diff --git a/PROJECT-STATUS-AND-INNOVATION.md b/PROJECT-STATUS-AND-INNOVATION.md
index 07c9245d..2e45dd73 100644
--- a/PROJECT-STATUS-AND-INNOVATION.md
+++ b/PROJECT-STATUS-AND-INNOVATION.md
@@ -1,423 +1,286 @@
-# SecuBox Project Status Analysis & Generative Innovation Proposal
+# SecuBox v1.0.0-beta — Project Status & Innovation
+
+**Version:** 1.0.0-beta
+**Status:** Beta Release — Pen Testing & Bug Bounty Ready
+**Date:** 2026-03-15
+**Publisher:** [CyberMind.fr](https://cybermind.fr)
+
+---
 
 ## Executive Summary
 
-**Current Status**: SecuBox is a mature, production-ready security suite for OpenWrt with 15 fully implemented modules (100% completion rate) and 26,638 lines of JavaScript across 110 views. The system follows a robust three-loop security architecture and has comprehensive documentation, validation tools, and deployment workflows.
+SecuBox is a **production-ready** security and mesh networking platform for OpenWrt, featuring 86 LuCI modules, AI-powered threat analysis, and a unique three-channel service exposure model. The v1.0.0-beta release is ready for security testing and bug bounty programs.
 
-**Key Strengths**:
-- ✅ Complete three-loop security architecture (Operational, Tactical, Strategic)
-- ✅ 15 production-ready modules with extensive functionality
-- ✅ Comprehensive documentation and development guidelines
-- ✅ Robust validation and deployment tooling
-- ✅ Strong OpenWrt integration and UCI-based configuration
-- ✅ Professional design system and consistent UI patterns
+### Key Achievements
 
-**Innovation Opportunities**: Significant potential for generative AI integration, automation enhancement, and ecosystem expansion.
+| Metric | Value |
+|--------|-------|
+| **LuCI Modules** | 86 |
+| **Total Packages** | 123+ |
+| **RPCD Methods** | 400+ |
+| **JavaScript Views** | 150+ |
+| **Architectures** | x86-64, ARM64, MIPS, MediaTek |
 
-## Current Project Status Analysis
+### Release Artifacts
 
-### 1. Module Completion Status
+- **Source Code:** [github.com/CyberMind-FR/secubox-openwrt](https://github.com/CyberMind-FR/secubox-openwrt)
+- **VM Appliance:** SecuBox-v1.0.0-beta.tar.gz (69 MB)
+- **Documentation:** BETA-RELEASE.md, SECURITY.md
 
-**15 Modules - 100% Complete**
+---
 
-| Category | Modules | Status | Key Features |
-|----------|---------|--------|--------------|
-| **Core Control** | 2 | ✅ Production Ready | System hub, module management |
-| **Security & Monitoring** | 2 | ✅ Production Ready | CrowdSec, Netdata monitoring |
-| **Network Intelligence** | 2 | ✅ Production Ready | DPI, network modes |
-| **VPN & Access Control** | 3 | ✅ Production Ready | WireGuard, client guardian, auth guardian |
-| **Bandwidth & Traffic** | 3 | ✅ Production Ready | QoS, traffic shaping, media detection |
-| **Performance & Services** | 3 | ✅ Production Ready | CDN cache, vhost manager, KSM |
+## Four-Layer Security Architecture
 
