Datasetpublic

darkknight25/phishing_benign_email_dataset

Phishing and Benign Email Dataset This dataset contains a curated collection of phishing and legitimate (benign) emails for use in cybersecurity training, phishing detection models, and email classification systems. Each entry is structured with subject, body, intent, technique, target, and classification label. 📁 Dataset Format The dataset is stored in .jsonl (JSON Lines) format. Each line is a standalone JSON object. Fields: Field… See the full description on the dataset page: https://huggingface.co/datasets/darkknight25/phishing_benign_email_dataset.

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Dataset Card

Phishing and Benign Email Dataset

This dataset contains a curated collection of phishing and legitimate (benign) emails for use in cybersecurity training, phishing detection models, and email classification systems. Each entry is structured with subject, body, intent, technique, target, and classification label.

📁 Dataset Format

The dataset is stored in .jsonl (JSON Lines) format. Each line is a standalone JSON object.

Fields:

Field	Description
`id`	Unique email ID
`subject`	Email subject line
`body`	Full email content
`intent`	Purpose of the email (e.g., credential harvesting, malware delivery)
`technique`	Social engineering or technical trick used
`target`	Who or what is being impersonated
`spoofed_sender`	Forged email address
`label`	`"phishing"` or `"benign"`

🔍 Example Entry

json

{
  "id": "phish-0003",
  "subject": "Unusual Activity Detected",
  "body": "Suspicious login from Russia. Reset password now: https://g00gle-security.com",
  "intent": "Credential Harvesting",
  "technique": "Homoglyph Link Spoofing",
  "target": "Google",
  "spoofed_sender": "no-reply@g00gle.com",
  "label": "phishing"
}
✅ Use Cases

    Train NLP models to detect phishing content

    Classify or filter email threats in spam filters

    Educate users and red teams on phishing techniques

    Simulate email-based social engineering scenarios

📊 Dataset Summary

    🔐 Phishing Emails: ~100 entries

    ✅ Benign Emails: ~100 entries

    ⚖️ Balanced and ready for binary classification or LLM pretraining

⚠️ Disclaimer

This dataset is for research and educational purposes only. Do not use these emails in live environments. The authors are not responsible for misuse.
📜 License

This dataset is released under the MIT License.
📫 Contributions

Feel free to submit pull requests to add more phishing or legit emails. The more diverse, the better for training secure systems.