Warning

This project is in an early stage. Some domains may be incorrectly flagged as disposable. We actively welcome contributors to help improve accuracy, particularly by maintaining the whitelists.

Real-time Disposable Email Domains

This project automatically aggregates disposable email domains using curated public lists, third-party sources, and internally collected intelligence. All ingestion, validation, and publishing workflows are fully automated. All domains are normalised and validated before inclusion.

Repository Structure

├── data/
│   ├── domains.txt  # All flagged disposable domains (includes subdomains)
│   ├── root.txt     # Flagged disposable root domains
│   └── active.txt   # Flagged root domains with active MX records
│
├── domain_whitelist.txt      # Manual domain whitelist
└── tld_whitelist.txt         # Manual TLD whitelist

Data Update Frequency

The dataset is continuously maintained:

• data/domains.txt is updated every hour
• data/root.txt is updated every hour
• data/active.txt is updated once per day

active.txt contains only domains that currently resolve with a valid MX record.

Reporting Incorrectly Flagged Domains

If you believe a legitimate domain has been incorrectly classified as disposable, you can help improve accuracy by contributing to the whitelist.

To contribute:

1. Confirm that the domain provides a legitimate, non-disposable email service
2. Add the domain to domain_whitelist.txt, or add a TLD to tld_whitelist.txt
3. Submit a pull request

The allow list acts as a manual override to prevent false positives.

Data Sources

Domains are sourced from:

• established public disposable email domain lists
• open-source intelligence feeds
• internal discovery and monitoring systems
• community contributions

Sources are aggregated, cleaned, validated, and standardised before publication.

Contributions

Although the project is automatically maintained through scraping and aggregation, domain ecosystems change frequently. Providers appear, disappear, and repurpose infrastructure.

Community input is essential to:

• reduce false positives
• identify new disposable providers
• maintain data freshness
• improve validation logic

First-time contributors are welcome. Even small corrections significantly improve dataset reliability.

Every contribution directly strengthens the integrity and usefulness of this resource.