DiabloRain
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- README.md: Complete project overview with features, download, quick start - ARCHITECTURE.md: System design, components, security architecture - Includes technology stack, deployment models, performance specs - All non-sensitive IP suitable for public consumption
177 lines
5.5 KiB
Markdown
177 lines
5.5 KiB
Markdown
# Syn_OS Architecture Overview
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## System Design Philosophy
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Syn_OS is built on three core principles:
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1. **Modularity** — Clean separation between kernel, services, and applications
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2. **Security by Design** — Defense-in-depth with multiple layers of protection
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3. **AI Integration** — Machine learning at every level, from kernel to user interface
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---
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## High-Level Architecture
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```
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┌──────────────────────────────────────────────────────────────┐
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│ USER SPACE APPLICATIONS │
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│ ALFRED AI │ GRIMOIRE Labs │ Security Tools │ TUI Apps │
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├──────────────────────────────────────────────────────────────┤
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│ CORE SERVICES LAYER │
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│ AI Daemon │ Consciousness │ Data Lake │ Zero-Trust Engine │
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├──────────────────────────────────────────────────────────────┤
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│ KERNEL SPACE (Linux) │
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│ Rust Modules │ eBPF Monitors │ Custom Syscalls (480-491) │
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├──────────────────────────────────────────────────────────────┤
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│ HARDWARE LAYER │
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│ CPU │ GPU │ TPU │ Memory │ Storage │ Network │
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└──────────────────────────────────────────────────────────────┘
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```
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---
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## Component Breakdown
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### 1. Kernel Layer
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**Base:** Linux 6.12.57 (Production) / 6.18.2 (Experimental)
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**Custom Components:**
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- **11 Custom Syscalls (480-491)** — Direct AI-kernel communication
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- **12 Rust Kernel Modules** — Memory-safe kernel extensions
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- **5 eBPF Monitors** — Real-time security monitoring
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- **AI Scheduler Hooks** — Process scheduling with ML optimization
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### 2. Core Services
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**ALFRED Daemon (Rust + Python)**
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- LLM inference engine (ONNX/TensorFlow Lite)
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- RAG system with ChromaDB vector database
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- STIX 2.1 threat intelligence processing
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- Raft consensus for distributed deployments
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**Consciousness Framework**
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- Distributed state machine across multiple nodes
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- Neural network-based decision making
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- Self-healing and optimization
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**Zero-Trust Engine**
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- PKI-based authentication
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- Behavioral analytics
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- Policy enforcement engine
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### 3. Application Layer
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**GRIMOIRE Labs Platform**
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- 50+ hands-on cybersecurity labs
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- Docker-based isolated environments
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- Progress tracking with XP/skill trees
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**Security Tools Suite**
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- 600+ tools from Kali/Parrot/BlackArch
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- Unified CLI with `alfred` integration
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- Automated workflow engine
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---
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## Security Architecture
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### Defense Layers
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```
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Layer 1: Hardware Security (TPM, Secure Boot)
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Layer 2: Kernel Hardening (SELinux, AppArmor, eBPF)
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Layer 3: Service Isolation (Systemd, containers)
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Layer 4: Application Sandboxing (Flatpak, Snap)
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Layer 5: Network Security (Zero-Trust, PQC)
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Layer 6: AI Monitoring (Real-time threat detection)
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```
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### Post-Quantum Cryptography
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- **ML-KEM** — Key encapsulation (NIST FIPS 203)
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- **ML-DSA** — Digital signatures (NIST FIPS 204)
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- **SLH-DSA** — Stateless hash-based signatures (NIST FIPS 205)
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---
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## Data Flow
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### Threat Detection Pipeline
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```
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1. eBPF Monitor → Detect anomaly in kernel
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2. Syscall 480 → Report to ALFRED daemon
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3. ML Inference → Classify threat (confidence score)
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4. Policy Engine → Determine response action
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5. Enforcement → Block/log/alert
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6. STIX Export → Share intel with SIEM
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```
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### ALFRED Request Flow
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```
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1. User Input → CLI/Voice/API
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2. Context Retrieval → RAG system (ChromaDB)
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3. LLM Inference → Generate response
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4. Action Execution → Run tools/scripts
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5. Result → Display to user
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6. Memory Update → Store in knowledge base
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```
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---
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## Deployment Models
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### 1. Standalone Workstation
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- Single-user system
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- Local AI inference
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- Offline capable
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### 2. Team Environment
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- Multi-user access
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- Shared GRIMOIRE labs
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- Centralized logging
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### 3. Enterprise Deployment
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- Distributed consciousness
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- SIEM integration
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- High availability with Raft consensus
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---
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## Technology Stack
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| Layer | Technologies |
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|-------|-------------|
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| **Kernel** | Linux 6.12+, Rust, C, eBPF |
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| **Core Services** | Rust (Tokio), Python, PostgreSQL, TimescaleDB |
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| **AI/ML** | ONNX, TensorFlow Lite, PyTorch, ChromaDB |
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| **Networking** | QUIC, WireGuard, liboqs (PQC) |
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| **Containers** | Docker, Podman, systemd-nspawn |
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| **Build** | Debian live-build, Cargo, CMake |
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---
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## Performance Characteristics
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**Boot Time:** ~30 seconds (UEFI SSD)
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**Memory Footprint:** ~2GB idle, ~4GB with ALFRED active
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**AI Inference:** 7B LLM on 8GB RAM (TNGS-optimized)
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**Lab Startup:** ~5 seconds per Docker container
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---
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## Scalability
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**Vertical:** Up to 128GB RAM, 32 cores tested
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**Horizontal:** Raft consensus supports 5-7 nodes
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**Storage:** TimescaleDB handles TB-scale logs
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---
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For more details, see:
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- [Kernel Integration](articles/kernel-architecture.md)
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- [ALFRED Technical Spec](articles/alfred-architecture.md)
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- [GRIMOIRE Platform Design](articles/grimoire-architecture.md)
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