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Coover

Configuration environment

Step 1: Install Hashcat

For Windows

  1. Download the latest Hashcat binaries from the official Hashcat website.
  2. Extract the contents of the zip file to a folder of your choice.

For macOS and Linux

Install Hashcat through the package manager:

On macOS with Homebrew: brew install hashcat
On Linux (Debian-based): sudo apt install hashcat

This project is based on Hashcat v6.2.6.

Step 2: Requirements

The required libraries are listed inside requirements.txt placed in the base folder. You can use pip install -r requirements.txt to setup all the required libraries.

Cookie Value Learning Algorithm

bash cookie_value_learning_algorithm.sh

Run this file to obtain the ful output of the cookie value analysis. As the final output, the algorithm will generate a csv file containing all learned segments for the cookie values.

Phase 1: Cookie Value Pre-processing

cookie_value_pre_processing.py: Run this file to pre-processing all input cookie values. The input for this phase is the collected cookie values (default as: /Dataset/all_collected_cookies.xlsx). The output is default as the 1_decoded_cracked_example_crawl.csv.

Phase 2: Rules-Based Patterns Extraction

rules_based_patterns_extraction.py: Run this file to extract all fixed patterns in cookie values. The input for this phase is pre-processed cookie values from Phase 1 (default as: 1_decoded_cracked_example_crawl.csv). The output is default as the 2_filtered_rules_based_patterns.csv to the remaining cookie values and the extracted segments are saved in all_segments_date_pattern.txt, all_segments_ipv4_pattern.txt, all_segments_uuid_pattern.txt, all_segments_url_or_domain_pattern.txt.

Pre-processing with Delimiter

pre_processing_with_delimiter.py: The input for this phase is from the Phase 2 (default as: 2_filtered_rules_based_patterns.csv). The output is default as the 3_final_separated_data.csv to the remaining cookie values and the extracted segments are saved in all_segments_date_pattern.txt, all_segments_ipv4_pattern.txt, all_segments_uuid_pattern.txt, all_segments_url_or_domain_pattern.txt.

Plain-texts Recognition

plain_texts_recognition.py: The input for this phase is default as: 3_final_separated_data.csv. The output contains two files named 3_all_plain_texts.csv and 3_all_non_plain_texts.csv.

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