruh doc) + AdaYaml parser

License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.

Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.

https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
2026-06-10 06:53:01 +00:00

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Standards - AWS Macie for Data Classification

Compliance Frameworks Supported

  • GDPR Article 30: Records of processing activities
  • CCPA: California Consumer Privacy Act data discovery
  • HIPAA: Protected health information identification
  • PCI DSS 4.0: Cardholder data discovery (Requirement 3)
  • SOC 2: Data classification and protection controls

AWS Well-Architected Security Pillar

  • SEC 8: Protect data at rest
  • SEC 10: Prepare for security events

NIST 800-53 Controls

  • RA-5: Vulnerability Monitoring and Scanning
  • SC-28: Protection of Information at Rest
  • SI-4: System Monitoring
  • MP-4: Media Storage