Hacking News Network Forensics Tool To Analysis a Packet Capture

Published on July 4th, 2019 📆 | 8579 Views ⚑

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Network Forensics Tool To Analysis a Packet Capture

Network Forensics Tool

Network Forensics Tool is often used by security professionals to test the vulnerabilities in the network. With this kali Linux tutorial, we introduce a Comprehensive tool PcapXray to analyze the pcap file.

The tool plots hosts in the network, network traffic, highlight important traffic and Tor traffic as well as potentially malicious traffic.

The tool contains the following components

  • Network Diagram.
  • Device/Traffic Details and Analysis.
  • Malicious Traffic Identification.
  • Tor Traffic
  • GUI – a GUI with options to upload pcap file

Tutorial – Network Forensics Tool 

The packet capture tool can be called from GitHub. The tool gives security officials an initial glitch for investigation.

git clone https://github.com/Srinivas11789/PcapXray.git

cd PcapXray

To install the requirements: pip install -r requirements.txt

To Run : python Source/main.py

It will launch a graphical user interface and ask’s to locate the pcap file.

For demonstration, we have used Netflix phishing campaign’s pcap file, with this tool we can extract the web traffic, Tor traffic, Malicious traffic and other traffic details.

The analysis takes some time, after that, we get detailed report on communication, Device and Packet details.

Network Forensics Tool
Network Forensics Tool
Network Forensics Tool

The location URL detected a Netflix Phishing page.

Network Forensics Tool

And the Destination IP 98[.]209[.]70[.]101 is not resolvable at the time of our analysis, looks like the campaign already ended.

The tool includes following python libraries

Scapy – rdpcap to read the packets from the pcap file
Ipwhois – to obtain whois information from ip
Netaddr – to check ip information type
Pillow – image processing library
Stem – tor consensus data fetch library
pyGraphviz – plot graph
Networkx – plot graph
Matplotlib – plot graph

Demo:

Author Credits Srinivas P G Github.

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