The Hidden Challenge of Disposable Email Detection (And How You Can Help)

Disposable email services have become a double-edged sword for developers. While they offer privacy-conscious users a way to avoid spam, they also enable abuse of online services. That's why many platforms try to block them—but maintaining an accurate disposable domain list is harder than it looks.

The Scale of the Problem

Our open-source project currently tracks 205,824 known disposable domains, but here's the catch:

1. New disposable providers emerge daily (often with legitimate-sounding domains)
2. Legitimate domains sometimes get falsely flagged (causing real users problems)
3. Providers constantly rotate domains to bypass filters

This creates an endless game of cat-and-mouse that no single maintainer can handle alone.

How We Keep Up

Our system combines:

• Automated scraping of known disposable providers
• Community-contributed lists from various sources
• Manual verification of disputed domains

But automation alone isn't enough. The most valuable contributions come from humans spotting false positives—like when a legitimate email service gets mistakenly blacklisted.

Why This Matters

Every incorrectly flagged domain means:

• 🚫 Legitimate users locked out of services
• ⏳ Developer time wasted handling support tickets
• 🔄 Constant maintenance overhead

Join the Effort

We've intentionally kept contribution barriers low because:

✅ No coding experience needed to report false flags

✅ Small corrections have big impact (single domains help real users)

✅ Great first open-source contribution

How to help:

• Review the allow_list.txt for missing legitimate domains
• Report new disposable providers you encounter
• Help improve our scrapers if you have technical skills

This isn't about promoting a tool—it's about maintaining a community resource that helps balance privacy and security across the web. The more eyes we have on this, the better it works for everyone.

Contribute to the project here →

Footnote: Special thanks to all current contributors—your pull requests directly reduce false positives for thousands of applications using this data.