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Un{i}packer PyPI: unipacker Docker Cloud Build Status DOI

Master Build Status
Dev Build Status

Unpacking PE files using Unicorn Engine

The usage of runtime packers by malware authors is very common, as it is a technique that helps to hinder analysis. Furthermore, packers are a challenge for antivirus products, as they make it impossible to identify malware by signatures or hashes alone.

In order to be able to analyze a packed malware sample, it is often required to unpack the binary. Usually this means, that the analyst will have to manually unpack the binary by using dynamic analysis techniques (Tools: OllyDbg, x64Dbg). There are also some approaches for automatic unpacking, but they are all only available for Windows. Therefore when targeting a packed Windows malware the analyst will require a Windows machine. The goal of our project is to enable platform independent automatic unpacking by using emulation that yields runnable Windows binaries.

Fully supported packers

  • ASPack: Advanced commercial packer with a high compression ratio
  • FSG: Freeware, fast to unpack
  • MEW: Specifically designed for small binaries
  • MPRESS: Free, more complex packer
  • PEtite: Freeware packer, similar to ASPack
  • UPX: Cross-platform, open source packer
  • YZPack

Other packers

Any other packers should work as well, as long as the needed API functions are implemented in Un{i}packer. For packers that aren't specifically known you will be asked whether you would like to manually specify the start and end addresses for emulation. If you would like to start at the entry point declared in the PE header and just emulate until section hopping is detected, press Enter


We are humbled to see some active usage of Un{i}packer for research projects, university courses and other resources that teach students about malware obfuscation:

  • Tutorial video belonging to the Master's course "Malware Analysis and Cyber Threat Intelligence" at the Westphalian University, demonstrating how to analyze obfuscated malware with Un{i}packer
  • DeepReflect: Paper presenting a tool for localizing and identifying malware components within a malicious binary. Its dataset relies on a Un{i}packer preprocessing step
  • BDHunter: Paper describing a system that automatically identifies behavior dispatchers to assist triggering malicious behaviors. The tool requires unpacked malware samples as input, where the authors propose using Un{i}packer
  • JARV1S Disassembler: Disassembler that uses Un{i}packer as a preprocessing step
  • Anti-Anti-Virus 2 lecture of University of Virginia's "CS 4630: Defense Against the Dark Arts", using Un{i}packer as an example for unpacking techniques
  • Mastering Malware Analysis: The second edition of this comprehensive guide to malware analysis by Alexey Kleymenov and Amr Thabet also explains how unpacking and deobfuscation works, mentioning Un{i}packer as a suitable tool for several popular packers

If you are using Un{i}packer for additional projects and would like them featured in this list, we would love to hear from you!


Normal installation

Install the YARA package for your OS, get Un{i}packer from PyPi and start it using the automatically created command line wrapper:

pip3 install unipacker

For detailed instructions on how to use Un{i}packer please refer to the Wiki. Additionally, all of the shell commands are documented. To access this information, use the help command

You can take a quick look at Un{i}packer in action in a (german) video by Prof. Chris Dietrich

Development mode installation

Clone the repository, and inside the project root folder activate development mode using pip3 install -e .

Using Docker

You can also use the provided Dockerfile to run a containerized version of Un{i}packer:

docker run -it -v ~/local_samples:/root/unipacker/local_samples vfsrfs/unipacker

Assuming you have a folder called local_samples in your home directory, this will be mounted inside the container. Un{i}packer will thus be able to access those binaries via /root/unipacker/local_samples


A 3rd party wrapper created by @rpgeeganage allows to unpack samples by sending a request to a RESTful server: