Introduction to Dissect
Digital forensics and incident response play a crucial role in investigating cybercrimes and security breaches.
The ability to quickly access and analyze forensic artifacts from different disk and file formats is essential for effective investigations. This is where Dissect comes into the picture.
Dissect is a powerful digital forensics and incident response framework that enables analysts to efficiently examine and interpret evidence from a wide range of sources.
In this article, we will explore the capabilities of Dissect and how it simplifies the process of accessing and analyzing forensic artifacts.
This project is a meta package, it will install all other Dissect modules with the right combination of versions.
For more information, please see the documentation.
Digital forensics, often referred to as cyber forensics, is the meticulous process of uncovering, preserving, and analyzing digital evidence for investigative purposes. It plays a pivotal role in both criminal investigations and cybersecurity incidents. Here, we shed light on the key aspects of digital forensics.
Incident response complements digital forensics by providing a systematic approach to managing and mitigating security incidents.
What is Dissect?
Dissect is an open-source project developed by Fox-IT, now part of NCC Group. It is a comprehensive collection of Python libraries and tools that facilitate enterprise-scale incident response and forensics.
The primary objective of Dissect is to provide analysts with the necessary resources to acquire, normalize, process, and analyze digital evidence. It allows analysts to focus on analysis, plugin development, and research, rather than worrying about accessing and managing investigation data.
Dissect is an incident response framework built from various parsers and implementations of file formats. Tying this all together, it allows you to work with tools named
target-shell to quickly gain access to forensic artifacts, such as Runkeys, Prefetch files, and Windows Event Logs, just to name a few!
Key Features and Capabilities:
And the best thing: all in a singular way, regardless of underlying container (E01, VMDK, QCoW), filesystem (NTFS, ExtFS, FFS), or Operating System (Windows, Linux, ESXi) structure/combination. You no longer have to bother extracting files from your forensic container, mount them (in case of VMDKs and such), retrieve the MFT, and parse it using a separate tool, to finally create a timeline to analyze. This is all handled under the hood by Dissect in a user-friendly manner.
If we take the example above, you can start analyzing parsed MFT entries by just using a command like
target-query -f mft <PATH_TO_YOUR_IMAGE>!
Create a lightweight container using Acquire
Dissect also provides you with a tool called
acquire. You can deploy this tool on endpoint(s) to create a lightweight container of these machine(s). What is convenient as well, is that you can deploy
acquire on a hypervisor to quickly create lightweight containers of all the (running) virtual machines on there! All without having to worry about file-locks.
These lightweight containers can then be analyzed using tools like
target-shell, but feel free to use other tools as well. This allows for easy analysis without the need to extract files or worry about file locks, further streamlining the investigation process.
A modular setup
Dissect is made with a modular approach in mind. This means that each individual project can be used on its own (or in combination) to create a completely new tool for your engagement or future use. This flexibility enhances the adaptability of the framework to different forensic scenarios.
Try it out now!
Interested in trying it out for yourself? You can simply
pip install dissect start using the
target-* tooling right away. Or you can use the interactive playground at https://try.dissect.tools to try Dissect in your browser.
Dissect currently consists of the following projects.
These projects are closely related to the tool, but not installed by this meta package.
This project is part of the Dissect framework and requires Python.
Information on the supported Python versions can be found in the Getting Started section of the documentation.
dissect is available on PyPI.
Build and test instructions
This project uses
tox to build source and wheel distributions. Run the following command from the root folder to build these:
The build artifacts can be found in the
tox is also used to run linting and unit tests in a self-contained environment. To run both linting and unit tests using the default installed Python version, run:
For a more elaborate explanation on how to build and test the project, please see the documentation.