-**Total**: 26,638 JS lines, 281 RPCD methods, 110 views
-
-### 2. Architecture Maturity
-
-**Three-Loop Security Model Fully Implemented**:
-- **Loop 1 (Operational)**: Real-time blocking with nftables, netifyd DPI, CrowdSec
-- **Loop 2 (Tactical)**: Pattern correlation with CrowdSec LAPI, Netdata metrics
-- **Loop 3 (Strategic)**: Threat intelligence via CrowdSec CAPI, blocklists
-
-**Technical Stack**:
-- ✅ OpenWrt 24.10.x & 25.12 support
-- ✅ LuCI framework integration
-- ✅ RPCD/ubus backend architecture
-- ✅ UCI configuration management
-- ✅ Comprehensive ACL and menu system
-
-### 3. Development Ecosystem
-
-**Robust Tooling**:
-- ✅ `validate-modules.sh` - Structural validation
-- ✅ `local-build.sh` - SDK automation
-- ✅ `fix-permissions.sh` - Permission management
-- ✅ `deploy-*.sh` - Remote deployment helpers
-- ✅ Comprehensive CI/CD workflows
-
-**Documentation**:
-- ✅ Development guidelines
-- ✅ Module implementation guides
-- ✅ Code templates and examples
-- ✅ Validation and testing procedures
-
-### 4. Design System
-
-**Professional UI Framework**:
-- ✅ Consistent CSS variables and classes
-- ✅ Responsive design patterns
-- ✅ Gradient-based visual language
-- ✅ Inter/JetBrains Mono typography
-- ✅ Accessible color palette
-
-## Generative Innovation Opportunities
-
-### 1. AI-Powered Security Automation
-
-**Opportunity**: Integrate generative AI to enhance the three-loop security architecture.
-
-**Proposed Innovations**:
-
-#### 1.1 AI-Enhanced Loop 1 (Operational)
-```markdown
-**Real-time Threat Analysis with AI**
-- AI-powered anomaly detection in network traffic
-- Machine learning-based protocol classification
-- Automated signature generation for new threats
-- Predictive blocking based on behavioral patterns
+```
++============================================================+
+|              LAYER 4: MESH NETWORKING                       |
+|              MirrorNet / P2P Hub / Services Mirrors         |
+|  +--------------------------------------------------------+ |
+|  |           LAYER 3: AI GATEWAY                          | |
+|  |           MCP Server / Threat Analyst / DNS Guard      | |
+|  |  +----------------------------------------------------+ | |
+|  |  |         LAYER 2: TACTICAL                          | | |
+|  |  |         CrowdSec / WAF / Scenarios                 | | |
+|  |  |  +------------------------------------------------+ | | |
+|  |  |  |       LAYER 1: OPERATIONAL                     | | | |
+|  |  |  |       fw4 / DPI / Bouncer / HAProxy            | | | |
+|  |  |  +------------------------------------------------+ | | |
+|  |  +----------------------------------------------------+ | |
+|  +--------------------------------------------------------+ |
++============================================================+
 ```
 
-**Implementation**:
-- Integrate Python ML models with RPCD backend
-- Use TensorFlow Lite for edge device compatibility
-- Train models on historical attack patterns
-- Provide real-time threat scoring and recommendations
+| Layer | Function | Time Scale | Components |
+|-------|----------|------------|------------|
+| **Layer 1** | Real-time blocking | ms → seconds | nftables/fw4, netifyd DPI, CrowdSec Bouncer |
+| **Layer 2** | Pattern correlation | minutes → hours | CrowdSec Agent/LAPI, mitmproxy WAF, Scenarios |
+| **Layer 3** | AI analysis | minutes → hours | MCP Server, Threat Analyst, DNS Guard |
+| **Layer 4** | Mesh networking | continuous | P2P Hub, MirrorBox, Services Registry |
 
-#### 1.2 AI-Enhanced Loop 2 (Tactical)
-```markdown
-**Automated Pattern Correlation**
-- AI-driven attack chain identification
-- Automated scenario generation from logs
-- Predictive threat intelligence synthesis
-- Anomaly detection in correlation patterns
+---
+
+## Punk Exposure — Three-Channel Service Publishing
+
+The **Peek / Poke / Emancipate** model enables decentralized service exposure:
+
+```
+┌─────────────────────────────────────────────────────────────┐
+│                    YOUR CONTENT/SERVICE                      │
+└─────────────────────────────────────────────────────────────┘
+                            │
+         ┌──────────────────┼──────────────────┐
+         ▼                  ▼                  ▼
+    ┌─────────┐        ┌─────────┐        ┌─────────┐
+    │   TOR   │        │   DNS   │        │  MESH   │
+    │ .onion  │        │  /SSL   │        │  P2P    │
+    └─────────┘        └─────────┘        └─────────┘
+    Anonymous          Classical          Tribal
+    Hidden Service     HTTPS              Gossip Network
 ```
 
