mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
synced 2026-08-01 08:30:20 +00:00
24f816b6a3
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
823 B
823 B
Workflows - AWS Macie Data Classification
Implementation Workflow
1. Enable Macie → Configure administrator account
2. Bucket Inventory → Review automated S3 inventory
3. Discovery Jobs → Create targeted classification jobs
4. Custom Identifiers → Add organization-specific patterns
5. Allow Lists → Suppress known false positives
6. Automation → EventBridge + Lambda for response
7. Reporting → Dashboard and Security Hub integration
Remediation Workflow
1. Finding Generated → Macie detects sensitive data
2. Triage → Security team reviews severity and data type
3. Classify → Determine data classification level
4. Protect → Apply encryption, access controls, or relocate
5. Validate → Re-scan to confirm remediation
6. Document → Update data classification inventory