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SubCrawl is a framework developed by Patrick Schläpfer (https://twitter.com/stoerchl), Josh Stroschein (https://twitter.com/jstrosch) and Alex Holland (https://twitter.com/cryptogramfan) of HP Inc’s Threat Research (https://threatresearch.ext.hp.com/blog/) team. SubCrawl is designed to find, scan and analyze open directories. The framework is modular, consisting of four components: input modules, processing modules, output modules and the core crawling engine. URLs are the primary input values, which the framework parses and adds to a queuing system before crawling them. The parsing of the URLs is an important first step, as this takes a submitted URL and generates additional URLs to be crawled by removing sub-directories, one at a time until none remain. This process ensures a more complete scan attempt of a web server and can lead to the discovery of additional content. Notably, SubCrawl does not use a brute-force (https://www.kitploit.com/search/label/Brute-force) method for discovering URLs. All the content scanned comes from the input URLs, the process of parsing the URL and discovery during crawling. When an open directory is discovered, the crawling engine extracts links from the directory for evaluation. The crawling engine determines if the link is another directory or if it is a file. Directories are added to the crawling queue, while files undergo additional analysis by the processing modules. Results are generated and stored for each scanned URL, such as the SHA256 and fuzzy hashes of the content, if an open directory was found, or matches against YARA rules. Finally, the result data is processed according to one or more output modules, of which there are currently three. The first provides integration with MISP, the second simply prints the data to the console, and the third stores the data in an SQLite database. Since the framework is modular, it is not only easy to configure which input, processing and output modules are desired, but also straightforward to develop new modules.

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Figure 1 - SubCrawl architectureSubCrawl supports two different modes of operation. First, SubCrawl can be started in a run-once mode. In this mode, the user supplies the URLs to be scanned in a file where each input value is separated by a line break. The second mode of operation is service mode. In this mode, SubCrawl runs in the background and relies on the input modules to supply the URLs to be scanned. Figure 1 shows an overview of SubCrawl’s architecture. The components that are used in both modes of operation are blue, run-once mode components are yellow, and service mode components are green.
Requirements
Based on the chosen run mode, other preconditions must be met.
Run-Once Mode Requirements
SubCrawl is written in Python3. In addition, there are several packages that are required before running SubCrawl. The following command can be used to install all required packages before running SubCrawl. From the crawler directory, run the following command:$ sudo apt install build-essential
$ pip3 install -r requirements.txt

Service Mode Requirements
If SubCrawl is started in service mode, this can be done using Docker. For this reason, the installation of Docker and Docker Compose is required. Good installation instructions for this can be found directly on the Docker.com website.Installing Docker Engine (https://docs.docker.com/engine/install/ubuntu/)Installing Docker Compose (https://docs.docker.com/compose/install/)
Getting Help
SubCrawl has built-in help through the -h/--help argument or by simply executing the script without any arguments. ******** ** ****** **
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~~ Harvesting the Open Web ~~

usage: subcrawl.py [-h] [-f FILE_PATH] [-k] [-p PROCESSING_MODULES] [-s STORAGE_MODULES]

optional arguments:
-h, --help show this help message and exit
-f FILE_PATH, --file FILE_PATH
Path of input URL file
-k, --kafka Use Kafka Queue as input
-p PROCESSING_MODULES, --processing PROCESSING_MODULES
Processing modules to be executed comma separated.
-s STORAGE_MODULES, --storage STORAGE_MODULES
Storage modules to be executed comma separated.

Available processing modules:
- ClamAVProcessing
- JARMProcessing
- PayloadProcessing
- TLSHProcessing
- YARAProcessing

Available storage modules:
- ConsoleStorage
- MISPStorage
- SqliteStorage

Run-Once Mode
This mode is suitable if you want to quickly scan a manageable amount of domains. For this purpose, the URLs to be scanned must be saved in a file, which then serves as input for the crawler. The following is an example of executing in run-once mode, not the -f argument is used with a path to a file.python3 subcrawl.py -f urls.txt -p YARAProcessing,PayloadProcessing -s ConsoleStorage

Service Mode
With the service mode, a larger amount of domains can be scanned and the results saved. Based on the selected storage module, the data can then be analyzed and evaluated in more detail. To make running the service mode as easy as possible for the user, we built all the functionalities into a Docker image. In service mode, the domains to be scanned are obtained via Input modules. By default, new malware and phishing URLs are downloaded from URLhaus (https://urlhaus.abuse.ch/) and PhishTank (https://www.phishtank.com/) and queued for scanning. The desired processing and storage modules can be entered directly in the config.yml. By default, the following

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Install Docker Engine on Ubuntu

Jumpstart your client-side server applications with Docker Engine on Ubuntu. This guide details prerequisites and multiple methods to install Docker Engine on Ubuntu.

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processing modules are activated, utilizing the SQLite storage:ClamAVProcessingJARMProcessingTLSHProcessingYARAProcessingIn addition to the SQLite storage module, a simple web UI was developed that allows viewing and managing the scanned domains and URLs.

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