| | --- |
| | license: mit |
| | task_categories: |
| | - text-classification |
| | tags: |
| | - malware |
| | - code |
| | - decompiled |
| | pretty_name: malware dataset code and decompiled C pseudocode |
| | size_categories: |
| | - n<1K |
| | --- |
| | # 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.c` extension** |
| | - 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. |