-**Implementation**:
-- Natural language processing for log analysis
-- Graph-based attack pattern detection
-- Automated scenario generation engine
-- Integration with CrowdSec for collaborative learning
+| Channel | Use Case | Status |
+|---------|----------|--------|
+| **Tor** | Anonymous hidden services | ✅ Implemented |
+| **DNS/SSL** | Classical HTTPS with auto-SSL | ✅ Implemented |
+| **Mesh** | Tribal gossip network | ✅ Implemented |
 
-#### 1.3 AI-Enhanced Loop 3 (Strategic)
-```markdown
-**Generative Threat Intelligence**
-- AI-generated threat intelligence reports
-- Predictive threat landscape analysis
-- Automated blocklist generation
-- Generative adversarial network for threat simulation
+### Emancipate CLI
+
+```bash
+# Full emancipation (Tor + DNS + Mesh)
+secubox-exposure emancipate myblog 8080 blog.example.com --all
+
+# Selective channels
+secubox-exposure emancipate myapp 8080 myapp.secubox.in --dns --mesh
 ```
 
-**Implementation**:
-- Large language models for report generation
-- Predictive analytics for emerging threats
-- Automated intelligence sharing protocols
-- Threat simulation and red teaming
+---
 
-### 2. Autonomous Network Management
+## Innovation Highlights
 
-**Opportunity**: AI-driven network optimization and self-healing.
+### 1. AI Gateway (Implemented)
 
-**Proposed Innovations**:
+**Data Classification & Routing:**
+- **LOCAL_ONLY:** Sensitive data stays on device
+- **SANITIZED:** PII scrubbed before EU cloud processing
+- **CLOUD_DIRECT:** Generic queries to opted-in providers
 
-#### 2.1 AI Network Orchestration
-```markdown
-**Self-Optimizing Network Modes**
-- AI-driven network mode selection
-- Automated QoS parameter tuning
-- Predictive bandwidth allocation
-- Self-healing network configurations
+**Provider Priority:** LocalAI → Mistral EU → Claude → OpenAI → Gemini
+
+### 2. MCP Server (Implemented)
+
+Model Context Protocol integration for Claude Desktop:
+
+```json
+{
+  "mcpServers": {
+    "secubox": {
+      "command": "ssh",
+      "args": ["root@192.168.255.1", "/usr/bin/secubox-mcp"]
+    }
+  }
+}
 ```
 
-**Implementation**:
-- Reinforcement learning for network optimization
-- Real-time traffic pattern analysis
-- Automated configuration adjustments
-- Failure prediction and prevention
+**Available Tools:** `crowdsec.alerts`, `waf.logs`, `dns.queries`, `network.flows`, `ai.analyze_threats`, `ai.suggest_waf_rules`
 
-#### 2.2 AI Traffic Engineering
-```markdown
-**Intelligent Traffic Routing**
-- AI-powered load balancing
-- Predictive congestion avoidance
-- Automated path optimization
-- Self-adjusting QoS policies
-```
+### 3. Dual-Stream DPI (Implemented)
 
-**Implementation**:
-- Traffic flow prediction models
-- Dynamic routing algorithms
-- Congestion detection and mitigation
-- Automated policy generation
+**Phase 1 — TAP Stream:** tc mirred passive monitoring
+**Phase 2 — MITM Double Buffer:** Enhanced correlation
+**Phase 3 — Correlation Engine:** Auto-ban for high-reputation IPs
+**Phase 4 — LAN Passive Flow:** Zero-MITM LAN observation
 
-### 3. Generative Security Policies
+### 4. Threat Analyst (Implemented)
 
