Disposable email services (yopmail, mailinator, temp-mail and hundreds of others) give anyone a working inbox in one click, with no account. They are handy for privacy, and they are the favorite tool of anyone farming your free tier: a new address for every new trial.

This post shows how to reject them at signup with one server-side call, in Node.js, Python and PHP, without breaking your signup when the check fails.

The first thing most teams try against throwaway signups is a blocklist: a file of a few thousand disposable domains from GitHub, checked at signup. It works for a week. Then the fake signups start again, from domains that aren't on the list.

This post explains why lists fall behind, and what a domain's DNS records reveal about it even when nobody has listed it yet.

A user types [email protected], clicks Sign up and waits for a verification email that never arrives. They don't come back. You lose a real user, and the bounce counts against your sender reputation.

Typos are the most common bad address at signup, and unlike fake addresses, the person behind them actually wants your product. Catching them is pure gain.

A free tier is a marketing budget. Every account costs you something: compute for an AI tool, seats for a SaaS, a coupon for a shop. Most people use it as intended. A few create dozens of accounts, and for products with expensive free credits, those few can cost more than everyone else combined.

Here are the seven tricks we see most, what each one costs to stop, and which ones an email check can and can't solve.

[email protected], [email protected] and [email protected] are three different strings and one inbox. If your signup treats them as three users, one person gets three free trials, three sets of credits or three referral bonuses.

The fix is not to block these addresses: real people use them. The fix is to know they belong to the same inbox.

We sell a disposable email check, so you might expect this post to say "always block them". It doesn't. Blocking throwaway addresses is right for many products and wrong for some, and doing it carelessly costs you real users.