puyang2025/seven-phishing-email-datasets

Dataset Card for Seven Phishing/Spam Email Datasets

Dataset Summary

This dataset is a unified, row-level email corpus built from seven commonly used public email datasets. It is intended for research on phishing/spam detection and related email-text classification tasks.

Each row contains the email body (text), optional header-like fields (e.g., sender, receiver, date), the source dataset name (dataset_name), and a binary label (label).

Supported Tasks and Leaderboards

• Binary classification: phishing/spam vs benign/legitimate email.

Languages

• Primarily English (en).

Dataset Structure

Data Instances

Each example has the following fields:

• text (string): Email body content (may include quoted replies/forwards).
• subject (string): Email subject line.
• label (int64): Binary label where 0 = benign/legitimate (ham) and 1 = phishing/spam.
• sender (string, nullable): Sender address/name when available.
• receiver (string, nullable): Receiver address/name when available.
• date (timestamp[ns], nullable): Parsed timestamp when available.
• urls (int64, nullable): Count of URL-like substrings detected in the email content (when available).
• dataset_name (string): Source dataset identifier (Assassin, CEAS-08, Enron, Ling, TREC-05, TREC-06, TREC-07).

Data Splits

The repository contains Parquet shards for a single split:

• train: 203,017 examples total (8 Parquet shards: train-00000-of-00008.parquet … train-00007-of-00008.parquet).

Usage

With the datasets library:

from datasets import load_dataset

ds = load_dataset("YOUR_HF_ORG/seven-phishing-email-datasets")
ds["train"][0]

Per-source counts:

dataset_name	benign (label=0)	phishing/spam (label=1)	total
TREC-05	32,329	22,946	55,275
TREC-07	24,358	29,399	53,757
CEAS-08	17,312	21,842	39,154
Enron	15,791	13,976	29,767
TREC-06	12,411	3,989	16,400
Assassin	4,087	1,718	5,805
Ling	2,401	458	2,859
Total	108,689	94,328	203,017

Missingness notes (null counts over the full dataset):

• sender: 32,626 nulls
• receiver: 32,626 nulls
• date: 36,084 nulls
• urls: 32,626 nulls

Dataset Creation

Source Data

The dataset aggregates emails from seven widely-used sources (as present in data_raw/):

• Assassin.csv (SpamAssassin public corpus–derived)
• CEAS-08.csv (CEAS 2008 email dataset)
• Enron.csv (Enron email corpus–derived)
• Ling.csv (Ling-Spam dataset)
• TREC-05.csv (TREC 2005 spam track–derived)
• TREC-06.csv (TREC 2006 spam track–derived)
• TREC-07.csv (TREC 2007 spam track–derived)

Data Processing

This Hugging Face distribution provides a normalized schema across sources and exports the result as Parquet. Some header fields are missing for certain sources, which is reflected by null values in sender, receiver, date, and urls.

Considerations for Using the Data

Social Impact and Intended Use

This dataset is intended for security/NLP research (e.g., spam/phishing detection, robustness evaluation, domain adaptation). It should not be used for surveillance or to make high-stakes decisions without additional validation and safeguards.

Risks, Biases, and Limitations

• Label semantics: label=1 represents phishing/spam content in the original sources; depending on the source, it may include marketing spam and other unwanted email that is not strictly phishing.
• Temporal/domain shift: Many sources are historical; modern phishing campaigns and email formats may differ substantially.
• Duplicates and thread text: Emails may contain quoted replies/forwards and signatures; naive splitting can leak information between train/test if you create your own splits.
• PII: Emails can contain personal data (names, addresses, phone numbers, email addresses) and should be handled accordingly.
• Malicious content: Emails may include harmful URLs or instructions. Do not click links or execute attachments referenced in the text.

Recommendations

• Create your own train/validation/test split carefully (e.g., group by thread, sender domain, or near-duplicate clustering) to reduce leakage.
• Consider redacting PII (addresses, phone numbers, account numbers) for downstream sharing or model release.

Licensing

This repository aggregates multiple datasets with potentially different licensing terms and usage restrictions. No single license is asserted for the combined dataset here; please consult the original sources for each component dataset and ensure your intended use complies with their terms.

Citation

If you use this dataset, cite the original source datasets as appropriate (e.g., TREC Spam Track corpora, CEAS 2008, Enron email corpus, Ling-Spam, SpamAssassin public corpus) and also cite this Hugging Face dataset entry.

Contact

For questions or issues with this Hugging Face conversion, please open an issue or discussion in the repository hosting this dataset.