-**Opportunity**: AI-generated security policies and rules.
-
-**Proposed Innovations**:
-
-#### 3.1 AI Policy Generation
-```markdown
-**Automated Security Policy Creation**
-- AI-generated firewall rules
-- Automated access control policies
-- Context-aware security profiles
-- Adaptive security posture management
-```
-
-**Implementation**:
-- Policy generation based on usage patterns
-- Context-aware rule creation
-- Automated policy optimization
-- Continuous policy refinement
-
-#### 3.2 AI Compliance Management
-```markdown
-**Automated Compliance Monitoring**
-- AI-driven compliance checking
-- Automated audit trail generation
-- Predictive compliance risk assessment
-- Self-correcting compliance violations
-```
-
-**Implementation**:
-- Compliance rule databases
-- Automated audit procedures
-- Risk assessment algorithms
-- Remediation workflows
-
-### 4. Generative Interface Enhancements
-
-**Opportunity**: AI-powered UI generation and personalization.
-
-**Proposed Innovations**:
-
-#### 4.1 AI Dashboard Generation
-```markdown
-**Automated Dashboard Creation**
-- AI-generated dashboard layouts
-- Context-aware widget selection
-- Personalized information display
-- Adaptive visualization techniques
-```
-
-**Implementation**:
-- Dashboard generation algorithms
-- User preference learning
-- Context-aware layout optimization
-- Automated widget configuration
-
-#### 4.2 AI Assistants
-```markdown
-**Intelligent User Assistance**
-- AI-powered help system
-- Natural language query processing
-- Context-aware recommendations
-- Automated troubleshooting guides
-```
-
-**Implementation**:
-- Natural language processing
-- Knowledge base integration
-- Context-aware assistance
-- Automated problem resolution
-
-### 5. Generative Documentation
-
-**Opportunity**: AI-powered documentation generation and maintenance.
-
-**Proposed Innovations**:
-
-#### 5.1 AI Documentation Generation
-```markdown
-**Automated Documentation Creation**
-- AI-generated module documentation
-- Automated API documentation
-- Context-aware user guides
-- Self-updating documentation
-```
-
-**Implementation**:
-- Code analysis for documentation generation
-- API specification extraction
-- Context-aware guide creation
-- Automated documentation updates
-
-#### 5.2 AI Knowledge Base
-```markdown
-**Intelligent Knowledge Management**
-- AI-powered knowledge base
-- Automated FAQ generation
-- Context-aware help articles
-- Self-learning knowledge system
-```
-
-**Implementation**:
-- Knowledge extraction from code
-- Automated FAQ generation
-- Context-aware help system
-- Continuous knowledge learning
-
-## Implementation Roadmap
-
-### Phase 1: Foundation (3-6 months)
-```markdown
-**AI Infrastructure Setup**
-- Python ML environment integration
-- Model training pipeline
-- Edge device optimization
-- Security model integration
-```
-
-### Phase 2: Core AI Features (6-12 months)
-```markdown
-**AI Security Enhancements**
+Autonomous AI agent for:
 - Real-time threat analysis
-- Automated pattern correlation
-- Generative threat intelligence
-- AI policy generation
+- CrowdSec scenario generation
+- WAF rule suggestions
+- CVE lookups and context enrichment
+
+### 5. Configuration Vault (Implemented)
+
+Git-based config versioning with:
+- Auto-commit and auto-push
+- 9 configuration modules
+- Export/import clone tarballs
+- Device provisioning workflows
+
+### 6. Unified SMTP Relay (Implemented)
+
+Centralized SMTP configuration:
+- Modes: external (Gmail, SendGrid), local (auto-detect), direct
+- Shared library: `send_mail()` function
+- All SecuBox apps use unified relay
+
+---
+
+## Module Categories
+
+### Core (6 modules)
+- luci-app-secubox, luci-app-secubox-portal, luci-app-secubox-admin
+- secubox-app-bonus, luci-app-system-hub, luci-theme-secubox
+
+### Security (15 modules)
+- CrowdSec, mitmproxy WAF, MAC Guardian, DNS Guard
+- Threat Analyst, KSM Manager, Master Link
+- Auth Guardian, Client Guardian, Exposure Manager
+
+### Network (12 modules)
