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subparse — Modular malware analysis artifact collection and correlation framework | Kitploit
Tools/GitHubGitHub/jstrosch/subparse
Static AnalysisDynamic Analysis (Sandboxing)ForensicsInformation GatheringMalware AnalysisThreat Intelligence
GitHubjstrosch/subparse

subparse

Modular malware analysis artifact collection and correlation framework

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5612112 years agoReviewed by Kitploit

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subparse

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Subparse, is a modular framework developed by Josh Strochein, Aaron Baker, and Odin Bernstein. The framework is designed to parse and index malware files and present the information found during the parsing in a searchable web-viewer. The framework is modular, making use of a core parsing engine, parsing modules, and a variety of enrichers that add additional information to the malware indices. The main input values for the framework are directories of malware files, which the core parsing engine or a user-specified parsing engine parses before adding additional information from any user-specified enrichment engine all before indexing the information parsed into an elasticsearch index. The information gathered can then be searched and viewed via a web-viewer, which also allows for filtering on any value gathered from any file. There is currently 3 parsing engine, the default parsing engines (PEParser, OLEParser and ELFParser), and 2 enrichment engines (ABUSEEnricher and CAPEEnricher ).

 

Getting Started

Software Requirements

To get started using Subparse there are a few requrired/recommened programs that need to be installed and setup before trying to work with our software.

SoftwareStatusLink
DockerRequiredInstallation Guide
Python3.8.1RequiredInstallation Guide
PyenvRecommendedInstallation Guide

Additional Requirements

After getting the required/recommended software installed to your system there are a few other steps that need to be taken to get Subparse installed.

Python Requirements
Python requires some other packages to be installed that Subparse is dependent on for its processes. To get the Python set up completed navigate to the location of your Subparse installation and go to the *parser* folder. The following commands that you will need to use to install the Python requirements is:
sudo get apt install build-essential
pip3 install -r ./requirements.txt
Docker Requirements
Since Subparse uses Docker for its backend and web interface, the set up of the Docker containers needs to be completed before being able to use the program. To do this navigate to the root directory of the Subparse installation location, and use the following command to set up the docker instances:
docker-compose up

Note: This might take a little time due to downloading the images and setting up the containers that will be needed by Subparse.

 

Installation steps

  • Installation Steps

Usage

Command Line Options

Command line options that are available for subparse/parser/subparse.py:

ArgumentAlternativeRequiredDescription
-h--helpNoShows help menu
-d SAMPLES_DIR--directory SAMPLES_DIRYesDirectory of samples to parse
-e ENRICHER_MODULES--enrichers ENRICHER_MODULESNoEnricher modules to use for additional parsing
-r--resetNoReset/delete all data in the configured Elasticsearch cluster
-v--verboseNoDisplay verbose commandline output
-s--service-modeNoEnters service mode allowing for mode samples to be added to the SAMPLES_DIR while processing

Viewing Results

To view the results from Subparse's parsers, navigate to localhost:8080. If you are having trouble viewing the site, make sure that you have the container started up in Docker and that there is not another process running on port 8080 that could cause the site to not be available.

 

General Information Collected

Before any parser is executed general information is collected about the sample regardless of the underlying file type. This information includes:

  • MD5 hash of the sample
  • SHA256 hash of the sample
  • Sample name
  • Sample size
  • Extension of sample
  • Derived extension of sample

Parser Modules

Parsers are ONLY executed on samples that match the file type. For example, PE files will by default have the PEParser executed against them due to the file type corresponding with those the PEParser is able to examine.

Default Modules

ELFParser
This is the default parsing module that will be executed against ELF files. Information that is collected:
  • General Information
  • Program Headers
  • Section Headers
  • Notes
  • Architecture Specific Data
  • Version Information
  • Arm Unwind Information
  • Relocation Data
  • Dynamic Tags
OLEParser
This is the default parsing module that will be executed against OLE and RTF formatted files, this uses the OLETools package to obtain data. The information that is collected:
  • Meta Data
  • MRaptor
  • RTF
  • Times
  • Indicators
  • VBA / VBA Macros
  • OLE Objects
PEParser
This is the default parsing module that will be executed against PE files that match or include the file types: PE32 and MS-Dos. Information that is collected:
  • Section code and count
  • Entry point
  • Image base
  • Signature
  • Imports
  • Exports

 

Enricher Modules

These modules are optional modules that will ONLY get executed if specified via the -e | --enrichers flag on the command line.

Default Modules

ABUSEEnricher
This enrichers uses the [Abuse.ch](https://abuse.ch/) API and [Malware Bazaar](https://bazaar.abuse.ch) to collect more information about the sample(s) subparse is analyzing, the information is then aggregated and stored in the Elastic database.
CAPEEnricher
This enrichers is used to communicate with a CAPEv2 Sandbox instance, to collect more information about the sample(s) through dynamic analysis, the information is then aggregated and stored in the Elastic database utilizing the Kafka Messaging Service for background processing.
STRINGEnricher
This enricher is a smart string enricher, that will parse the sample for potentially interesting strings. The categories of strings that this enricher looks for include: Audio, Images, Executable Files, Code Calls, Compressed Files, Work (Office Docs.), IP Addresses, IP Address + Port, Website URLs, Command Line Arguments.
YARAEnricher
This ericher uses a pre-compiled yara file located at: parser/src/enrichers/yara_rules. This pre-compiled file includes rules from VirusTotal and YaraRulesProject

 

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