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

677 B

Workflows - WMIExec Lateral Movement

Lateral Movement Chain

1. Initial Compromise → Credential Harvesting → WMIExec to target
2. On each new host:
   ├── Enumerate local users and groups
   ├── Harvest credentials (LaZagne, Mimikatz, SAM dump)
   ├── Check for domain admin sessions
   └── Pivot to next target using recovered credentials

Multi-Method Fallback

Primary:   wmiexec.py (semi-interactive, output capture)
Fallback1: dcomexec.py (different DCOM object, avoids WMI-specific detection)
Fallback2: Native PowerShell CIM (blends with admin activity)
Fallback3: smbexec.py (uses SMB service, noisier but reliable)