DataSurgeon - Quickly Extracts IP's, Email Addresses, Hashes, Files, Credit Cards, Social Secuirty Numbers And More From Text

 DataSurgeon (ds) is a versatile tool designed for incident response, penetration testing, and CTF challenges. It allows for the extraction of various types of sensitive information including emails, phone numbers, hashes, credit cards, URLs, IP addresses, MAC addresses, SRV DNS records and a lot more!

• Supports Windows, Linux and MacOS

Extraction Features

• Emails
• Files
• Phone numbers
• Credit Cards
• Google API Private Key ID's
• Social Security Numbers
• AWS Keys
• Bitcoin wallets
• URL's
• IPv4 Addresses and IPv6 addresses
• MAC Addresses
• SRV DNS Records
• Extract Hashes
  • MD4 & MD5
  • SHA-1, SHA-224, SHA-256, SHA-384, SHA-512
  • SHA-3 224, SHA-3 256, SHA-3 384, SHA-3 512
  • MySQL 323, MySQL 41
  • NTLM
  • bcrypt

Want more?

Please read the contributing guidelines here

Quick Install

Install Rust and Github

Linux

wget -O - https://raw.githubusercontent.com/Drew-Alleman/DataSurgeon/main/install/install.sh | bash

Windows

Enter the line below in an elevated powershell window.

IEX (New-Object Net.WebClient).DownloadString("https://raw.githubusercontent.com/Drew-Alleman/DataSurgeon/main/install/install.ps1")

Relaunch your terminal and you will be able to use ds from the command line.

Mac

curl --proto '=https' --tlsv1.2 -sSf https://raw.githubusercontent.com/Drew-Alleman/DataSurgeon/main/install/install.sh | sh

Command Line Arguments

Video Guide

Examples

Extracting Files From a Remote Webiste

Here I use wget to make a request to stackoverflow then I forward the body text to ds . The -F option will list all files found. --clean is used to remove any extra text that might have been returned (such as extra html). Then the result of is sent to uniq which removes any non unique files found.

 wget -qO - https://www.stackoverflow.com | ds -F --clean | uniq

Extracting Mac Addresses From an Output File

Here I am pulling all mac addresses found in autodeauth's log file using the -m query. The --hide option will hide the identifer string infront of the results. In this case 'mac_address: ' is hidden from the output. The -T option is used to check the same line multiple times for matches. Normallly when a match is found the tool moves on to the next line rather then checking again.

$ ./ds -m -T --hide -f /var/log/autodeauth/log     
2023-02-26 00:28:19 - Sending 500 deauth frames to network: BC:2E:48:E5:DE:FF -- PrivateNetwork
2023-02-26 00:35:22 - Sending 500 deauth frames to network: 90:58:51:1C:C9:E1 -- TestNet

Reading all files in a directory

The line below will will read all files in the current directory recursively. The -D option is used to display the filename (-f is required for the filename to display) and -e used to search for emails.

$ find . -type f -exec ds -f {} -CDe \;

Speed Tests

When no specific query is provided, ds will search through all possible types of data, which is SIGNIFICANTLY slower than using individual queries. The slowest query is --files. Its also slightly faster to use cat to pipe the data to ds.

Below is the elapsed time when processing a 5GB test file generated by ds-test. Each test was ran 3 times and the average time was recorded.

Computer Specs

Processor	Intel(R) Core(TM) i5-10400F CPU @ 2.90GHz, 2904 Mhz, 6 Core(s), 12 Logical Processor(s)
Ram         12.0 GB (11.9 GB usable)

Searching all data types

Using specific queries

Project Goals

• JSON and CSV output
• Untar/unzip and a directorty searching mode
• Base64 Detection and decoding

Zenbuster - Multi-threaded URL Enumeration/Brute-Forcing Tool

ZenBuster is a multi-threaded, multi-platform URL enumeration tool written in Python by Zach Griffin (@0xTas).

I wrote this tool as a way to deepen my familiarity with Python, and to help increase my understanding of Cybersecurity tooling in general. ZenBuster may not be the fastest or most comprehensive tool of its kind. It is however, simple to use, decently flexible, and in practice only marginally slower than other "tried-and-true" tools like Gobuster. Personally, I have been using it to help me solve CTF challenges on platforms like TryHackMe, and have found my implementation to be satisfactorily reliable.

This software is intended for use in CTF challenges, or by security professionals to gather information on their targets:

• It is capable of brute-force enumerating subdomains and also URI resources (directories/files).
• Both methods of enumeration require use of an appropriate wordlist or dictionary file.
• Features Include:
  1. Hostname format supports standard, IPv4, and IPv6.
  2. Support for logging results to a file with -O [filename].
  3. Specifying custom ports for nonstandard webservers with -p .
  4. Optional file extensions in directory mode with -x .
  5. Quiet mode for less distracting output with -Q.
  6. Color can be disabled for less distracting output with -nc/-nl.
  7. Tested on Python versions 3.9 and 3.10, with theoretical support for versions >= 3.6

CAUTION/DISCLAIMER

ZenBuster is capable of producing a potentially unwelcome number of HTTP requests in a short amount of time.

The developers and contributors are not liable or responsible for any damage caused by misuse or abuse of this software.

Please Enumerate Responsibly!

License

ZenBuster is licensed under the GNU GPLv3 License, see here for more information.

Credits

Yin-Yang ASCII art in the banners were created by Joan G. Stark (jgs) and Hayley Jane Wakenshaw (hjw). Modifications were made by me, when specified with: 'zg'.

Installation

Firstly, ensure that Python version >= 3.6 is installed, then clone the repository with:

git clone https://github.com/0xTas/zenbuster.git

Next, cd zenbuster.

Dependencies

ZenBuster relies on 3 external libraries to function, and it is recommended to install these with:

pip install -r requirements.txt

The modules that will be installed and their purposes are as follows:

1. Python requests

   • The backbone of each enumeration request. Without this, the script will not function.

2. termcolor

   • Enables colored terminal output. Non-critical, the script can still run without color if this is not present.

3. colorama (Windows only)

   • Primes the Windows terminal to accept ANSI color codes (from Termcolor). Non-critical.

These dependencies may be installed manually, with pip using requirements.txt, or via interaction with the script upon first run.

Usage

Once dependencies have been installed, you can run the program in the following ways:

On Linux (+Mac?):

./zenbuster.py [options] or python3 zenbuster.py [options]

On Windows:

python zenbuster.py [options]

[Options]

Example Usage

./zenbuster.py -d -w /usr/share/wordlists/dirb/common.txt -u target.thm -v

python3 zenbuster.py -w ../subdomains.txt --host target.thm --ssl -O myResults.log

zenbuster -w subdomains.txt -u target.thm --quiet (With .bashrc alias)

Planned Features/Improvements

• Increased levels of optional verbosity.
• Allow optional throttling of task thread-count.
• Allow users to modify the list of ignored status codes.
• Allow greater user control over various request headers.
• Allow optional ignoring of responses based on content-length.
• Expand subdomain enumeration to include OSINT methods instead of just brute-forcing.
• Explore a more comprehensive and source-readable solution to fancy colored output (possibly using rich).

Known Issues/Limitations

• Enumerating long endpoints may result in ugly terminal output due to line-wraping on smaller console windows. Logging to a file is recommended, especially on Windows.
• If target host is a vHost on a shared webserver, enumeration via IP may not function as expected. Use domain/hostname instead.