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A small CLI security toolkit

Project description

GresecML

This command-line tool analyzes network traffic from either a .pcap file or a live capture, and makes predictions using a TensorFlow model. Results can be displayed in the console and/or exported to an HTML file.


⚠️ Important

The predictions are not fully reliable. They are intended for research and exploration only, and should not be used as the sole basis for security or operational decisions.


Features

  • Analyze .pcap files or capture of live network traffic
  • Predict traffic sessions using a TensorFlow model
  • Export results to an HTML report
  • Filter sessions by probability thresholds
  • Support for lazy loading to save memory
  • Verbose mode for detailed console output

Workflow

The prediction pipeline follows these steps:

  1. Capture – Collects packets from a file or live network interface
  2. Sessions – Groups packets into sessions
  3. Prediction – Runs sessions through the TensorFlow model
  4. Output – Displays results in console and/or export to HTML

Installation

Install with pip:

pip install gresecml

Usage

Run the CLI with:

gresecml [OPTIONS] COMMAND [ARGS]...

For help:

gresecml --help

Examples with "gresecml tf predict":

  • Analyze a .pcap file with tensorflow and save results to HTML

    gresecml tf predict -i traffic.pcap -o results.html
    
  • Run live capture on default interface for 60 seconds

    gresecml tf predict
    
  • Run live capture on a specific interface with custom timeout

    gresecml tf predict -if eth0 -t 120
    
  • Enable verbose output and full HTML report

    gresecml tf predict -i traffic.pcap -o results.html -v -efo
    
  • Filter sessions with normal probability ≤ 70%

    gresecml tf predict -i traffic.pcap -pnm 70
    
  • Use lazy loading to save memory

    gresecml tf predict -i traffic.pcap -ll
    

Notes

  • If no --input is provided, the tool defaults to live capture.
  • Lazy loading is recommended for large .pcap files to reduce memory usage.
  • The HTML output provides a structured table of predictions for possible further investigation. The table is sorted by the prediction_normal column.

Example Output

When running with --verbose, predictions will be printed in the console.
If --output is specified, results will also be saved as an HTML file.


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