mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
synced 2026-08-01 08:30:20 +00:00
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
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927 B
AI-Powered BEC Detection Template
AI Platform Configuration
| Setting | Value | Status |
|---|---|---|
| Platform | ||
| Integration | API-based (Microsoft Graph) | |
| Baseline training period | 30+ days | |
| Scanning scope | Inbound + Internal + Outbound |
Detection Thresholds
| Score Range | Classification | Action |
|---|---|---|
| 90-100% | High-confidence BEC | Auto-quarantine + SOC alert |
| 70-89% | Moderate BEC | Warning banner + analyst queue |
| 50-69% | Low-confidence BEC | Warning banner only |
| < 50% | Likely legitimate | Deliver normally |
VIP Protection List
| Name | Title | Writing Style Profiled | |
|---|---|---|---|
| CEO | |||
| CFO | |||
| CTO |
Model Performance Metrics
| Metric | Target | Current |
|---|---|---|
| Detection accuracy | > 98% | |
| False positive rate | < 0.05% | |
| Mean detection time | < 5 sec | |
| BEC catch rate vs. rules | +25% |