Catch-all domain detection with conservative handling
Why it matters
Catch-all domains accept email to any local-part regardless of whether the mailbox exists — xyz1234@company.com and alice@company.com both succeed MX verification. This makes MX checks alone insufficient for validating contact quality. Contacts from catch-all domains appear deliverable but frequently bounce or are read by nobody, because many catch-all configurations feed unrouted mail to a trash mailbox. Mixing catch-all addresses with fully verified contacts inflates your apparent list size while depressing engagement rates, producing misleading health metrics and campaign analytics.
Severity rationale
Low because catch-all addresses are a list quality issue that degrades metrics and deliverability incrementally rather than causing immediate bounces or compliance exposure.
Remediation
Use an email validation API that returns a catch-all or accept_all status and store it on the contact record. Exclude catch-all addresses from cold outreach segments:
// Store validation status at ingest (example using ZeroBounce response shape):
await db.contact.upsert({
where: { email },
update: { validation_status: result.status },
create: { email, validation_status: result.status }
})
// Exclude from cold campaigns:
const campaignContacts = await db.contact.findMany({
where: {
NOT: { validation_status: 'catch-all' }
}
})
For budget-constrained situations, use the catch-all probe technique: during validation, send an SMTP RCPT TO command for a randomly generated address at the domain; if the server accepts it, flag the domain as catch-all. Many validation APIs perform this probe natively.
DetectionPro
The detection method for this pattern is part of AuditBuffet Pro.
The full method (what to look for, pass and fail conditions, and how results get reported) ships inside the Data Quality & List Hygiene Audit. The pattern definition, severity rationale, and remediation remain openly licensed under CC-BY-4.0.
External references
- iso-25010:2011 · functional-correctness — Functional Correctness (functional suitability)
Taxons
History
- 2026-04-18·v1.0.0·Initial import from data-quality-list-hygiene·automated