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metadata
license: mit
tags:
  - SQL Injection
widget:
  - text: 1 UNION SELECT username, password FROM users --
    example_title: SQL Injection Detection
metrics:
  - f1
  - accuracy

A distilBERT based SQL Injection Detection Model

Model description

This model, based on DistilBERT, is specifically tailored for the detection of SQL injection attacks. Through fine-tuning using the Hugging Face's Trainer API, the model has been trained to identify potentially malicious SQL queries with high accuracy.

  • Architecture: DistilBERT
  • Fine-tuning Method: Trainer API
  • Performance Metrics:
    • F1-score: 99.86%
    • Accuracy: 99.99%
  • Training Epochs: 6

Dataset description

The model was fine-tuned on the SQL Injectiom dataset, curated and made available by SAJID576 on Kaggle. This dataset comprises of 30,920 rows of SQL queries, including both benign and malicious examples, providing a comprehensive training corpus for robust model development.