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

739 B

Workflows

Workflow 1: Linux CIS Hardening Deployment

[Select CIS Benchmark for distro/version] → [Choose L1 or L2 profile]
  → [Run OpenSCAP baseline assessment] → [Review initial compliance score]
  → [Apply remediations (Ansible/manual)] → [Re-assess with OpenSCAP]
  → [Document exceptions] → [Deploy to production fleet]
  → [Schedule quarterly reassessment]

Workflow 2: Automated Remediation with Ansible

[Clone Ansible Lockdown role for target distro]
  → [Configure variables (skip list, exceptions)]
  → [Test against staging servers]
  → [Review changes and application compatibility]
  → [Deploy to production in rolling batches]
  → [Run OpenSCAP validation after each batch]