Scikit-learn
Joblib
English
tfidf_logistic_logsource_classifier
cybersecurity
sigma
detection-engineering
mitre-attack
gradio
enterprise
Instructions to use alirezaaminzadeh/sigmaforge-logsource-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use alirezaaminzadeh/sigmaforge-logsource-classifier with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("alirezaaminzadeh/sigmaforge-logsource-classifier", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
SigmaForge Logsource Classifier
TF-IDF + Logistic Regression classifier that maps detection hypotheses to Sigma logsource fields (product, service, category).
Intended Use
- Classify log source for Sigma rule generation pipeline
- Not for production SIEM routing without retraining on your environment
Training
Trained on synthetic hypothesis ↔ logsource pairs derived from SigmaHQ rule corpus.
Limitations
- CPU-only inference
- Best performance on Windows/Sysmon/DNS hypotheses
- Heuristic fallback when model artifacts unavailable
- Downloads last month
- -
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support