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