Packet Sniffer Built From Scratch

SniffDog is a lightweight packet-sniffing tool built in Python that captures and analyzes network traffic on Ethernet networks. The project was intentionally developed without any external dependencies, relying entirely on Python's standard library and Linux raw sockets.

The primary objective of this project was to gain a practical understanding of how network traffic moves across different layers of the networking stack. Rather than using established packet analysis frameworks, packet parsing was implemented manually to explore protocol structures, header formats, and low-level networking concepts in greater depth.

While studying computer networking, I wanted to move beyond theoretical concepts and observe how packets are transmitted and processed in real-world environments. Although tools such as Wireshark offer powerful packet inspection capabilities, much of the underlying packet processing remains abstracted from the user.

Building SniffDog from scratch provided an opportunity to examine raw packet data directly, understand protocol encapsulation, and learn how operating systems interact with network interfaces at a low level.

Technical Concepts Explored

• Raw socket programming in Linux
• Ethernet frame structure
• MAC addressing and frame delivery
• IPv4 packet header analysis
• Protocol identification and classification
• TCP, UDP, and ICMP traffic inspection
• Packet payload extraction and analysis
• Network traffic monitoring techniques
• Command-line interface development

Packet Capture Architecture

SniffDog captures packets directly from the network interface using Linux raw sockets. By accessing Ethernet frames before they are processed by higher layers of the operating system, the application can inspect and analyze network traffic in its original form.

socket.socket(socket.AF_PACKET, socket.SOCK_RAW, socket.ntohs(3))

This raw socket configuration enables the application to receive all Ethernet frames traversing the selected network interface, making it possible to inspect traffic at the packet level.

Packet Processing Pipeline

Captured packets pass through a multi-stage parsing process designed to extract meaningful information from raw binary data.

• Ethernet Frame Parsing
  • Source MAC address
  • Destination MAC address
  • EtherType identification
• IPv4 Header Analysis
  • IP version
  • Header length
  • Time To Live (TTL)
  • Protocol type
  • Source IP address
  • Destination IP address
• Transport Layer Inspection
  • TCP traffic
  • UDP traffic
  • ICMP packets
• Payload Extraction
  • Raw packet payload display
  • Traffic inspection and analysis

Features

• Detailed Packet Inspection – Displays Ethernet, IPv4, and transport layer information for captured packets.
• Traffic Logging – Supports logging captured packets to a file for later analysis.
• Keep-Alive Filtering – Optional command-line flag to include or exclude keep-alive packets during monitoring.
• No External Dependencies – Built entirely with Python's built-in libraries to maximize learning and transparency.

Challenges Encountered

Developing SniffDog introduced several challenges, particularly around understanding raw sockets and the Linux networking stack. Learning why elevated privileges are required and how packets are exposed to user-space applications provided valuable insight into operating system networking internals.

Another major challenge involved parsing protocol headers correctly. Converting raw byte streams into structured information required careful study of protocol specifications and binary data formats.

Testing the application across different environments also revealed how virtualization, network interface configurations, and operating system behavior can affect packet visibility and traffic capture.

Key Learnings

• Linux networking fundamentals
• Packet-level communication mechanisms
• Protocol analysis and inspection
• Binary data parsing techniques
• Network troubleshooting workflows
• Systems programming concepts

Most importantly, the project provided hands-on experience with how data travels across networks and how security professionals inspect and analyze network traffic during troubleshooting and investigations.

Future Improvements

• Advanced packet filtering capabilities
• Support for additional network protocols
• PCAP file export functionality
• Traffic statistics and analytics dashboards
• Interactive search and filtering tools

Repository

Source code and project documentation are available on GitHub: https://github.com/p4th4k/SniffDog