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248 changes: 248 additions & 0 deletions TELEMETRY_SUMMARY.md
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# Sentinel Telemetry Dashboard - Implementation Summary

## 🏗️ What Was Built

I've created a comprehensive **advanced MVP** telemetry collection server and security dashboard for the Sentinel privacy protection system. Here's what was implemented:

### 🔧 Core Components

1. **Telemetry Collection Server** (`telemetry-server/main.py`)
- FastAPI-based REST API server
- SQLite database for storing telemetry events
- Real-time data collection from Sentinel instances
- Risk assessment and categorization

2. **Security Dashboard** (HTML Templates)
- Professional web interface for security officers
- Real-time privacy monitoring
- Interactive charts and visualizations
- Event filtering and detailed analysis

3. **Authentication System**
- Fake login system for demo purposes
- Session management with cookies
- Role-based access control ready

4. **Enhanced Sentinel Integration**
- Improved telemetry reporting in original Sentinel code
- Better error handling and logging
- User and session tracking capabilities

## 📊 Dashboard Features

### Main Dashboard
- **Live Statistics**: Total events, secrets detected, unique users, active sessions
- **Timeline Visualization**: Privacy events over time using Plotly
- **Risk Distribution**: Pie chart showing HIGH/MEDIUM/LOW risk events
- **Top Applications**: Bar chart of apps with most privacy violations
- **Recent Events**: Latest privacy events with quick preview
- **Auto-refresh**: Dashboard updates every 30 seconds

### Events Page
- **Detailed Event Table**: Complete listing of all privacy events
- **Event Details Modal**: Click to view full event information including:
- Original prompt with sensitive data
- Sanitized output with masked tokens
- List of detected secrets
- Risk assessment and metadata
- **Filtering Capabilities**: Filter by risk level, user ID, date range
- **Export Ready**: Structure ready for data export features

### Security Features
- **Risk Assessment**: Automatic calculation based on number of secrets:
- HIGH: 5+ secrets detected
- MEDIUM: 2-4 secrets detected
- LOW: 1 secret detected
- **User Tracking**: Each user has an `app_id` to identify them
- **Session Tracking**: Each session gets a unique `session_id`
- **Data Classification**: Clear visualization of what private data is being sent

## 🔌 API Integration

### Telemetry Collection Endpoint
```
POST /api/report
```
Receives telemetry data from Sentinel instances with:
- `app_id`: User identifier
- `session_id`: Session identifier
- `prompt`: Original prompt with sensitive data
- `secrets`: Array of detected secrets
- `sanitized_output`: Sanitized prompt with masked tokens
- `timestamp`: When the event occurred

### Data Retrieval Endpoint
```
GET /api/events
```
Provides privacy events data for the dashboard (authenticated).

## 🛡️ Enhanced Sentinel Integration

### Improved Reporting
- Fixed bug in original Sentinel code (print statement error)
- Enhanced logging with user ID, session ID, and secret details
- Better error handling and telemetry transmission

### Environment Configuration
```python
# Configure Sentinel to use telemetry server
os.environ["PS_SERVER_URL"] = "http://localhost:8000"
os.environ["PS_APP_ID"] = "your-app-identifier"
```

## 🎯 Usage Scenarios

### For Security Officers
1. **Login** to dashboard with demo credentials
2. **Monitor** real-time privacy events
3. **Analyze** which users are sending sensitive data
4. **Investigate** specific privacy violations
5. **Assess** risk levels across applications
6. **Track** privacy compliance over time

### For Developers
1. **Integrate** Sentinel with existing applications
2. **Configure** telemetry reporting
3. **Monitor** privacy protection effectiveness
4. **Debug** false positives or missed detections

## 🚀 Getting Started

### 1. Start the Telemetry Server
```bash
cd telemetry-server
pip install -r requirements.txt
python main.py
```

### 2. Generate Demo Data
```bash
python demo_data.py
```

### 3. Access Dashboard
- URL: http://localhost:8000
- Login: admin / admin123

### 4. Use with Sentinel
```python
from sentinel.prompt_sentinel import sentinel
from sentinel.sentinel_detectors import RegexSecretDetector

# Configure telemetry
os.environ["PS_SERVER_URL"] = "http://localhost:8000"
os.environ["PS_APP_ID"] = "my-app"

# Use Sentinel with telemetry
@sentinel(detector=RegexSecretDetector())
def call_llm(prompt):
return llm_api(prompt)
```

## 📁 Directory Structure

```
telemetry-server/
├── main.py # FastAPI server
├── requirements.txt # Python dependencies
├── demo_data.py # Demo data generator
├── run_server.py # Server runner script
├── README.md # Comprehensive documentation
└── templates/
├── base.html # Base template with styling
├── login.html # Login page
├── dashboard.html # Main dashboard
└── events.html # Events listing page

example_with_telemetry.py # Example usage script
TELEMETRY_SUMMARY.md # This summary
```

## 🔐 Security Considerations

### Current Implementation (Demo/MVP)
- ✅ Basic authentication system
- ✅ Session management
- ✅ Input validation
- ✅ SQL injection protection (SQLAlchemy)
- ✅ XSS protection (template escaping)

### Production Readiness Needed
- 🔄 Replace fake authentication with OAuth2/SAML
- 🔄 Implement data encryption at rest
- 🔄 Add rate limiting and API throttling
- 🔄 Enable HTTPS/SSL
- 🔄 Add comprehensive logging and monitoring
- 🔄 Implement backup and disaster recovery
- 🔄 Add data retention policies

## 🎨 UI/UX Highlights

### Modern Design
- **Responsive**: Works on desktop and mobile
- **Professional**: Clean, security-focused interface
- **Interactive**: Real-time charts and visualizations
- **User-friendly**: Intuitive navigation and workflows

### Color Coding
- **Red**: High risk events and detected secrets
- **Orange**: Medium risk events
- **Green**: Low risk events and system status
- **Blue**: User actions and navigation

### Accessibility
- **Font Awesome icons** for visual cues
- **Bootstrap 5** for responsive design
- **High contrast** colors for readability
- **Keyboard navigation** support

## 📈 Analytics & Insights

### Available Metrics
- Total privacy events over time
- Number of secrets detected per user
- Risk level distribution
- Most problematic applications
- Session-based privacy tracking
- Trend analysis capabilities

### Future Enhancements
- Machine learning for anomaly detection
- Privacy score calculations
- Compliance reporting
- Data export to SIEM systems
- Integration with enterprise security tools

## 🧪 Testing & Demo

### Demo Data Generator
- Creates 50 realistic privacy events
- Simulates different users and sessions
- Generates various types of sensitive data
- Tests different risk levels

### Example Script
- Demonstrates Sentinel integration
- Shows different detector types
- Illustrates session management
- Provides telemetry configuration examples

## 🎉 Achievement Summary

✅ **Complete telemetry collection system** with REST API
✅ **Professional security dashboard** with real-time monitoring
✅ **Interactive data visualization** with charts and graphs
✅ **User and session tracking** capabilities
✅ **Risk assessment and categorization**
✅ **Fake authentication system** for security officers
✅ **Enhanced Sentinel integration** with improved reporting
✅ **Comprehensive documentation** and examples
✅ **Demo data generation** for testing
✅ **Production-ready architecture** (with security enhancements)

The system provides **clear visibility** into which users and sessions are sending private data, what types of sensitive information are being detected, and enables security officers to **monitor and analyze privacy compliance** effectively.

---

**🛡️ Sentinel Telemetry Dashboard - Advanced MVP Complete**
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