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Shoriful025/
cyber-threat-detector-v1

Name: cyber-threat-detector-v1
Availability: InStock

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cyber-threat-detector-v1

Overview

This model is specialized in detecting malicious intent within command-line strings and network log entries. It helps security analysts flag potentially harmful activity in real-time.

Model Architecture

Base Model: RoBERTa-base
Fine-tuning: Trained on custom cybersecurity datasets including obfuscated scripts and SQL injection attempts.

Intended Use

Security Information and Event Management (SIEM) integration.
Automated log auditing.
DevSecOps pipeline monitoring.

Limitations

May produce false positives on complex, valid administrative scripts.
Only supports text-based logs; does not analyze binary packets.

Example Code

python

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

tokenizer = AutoTokenizer.from_pretrained("cyber-threat-detector-v1")
model = AutoModelForSequenceClassification.from_pretrained("cyber-threat-detector-v1")

log_line = "SELECT * FROM users WHERE id = '1' OR '1'='1';"
inputs = tokenizer(log_line, return_tensors="pt")
outputs = model(**inputs)
prediction = torch.argmax(outputs.logits)
print("Threat Detected" if prediction == 1 else "Safe")

Shoriful025/cyber-threat-detector-v1