README.md

---
language: en
license: mit
tags:
- cybersecurity
- bert
- text-classification
- security
widget:
- text: "Files encrypted with ransom demand for Bitcoin payment"
  example_title: "Ransomware Example"
- text: "Website unreachable due to massive spike in incoming requests"
  example_title: "DDoS Example"
- text: "Employee downloading sensitive customer data before resignation"
  example_title: "Insider Threat Example"
---

# Cybersecurity BERT Classifier

This model is a fine-tuned `bert-base-uncased` model that classifies cybersecurity alerts into five threat categories.

## Model Details

- **Base Model:** `bert-base-uncased`
- **Task:** Text Classification
- **Labels:**
    - `0`: Ransomware
    - `1`: DDoS
    - `2`: Insider Threat
    - `3`: Web Attack
    - `4`: Benign

## Intended Uses & Limitations

This model is intended for security operations center (SOC) teams to automatically triage and classify security alert text. It achieves **92.86% accuracy** on a curated test set.

## How to Use

You can use this model directly with the Transformers pipeline for text classification:

```python
from transformers import pipeline

classifier = pipeline("text-classification", model="Aikaksh-Singh-Routela/cybersecurity-bert-model")

result = classifier("Files encrypted with ransom demand for Bitcoin payment")
print(result)
# Expected output: [{'label': 'Ransomware', 'score': 0.9286}]