JLB-JLB/android-ransomware-gnn-baseline
Graph Machine Learning • Updated • 1
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Android Ransomware FCG Dataset (Baseline)
Binary graph-classification dataset for Android ransomware detection based on function call graphs (FCGs) extracted with Androguard.
Dataset Summary
| Property | Value |
|---|---|
| Total graphs | 715 |
| Benign (label 0) | 502 |
| Malware (label 1) | 213 |
| Class ratio | 2.36 : 1 (benign : malware) |
| Feature dimension | 5 |
Malware Families
| Family | Samples |
|---|---|
| simplelocker | 64 |
| wipelocker | 70 |
| wannalocker | 51 |
| blackroselucy | 17 |
| pletor | 6 |
| filecoder | 5 |
Dataset Variants
internal_only/ — Author-Written Methods Only
Only methods defined in the APK's own code are kept as nodes. External/API calls are encoded as node features on the calling method.
Node features (dim=5):
[is_entrypoint, log_in_degree, log_out_degree, log_api_calls, log_other_ext_calls]
| Statistic | Min | Median | Mean | Max |
|---|---|---|---|---|
| Nodes | 15 | 25,356 | 38,401 | 398,727 |
| Edges | 2 | 31,227 | 51,400 | 989,585 |
full_fcg/ — Complete Function Call Graph
All methods (internal + external/API) are retained as graph nodes.
Node features (dim=5):
[is_external, is_android_api, is_entrypoint, log_in_degree, log_out_degree]
| Statistic | Min | Median | Mean | Max |
|---|---|---|---|---|
| Nodes | 42 | 32,007 | 45,243 | 428,203 |
| Edges | 42 | 65,909 | 98,220 | 1,388,042 |
Data Format
Each .pt file is a Python list of
torch_geometric.data.Data
objects, loadable with torch.load().
Each Data object contains:
x— node feature matrix[num_nodes, 5]edge_index— COO edge list[2, num_edges]y— graph label (0= benign,1= malware)family— string label ("benign","simplelocker", etc.)apk_name— source APK filename
Usage
from huggingface_hub import hf_hub_download
import torch
# Download the internal_only variant
path = hf_hub_download(
repo_id="JLB-JLB/android-ransomware-fcg-baseline",
filename="internal_only/fcg_dataset.pt",
repo_type="dataset",
)
dataset = torch.load(path, weights_only=False)
print(f"Loaded {len(dataset)} graphs")
print(f"First graph: {dataset[0].x.shape[0]} nodes, {dataset[0].edge_index.shape[1]} edges")
Citation
If you use this dataset, please cite the associated thesis work.
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Models trained or fine-tuned on JLB-JLB/android-ransomware-fcg-baseline