Skip to content

Latest commit

 

History

History
92 lines (57 loc) · 2.01 KB

README.md

File metadata and controls

92 lines (57 loc) · 2.01 KB

parse_ntds.py

parse_ntds.py is a Python script designed to parse an NTDS.dit file and export its content into CSV files. This tool provides a comprehensive way to extract and analyze data from NTDS files.

Install

Before using the script, ensure you have all the necessary dependencies installed. You can install them using pip:

cd scripts/
pip install -r requirements.txt

Usage

To display the help message and see all available options, run:

python parse_ntds.py -h

Command-line Arguments

  • -h, --help
    Show the help message and exit.

  • -f NTDS_FILE, --file NTDS_FILE
    Required: Path to the ntds.dit file.

  • -s SYSTEM_FILE, --system SYSTEM_FILE
    Required: Path to the SYSTEM hive file.

  • -d DOMAIN, --domain DOMAIN
    Domain name.

  • -o OUTPUT_DIR, --output OUTPUT_DIR
    Output directory. Default is the current directory.

  • -v, --verbose
    Increase output verbosity to DEBUG level.

  • --dump-all
    Dump all data except ACL (default).

  • --dump-users
    Dump user data.

  • --dump-groups
    Dump group data.

  • --dump-trusts
    Dump trust data.

  • --dump-domains
    Dump domain data.

  • --dump-ou
    Dump OU/container data.

  • --dump-acl
    Dump ACL data (required -d option).

Example

To parse an NTDS.dit file and export all data to CSV files in the current directory with verbose output:

python parse_ntds.py -f /path/to/ntds.dit -s /path/to/SYSTEM -v --dump-all

To dump only user and group data:

python parse_ntds.py -f /path/to/ntds.dit -s /path/to/SYSTEM --dump-users --dump-groups

To dump all with ACL:

python parse_ntds.py -f /path/to/ntds.dit -s /path/to/SYSTEM --dump-acl -d <domain_name>

About

This script was presented at the Troopers conference 2024. For more information about the conference, visit Troopers 2024.


Feel free to contribute to this project by submitting issues or pull requests. Your feedback and contributions are highly appreciated.