Text Classification
Scikit-learn
Joblib
English
cybersecurity
penetration-testing
vulnerability-classification
xgboost
enterprise
Instructions to use alirezaaminzadeh/pentestbrief-severity-engine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use alirezaaminzadeh/pentestbrief-severity-engine with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("alirezaaminzadeh/pentestbrief-severity-engine", "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
PentestBrief Severity Engine
TF-IDF + XGBoost multi-class severity classifier for penetration test finding descriptions.
Intended Use
- Classify vulnerability severity (Critical/High/Medium/Low/Informational) from finding text
- Used within the PentestBrief multi-agent pipeline
- Not for autonomous exploitation or offensive security operations
Training Data
- ayshajavd/code-security-vulnerability-dataset
- Synthetic pentest finding corpus
Reference Model
Limitations
- English-language findings perform best
- Requires structured finding text (title + description)
- Does not replace human pentest analyst review
Built by Aria AI Red Team Engineering.
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