KLUE RoBERTa Based Prompt Injection Detection Model

This repository contains a fine-tuned KLUE RoBERTa based text classification model for Korean prompt injection detection.

Intended Use

This model was developed for a university text mining project. It is intended for academic evaluation and research on Korean prompt injection detection.

The model classifies Korean text into two categories:

  • normal
  • attack

Evaluation

Metric Value
Accuracy 0.9870
Attack Precision 0.9752
Attack Recall 0.9882
Attack F1 0.9816
Macro F1 0.9858
Weighted F1 0.9870

Detailed evaluation files:

  • classification_report.txt
  • summary.csv

Project Repository

https://github.com/3recon/prompt-injection-detection

Limitations

This model is a research artifact for prompt injection detection. It should not be used as a standalone production security system without additional validation.

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