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Local Packet Whisperer (LPW)

Local Packet Whisperer (LPW) is an innovative project designed to facilitate local and private interactions with PCAP/PCAG NG files using a combination of Ollama, Streamlit, and PyShark. This tool serves as a 100% local assistant powered by customizable local large language models (LLMs), with features including Streamlit for the front end and PyShark for packet parsing, LPW is easily installable via pip, allowing users to seamlessly connect to an Ollama server over a network

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DOI

If you are using this project as part of your research, kindly consider citing this project as follow:

[1]V. Kumar, “Local Packet Whisperer (LPW)”. Zenodo, Nov. 30, 2024. doi: 10.5281/zenodo.14251995.

Features

  1. 100% local, private PCAP assistant powered by range of local LLMs at your control, powered by Ollama
  2. Uses streamlit for the FE and pyshark for the pcap parsing needs
  3. Available as a pip installable package. So just pip it away! 😎
  4. Connect LPW to a Ollama server running over a network.
  5. Experimental Support for Agentic Insights (NGAP only for now).

Refer Release History for more details info on what each release contains.

Requirements

  1. Download & Install Ollama by referring to instructions according to your OS here

  2. Pull any Chat based LLM models to use with LPW.

ollama pull dolphin-mistral:latest
  1. If not running the desktop application, Start Ollama Server (refer here)

  2. You also need to install tshark executable. You could either install the Wireshark Application or simply use brew install tshark.

    ⚠️Warning⚠️ If you don't perform this step, you may see below error
    TSharkNotFoundException: TShark not found. Try adding its location to the configuration file.
    

Installation & Usage

  1. Install/Upgrade LPW using pip
pip install -U lpw
  1. This will install lpw CLI in your machine. Now simply Start or Stop LPW as follows:
lpw {start or stop}
lpw -h #for help

Refer User Guide for more details.

Local Development

  1. Clone this repo and install requirements
git clone https://github.com/kspviswa/local-packet-whisperer.git
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
  1. Run streamlit app & point to http://localhost:8501
streamlit run bin/lpw_main.py

or simply

<lpw dir>/bin/lpw {start or stop}

Contributions

I just created this project based on inspiration from similar project called Packet Buddy which used open AI. But if you find this useful and wanna contribute bug fixes, additional features feel free to do so by raising a PR or open issues for me to fix. I intend to work on this as a hobby unless there is some interest in the community.

Metadata

Release files for lpw 0.2.5.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for lpw 0.2.5.0
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lpw-0.2.5.0-py3-none-any.whl Python 3 none any Details

Release files / lpw-0.2.5.0-py3-none-any.whl

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0.2.5.0 This release

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0.2.4.2

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0.2.4

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0.2.3

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0.2.1

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0.2.0

1 release file

0.1.3

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0.1.1

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0.1.0

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