🐍 V.I.P.E.R. Classification Engine (v1.0)

Maintainer: Cata Risk Lab

🧠 Model Overview

This repository contains the configuration and architecture definitions for the V.I.P.E.R. recruitment auditing system. It defines the risk thresholds and vectorization parameters used to detect "Resume Harvesting" attacks.

πŸ› οΈ Configuration

The model operates on a TfidfVectorizer pipeline optimized for short-text classification of email subjects and bodies.

  • Risk Threshold: 0.75 (Confidence score required to flag as SPAM)
  • Labels: ['harvesting', 'legitimate']
  • Dataset: Trained on forensic recruitment data (Swiss/US/UK).

βš–οΈ Sovereign AI

Designed for local inference to protect user data privacy.

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Dataset used to train Cata-Risk-Lab/VIPER-Text-Classifier-v1