Exploring Network Traffic With Python And Wireshark

Introduction

In this blog post, we will explore how to analyze network traffic using Python and Wireshark. We will focus on extracting useful information from packet capture (PCAP) files using the PyShark library. Later, we will visualize this data.

Requirements

To follow along with this tutorial, you will need:

• Python 3.x
• Wireshark
• PyShark library

To install PyShark, you can use pip:

pip install pyshark

Capturing Network Traffic

First, we need to capture network traffic. You can use Wireshark or another network analyzer tool for this purpose. Once you have captured the traffic, save it as a .pcap file.

Analyzing PCAP Files with PyShark

PyShark is a Python wrapper for the Wireshark library that allows you to access and manipulate packet data directly in Python. Let's start by reading a PCAP file and printing the packet information:

import pyshark

# Load the pcap file
cap = pyshark.FileCapture('example.pcap')

# Iterate through packets and print some information
for packet in cap:
    print(f"Packet #{packet.number}: {packet.highest_layer}")

This code snippet will read the example.pcap file and print each packet's number and highest-layer protocol.

Extracting Useful Information

Now that we can access the packet data, let's extract useful information such as IP addresses, packet length, and timestamps:

ip_addresses = []

for packet in cap:
    # Get packet layers
    layers = packet.layers()

    # Check if the packet has an IP layer
    if 'IP' in [layer.layer_name for layer in layers]:
        src_ip = packet.ip.src
        dst_ip = packet.ip.dst
        length = packet.length
        timestamp = packet.sniff_time

        ip_addresses.append({
            'src_ip': src_ip,
            'dst_ip': dst_ip,
            'length': length,
            'timestamp': timestamp
        })

print(ip_addresses)

This code snippet will create a list of dictionaries containing the source IP, destination IP, packet length, and timestamp for each IP packet.

Visualizing Network Traffic

We can visualize this data in various ways to get insights into the network traffic. For this example, we will use the matplotlib library to create a scatter plot of packet sizes over time:

import matplotlib.pyplot as plt

# Separate x and y values (timestamps and packet lengths)
x_values = [ip_info['timestamp'] for ip_info in ip_addresses]
y_values = [int(ip_info['length']) for ip_info in ip_addresses]

# Create a scatter plot
plt.scatter(x_values, y_values)

# Add labels and titles
plt.xlabel("Timestamp")
plt.ylabel("Packet Size (bytes)")
plt.title("Packet Sizes Over Time")

# Display the plot
plt.show()

This plot can provide useful insights into the network traffic, such as identifying patterns or anomalies.

Conclusion

In this blog post, we explored how to analyze network traffic using Python and Wireshark with the PyShark library. We also demonstrated how to extract useful information from PCAP files and visualize it. This is just the beginning—there is much more you can do with PyShark and Wireshark to gain valuable insights into network traffic and improve network performance and security.