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sica-fondt/knowledge/cyber-skills/skills/deploying-osquery-for-endpoint-monitoring/references/workflows.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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Workflows

Workflow 1: Osquery Fleet Deployment

[Install FleetDM server] → [Generate enrollment secret]
  → [Package osquery with fleet config] → [Deploy to pilot group]
  → [Verify enrollment and scheduled queries] → [Deploy to production]
  → [Create dashboards from query results] → [Ongoing monitoring]

Workflow 2: Threat Hunt with Osquery

[Define hypothesis] → [Write SQL query targeting hypothesis]
  → [Execute via FleetDM live query across fleet]
  → [Analyze results] → [Investigate anomalies]
  → [Document findings] → [Create scheduled detection if recurrent]