README.md

metadata

language: en
license: apache-2.0
tags:
  - xgboost
  - machine-learning
  - classification
  - cybersecurity
  - phishing-detection
datasets:
  - custom
metrics:
  - accuracy
  - precision
  - recall
  - f1

XGBoost Phishing Detection Models

Model Description

XGBoost models trained for phishing detection using URL and HTML content features.

This model is trained using XGBoost for binary classification tasks.

Model Architecture

• Model Type: XGBoost Classifier
• Framework: XGBoost
• Task: Binary Classification

Usage

import joblib
from huggingface_hub import hf_hub_download

# Download the model
model_path = hf_hub_download(repo_id="th1enq/xgboost_checkpoint", filename="xgboost phishing detection models.joblib")

# Load the model
model = joblib.load(model_path)

# Make predictions
predictions = model.predict(X_test)

Training

The model was trained using the XGBoost library with the following approach:

• Feature extraction from URLs/HTML content
• Binary classification (legitimate vs phishing)
• Cross-validation for model evaluation

Files

• xgboost phishing detection models.joblib: The trained XGBoost model
• features.py: Feature extraction functions
• URLFeatureExtraction.py: URL-specific feature extraction

License

This model is released under the Apache 2.0 License.