working well, good docs. TUI.
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README.md
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README.md
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# StreamLens - Ethernet Traffic Analyzer
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Advanced TUI-based network traffic analyzer for pcap files and live streams with specialized protocol dissection for aviation and industrial networks. Features sigma-based outlier identification and real-time statistical analysis.
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## Quick Start
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```bash
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# Install dependencies
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pip install scapy numpy
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# Analyze pcap file with TUI (flows sorted by largest sigma outliers)
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python ethernet_analyzer_modular.py --pcap file.pcap
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# Live capture with real-time statistics
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python ethernet_analyzer_modular.py --live --interface eth0
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# Console output with outlier reporting
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python ethernet_analyzer_modular.py --pcap file.pcap --no-tui
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# Generate comprehensive outlier report
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python ethernet_analyzer_modular.py --pcap file.pcap --report
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# Get pcap file information
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python ethernet_analyzer_modular.py --pcap file.pcap --info
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# Adjust outlier threshold (default: 3.0 sigma)
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python ethernet_analyzer_modular.py --pcap file.pcap --outlier-threshold 2.0
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# With BPF filter for live capture
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python ethernet_analyzer_modular.py --live --filter "port 319 or port 320"
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```
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## Features
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### Enhanced TUI Interface
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- **Three-Panel Layout**: Flows list (top-left), flow details (top-right), timing visualization (bottom)
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- **Sigma-Based Flow Sorting**: Flows automatically sorted by largest outlier sigma deviation
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- **Real-time Navigation**: Arrow keys to navigate between flows with instant detail updates
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- **Protocol-aware Display**: Shows detected protocols in flow list and details
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- **Smart Protocol Detection**: Prioritizes specialized protocols (Chapter 10, PTP, IENA) over generic ones
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- **Detailed Outlier Analysis**: Individual rows showing frame numbers and exact time deltas for outlier packets
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- **Visual Timeline**: ASCII timeline showing frame timing deviations with outlier highlighting
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- **Live Statistics**: Real-time running averages and outlier detection during capture
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### Core Analysis Engine
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- **Flow-based Analysis**: Groups packets by source-destination IP pairs with timing statistics
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- **Configurable Outlier Detection**: Adjustable sigma threshold (default: 3.0σ)
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- **Multi-layer Protocol Analysis**: Ethernet, IP, UDP, TCP with specialized dissectors
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- **Real-time Statistical Updates**: Running statistics for live capture mode
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- **High Jitter Flow Identification**: Coefficient of variation analysis
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### Specialized Protocol Dissectors
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- **Chapter 10 (IRIG 106-17)**: Complete packet dissection including data types, timestamps, and payload analysis
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- **PTP (IEEE 1588-2019)**: Precision Time Protocol message parsing with sync, delay, and announce messages
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- **IENA (Airbus)**: Industrial Ethernet Network Architecture with P/D/N/M/Q message types
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### Protocol Detection & Fallbacks
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- Automatic protocol identification based on port numbers and packet structure
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- Fallback to common protocols: HTTP, HTTPS, SSH, DNS, DHCP, NTP, SNMP, IGMP, ICMP
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- Multicast detection for aviation/industrial networks
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- Enhanced error handling and validation
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## Installation
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```bash
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# Clone or download the project
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cd streamlens
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# Install dependencies
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pip install scapy numpy
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# Run the analyzer
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python ethernet_analyzer_modular.py --help
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```
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## Key Features Highlights
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### 🎯 Sigma-Based Flow Prioritization
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Flows are automatically sorted by their largest outlier sigma deviation, putting the most problematic flows at the top of the list for immediate attention.
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### 📊 Real-time Statistics
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Live capture mode provides running averages and outlier detection as packets arrive, with TUI updates every 500ms.
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### 🔍 Configurable Analysis
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Adjust outlier detection sensitivity with `--outlier-threshold` (default: 3.0σ) to fine-tune analysis for your specific network conditions.
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### 📈 Comprehensive Reporting
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Generate detailed outlier reports with `--report` flag showing frame-by-frame sigma deviations and timing analysis.
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## TUI Controls
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- **↑↓**: Navigate between flows in main view
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- **d**: Switch to frame dissection view
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- **m** or **ESC**: Return to main view
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- **q**: Quit application
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## Timeline Visualization
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The bottom panel displays a visual timeline of the selected flow's timing behavior:
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- **Horizontal axis**: Progression through packet sequence
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- **Vertical axis**: Deviation from average inter-arrival time (centered on average)
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- **Characters**: `·` = normal timing, `•`/`○` = moderate deviation, `█`/`▄` = outliers
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- **Scale**: Automatically adjusts to show full range of deviations
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- **Info bar**: Shows total frames, deviation range, and outlier count
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## Project Structure
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```
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streamlens/
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├── ethernet_analyzer_modular.py # Main entry point
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├── analyzer/ # Core analysis package
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│ ├── main.py # CLI argument handling and main logic
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│ ├── analysis/ # Analysis engine
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│ │ ├── core.py # Main analyzer class
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│ │ ├── flow_manager.py # Flow tracking and management
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│ │ └── statistics.py # Statistical analysis and outlier detection
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│ ├── models/ # Data structures
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│ │ ├── flow_stats.py # Flow and frame type statistics
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│ │ └── analysis_results.py # Analysis result containers
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│ ├── protocols/ # Protocol dissectors
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│ │ ├── base.py # Base dissector interface
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│ │ ├── chapter10.py # IRIG106 telemetry protocol
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│ │ ├── ptp.py # IEEE 1588 Precision Time Protocol
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│ │ ├── iena.py # Airbus IENA protocol
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│ │ └── standard.py # Standard protocol detection
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│ ├── tui/ # Text User Interface
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│ │ ├── interface.py # Main TUI controller
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│ │ ├── navigation.py # Navigation handling
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│ │ └── panels/ # UI panel components
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│ │ ├── flow_list.py # Flow list panel
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│ │ ├── detail_panel.py # Flow details panel
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│ │ └── timeline.py # Timeline visualization panel
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│ └── utils/ # Utility modules
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│ ├── pcap_loader.py # PCAP file handling
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│ └── live_capture.py # Live network capture
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└── *.pcapng # Sample capture files
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```
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