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Malware Source Code and Decompiled C Pseudocode Dataset
Overview
This repository contains a curated dataset of malware source codes and C-like pseudocode obtained through automated decompilation using Ghidra, the reverse engineering framework developed by the NSA.
The dataset is intended for malware analysis, program analysis research, machine learning / LLM-based malware detection, and reverse engineering experiments.
Data Origin
The data is based on the following archive:
- VXUnderground Archive
- Old APT Collection
- Archive version:
2024.7z
VXUnderground is a well-known public repository that aggregates malware samples from various threat actor groups and historical campaigns.
Decompilation Scope and Limitations
⚠️ Important Notice
Due to computational resource constraints, not all executable files from the original VXUnderground archive were decompiled.
- Only a subset of executable malware samples was processed
- Decompilation was performed using Ghidra in headless mode
- Some binaries may be missing corresponding decompiled outputs
- The dataset should not be considered complete or exhaustive
This selective decompilation approach was chosen to balance dataset size with practical feasibility.
Repository Structure
.
├── code/
│ └── * (malware source code files without file extensions)
│
├── decompiled/
│ └── *.decomp.c (C-like pseudocode generated by Ghidra)
│
└── README.md
code/
- Contains original malware source code
- All files have no file extensions
- Files originate directly from the VXUnderground archive
- Code may be incomplete, obfuscated, or inconsistent in formatting
decompiled/
- Contains C-like pseudocode produced by Ghidra
- All files use the
.decomp.cextension - Represents decompiled versions of selected executable malware samples
- Output reflects:
- Ghidra’s internal analysis
- Heuristics and limitations of automated decompilation
- The code is not guaranteed to compile and may contain artifacts introduced by the decompiler
Intended Use Cases
This dataset can be used for:
- Malware classification (malware vs benign)
- Program comprehension and reverse engineering research
- Training and evaluation of:
- Large Language Models (LLMs)
- Recursive Language Models (RLMs)
- Static analysis pipelines
- Malware family analysis and feature extraction
- Source code ↔ pseudocode alignment tasks
Disclaimer
⚠️ Warning
- This repository contains real malware code
- The code is provided strictly for research and educational purposes
- Do NOT compile or execute any files unless in a properly isolated environment (e.g., sandbox, VM)
- The authors take no responsibility for misuse or damage caused by this dataset
License and Attribution
- Original malware samples are attributed to VXUnderground
- Ghidra is developed and maintained by the National Security Agency (NSA)
- This dataset is a derived work created for research purposes only
If you use this dataset in academic work, please cite:
- VXUnderground as the original data source
- Ghidra as the decompilation tool
Contact
For questions, issues, or collaboration related to this dataset, please open an issue or contact the repository maintainer.
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