+- HAProxy, WireGuard, Network Modes, DNS Provider
+- Bandwidth Manager, Traffic Shaper, CDN Cache
+
+### AI/LLM (4 modules)
+- LocalAI, Ollama, AI Gateway, MCP Server
+
+### Media (7 modules)
+- Jellyfin, Lyrion, PhotoPrism, Zigbee2MQTT, Domoticz
+
+### Content Platforms (6 modules)
+- Gitea, MetaBlogizer, HexoJS, Streamlit, Jitsi
+
+### P2P Mesh (4 modules)
+- P2P Hub, Service Registry, Device Intel, Content Package
+
+---
+
+## Roadmap
+
+| Version | Status | Focus |
+|---------|--------|-------|
+| v0.17 | ✅ Released | Core Mesh, 38 modules |
+| v0.18 | ✅ Released | P2P Hub, AI Gateway, 86 modules |
+| v0.19 | ✅ Released | Full P2P intelligence |
+| **v1.0.0-beta** | **Current** | Pen testing, bug bounty, documentation |
+| v1.1 | Planned | ANSSI certification, GA release |
+
+### v1.1 Targets
+
+1. **ANSSI CSPN Certification** — French security certification
+2. **CRA Compliance** — EU Cyber Resilience Act readiness
+3. **SBOM Pipeline** — Automated vulnerability scanning
+4. **Enterprise Features** — Multi-tenant, SSO, audit logging
+
+---
+
+## Security Testing
+
+The v1.0.0-beta release is specifically prepared for:
+
+### Attack Surface
+
+| Layer | Components | Risk Areas |
+|-------|------------|------------|
+| **Network Edge** | HAProxy, mitmproxy WAF | WAF bypass, header injection |
+| **Applications** | LuCI, RPCD | Shell injection, XSS, CSRF |
+| **Containers** | LXC services | Container escape, privilege escalation |
+| **Mesh/P2P** | WireGuard, gossip | Key theft, peer impersonation |
+
+### Bug Bounty Scope
+
+| Severity | Category |
+|----------|----------|
+| **Critical** | RCE, Auth Bypass |
+| **High** | Privilege Escalation, WAF Bypass |
+| **Medium** | Information Disclosure |
+| **Low** | DoS, XSS |
+
+**Report:** security@cybermind.fr
+
+---
+
+## Distribution
+
+### Virtual Appliance
+
+| File | Format | Use |
+|------|--------|-----|
+| C3Box-SecuBox.ova | OVA | VMware, VirtualBox |
+| C3Box-SecuBox.vdi | VDI | VirtualBox |
+| C3Box-SecuBox.vmdk | VMDK | VMware |
+| C3Box-SecuBox.qcow2 | QCOW2 | Proxmox/KVM |
+
+**Default Login:** root / c3box
+
+### Package Feed
+
+```
+src/gz secubox https://secubox.in/feed
 ```
 
-### Phase 3: Advanced Automation (12-18 months)
-```markdown
-**Autonomous Systems**
-- Self-optimizing networks
-- AI traffic engineering
-- Automated compliance
-- AI dashboard generation
-```
+---
 
-### Phase 4: Ecosystem Expansion (18-24 months)
-```markdown
-**AI Ecosystem Integration**
-- AI assistants
-- Generative documentation
-- Knowledge base integration
-- Continuous learning systems
-```
+## Technical Stack
 
-## Technical Implementation Strategy
+| Component | Technology |
+|-----------|------------|
+| **OS** | OpenWrt 24.10.x / 25.12 |
+| **Frontend** | LuCI JavaScript, KISS Theme |
+| **Backend** | RPCD/ubus, Shell, Lua |
+| **Security** | CrowdSec, mitmproxy, nftables |
+| **Containers** | LXC (Alpine/Debian) |
+| **AI** | LocalAI, Claude API, Mistral |
+| **P2P** | WireGuard, Gossip Protocol |
 
-### 1. AI Integration Architecture
+---
 
-```mermaid
-graph TD
-    A[SecuBox Core] --> B[AI Engine]
-    B --> C[Threat Analysis Models]
-    B --> D[Pattern Correlation]
-    B --> E[Policy Generation]
-    B --> F[Network Optimization]
-    C --> G[Real-time Detection]
-    D --> H[Attack Chain Analysis]
-    E --> I[Automated Rules]
-    F --> J[Self-Optimizing Networks]
-```
+## Contributors
 
-### 2. Model Integration Points
+- **Lead:** Gandalf — [CyberMind.fr](https://cybermind.fr)
+- **AI Assistance:** Claude (Anthropic)
 
-**Loop 1 Integration**:
-- RPCD backend enhancements
-- Real-time analysis modules
-- Automated blocking decisions
+---
 
-**Loop 2 Integration**:
-- Correlation engine enhancements
-- Pattern detection algorithms
-- Automated scenario generation
+## Links
 
-**Loop 3 Integration**:
-- Intelligence synthesis
-- Predictive analytics
-- Automated reporting
+- **Website:** [secubox.maegia.tv](https://secubox.maegia.tv)
+- **GitHub:** [github.com/CyberMind-FR/secubox-openwrt](https://github.com/CyberMind-FR/secubox-openwrt)
+- **Security:** [BETA-RELEASE.md](BETA-RELEASE.md) | [SECURITY.md](SECURITY.md)
+- **Issues:** [GitHub Issues](https://github.com/CyberMind-FR/secubox-openwrt/issues)
 
-### 3. Development Approach
+---
 
-**Incremental Integration**:
-1. Start with specific AI modules
-2. Gradually expand AI capabilities
-3. Continuous testing and validation
-4. User feedback integration
+**Ex Tenebris, Lux Securitas**
 
-**Modular Design**:
-- Plug-and-play AI components
-- Independent module operation
-- Gradual feature activation
-- Backward compatibility
-
-## Innovation Impact Assessment
-
-### Expected Benefits
-
-| Area | Current | With AI Innovation | Improvement |
-|------|---------|-------------------|-------------|
-| **Threat Detection** | Rule-based | AI-powered | 300-500% |
-| **Response Time** | Manual | Automated | 90% reduction |
-| **Policy Management** | Manual | AI-generated | 80% automation |
-| **Network Optimization** | Static | Dynamic | 40-60% efficiency |
-| **User Experience** | Standard | Personalized | 50-70% satisfaction |
-| **Documentation** | Manual | AI-generated | 80% automation |
-
-### Risk Assessment
-
-**Low Risk**:
-- AI model integration
-- Policy generation
-- Documentation automation
-
-**Medium Risk**:
-- Real-time threat analysis
-- Network optimization
-- Compliance management
-
-**High Risk**:
-- Autonomous decision making
-- Self-modifying systems
-- Continuous learning systems
-
-## Recommendations
-
-### 1. Immediate Actions
-- **AI Infrastructure Setup**: Prepare Python ML environment
-- **Model Training**: Start with threat detection models
-- **Integration Planning**: Design AI architecture
-- **Team Training**: AI/ML skills development
-
-### 2. Short-Term Goals
-- **Pilot Projects**: Start with specific AI modules
-- **User Testing**: Gather feedback on AI features
-- **Performance Optimization**: Edge device compatibility
-- **Security Validation**: AI model security testing
-
-### 3. Long-Term Strategy
-- **Continuous Innovation**: Regular AI feature updates
-- **Ecosystem Expansion**: Partner integrations
-- **Community Engagement**: Open source contributions
-- **Research Collaboration**: Academic partnerships
-
-## Conclusion
-
-SecuBox is at an excellent position for generative innovation. The existing architecture provides a solid foundation for AI integration, and the comprehensive module system allows for incremental AI enhancement. By strategically integrating generative AI capabilities across the three-loop security architecture, SecuBox can evolve into a next-generation, self-optimizing security platform with significant competitive advantages.
-
-**Key Innovation Areas**:
-1. **AI-Powered Security Automation** - 300-500% threat detection improvement
-2. **Autonomous Network Management** - 40-60% efficiency gains
-3. **Generative Security Policies** - 80% policy automation
-4. **Generative Interface Enhancements** - 50-70% UX improvement
-5. **Generative Documentation** - 80% documentation automation
-
-The proposed innovations align with SecuBox's existing architecture and can be implemented incrementally, ensuring minimal disruption while delivering maximum impact. This approach positions SecuBox as a leader in AI-powered network security for OpenWrt platforms.
-
-**Next Steps**:
-- Begin AI infrastructure setup
-- Develop pilot AI modules
-- Create implementation roadmap
-- Engage community for feedback
-- Establish research partnerships
\ No newline at end of file
+© 2024-2026 CyberMind.fr — Apache-2.0 License
diff --git a/README.md b/README.md
index aeae98b5..1b9391db 100644
--- a/README.md
+++ b/README.md
@@ -271,6 +271,11 @@ SecuBox includes an MCP server for AI integration:
 
 See [BETA-RELEASE.md](BETA-RELEASE.md) for security testing guidelines and bug bounty scope.
 
+### Default Credentials (VM Appliance)
+
+- **Username:** root
+- **Password:** c3box (change on first login!)
+
 ---
 
 ## Links