drorrabin/phishing_emails-data

🛡️ Phishing Email Classification Dataset

This dataset is curated for fine-tuning LLMs on the task of phishing email detection. It originates from this Kaggle dataset and has been transformed to better suit LLM-based classification tasks.

📦 Dataset Features

• Each row is a labeled email, with either:
  • safe email (label = 0)
  • phishing email (label = 1)
• The dataset includes metadata (sender, receiver, date, subject) and cleaned email body.
• Two main columns:
  • Email Text: Complete formatted text including metadata and message content.
  • label: Binary label indicating if the email is phishing.

🧠 LLM Fine-Tuning Ready

Processed using a phishing_items.py parser:

• Truncates or filters emails based on token limits for LLM input (between 30 and 250 tokens).

• Builds classification prompts in the format:

  Is the following email safe or phishing??
  
  [email content]
  
  Email type is: [safe email/phishing email]
  

• Optimized for models such as meta-llama/Meta-Llama-3.1-8B.

🧼 Preprocessing Highlights

• Removes non-informative characters (e.g., =, >, \) and extra whitespace.
• Tokenized with Hugging Face's AutoTokenizer.
• Discards overly short emails (under 120 characters or under 30 tokens).

🗂️ Example Usage

from phishing_items import Item

item = Item(data_row)
if item.include:
    print(item.prompt)

📚 Source

• Original dataset: Kaggle - Phishing Emails
• Transformed by: [your GitHub or Hugging Face handle]