Downloads · 30 days
10
11% of all-time downloads
Aikaksh-Singh-Routela/cybersecurity-bert-model
cybersecurity-bert-model is a text classification model from Aikaksh-Singh-Routela. Use it when you need a label for a piece of text. The card lists the license as mit.
This model is a fine-tuned bert-base-uncased model that classifies cybersecurity alerts into five threat categories.
Downloads · 30 days
10
11% of all-time downloads
All-time downloads
94
Public
Parameters
109M
438 MB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors438 MB · 100%
From the Hugging Face model README
This model is a fine-tuned bert-base-uncased model that classifies cybersecurity alerts into five threat categories.
bert-base-uncased0: Ransomware1: DDoS2: Insider Threat3: Web Attack4: BenignThis 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.
You can use this model directly with the Transformers pipeline for text classification:
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}]