Email Confirmation or One Time Codes Are Not Enough: How Modern Fraud Bypasses Basic Verification

Email confirmation links and one time codes have been the default way to verify new accounts for more than a decade. They are simple and familiar, and most onboarding flows treat them as the main email validation step. The problem is that modern fraud no longer behaves like a human. Automated inbox pipelines, disposable email APIs, and scripted token extraction tools can now pass these checks faster and more reliably than real users, while quietly hurting email deliverability and data quality.

For growth managers, email marketers, and martech leaders, this creates a deeper issue. Fraudulent signups enter your CRM, skew engagement metrics, reduce sender reputation, and introduce risk that is difficult to detect later. Basic verification validates presence, not legitimacy.

This article explains why confirmation flows fail, what modern fraud actually looks like, and how a layered onboarding strategy creates stronger protection without unnecessary friction.

Why this matters for deliverability, data quality, and growth

For e-commerce growth managers, fake signups inflate list size, lower conversion rates, and waste marketing spend across paid and lifecycle campaigns.

For email marketing managers, they cause bounce spikes that directly affect sender reputation and inbox placement across major providers.

For marketing technology leaders, they introduce data governance, compliance, and reporting challenges under regulations such as GDPR and CCPA. See our compliance notice at GDPR Notice for more detail.

When unreliable inboxes enter your ecosystem, you often see:

• lower engagement and declining inbox placement
• incorrect funnel and attribution reporting
• inflated acquisition metrics
• wasted email and automation resources
• deliverability issues that affect legitimate customers
• increased exposure to referral abuse, trial cycling, and coupon exploitation

Early verification accuracy has a direct impact on ROI and long term sender reputation. For a deeper look at the financial impact of clean data, see The ROI of Email Validation: How to Quantify and Prove Deliverability Gains.

How fraudsters bypass email confirmation and one time codes

Modern fraud rarely involves someone manually signing up. Instead, it uses a coordinated chain of automation, AI, and disposable infrastructure that is designed to pass basic checks.

1. Automated inbox creation: Fraud tools use APIs to create thousands of temporary inboxes in seconds. These inboxes exist long enough to receive your confirmation or OTP email and are deleted immediately after.

2. Instant token extraction: Scripts monitor inbox traffic and extract verification tokens the moment they arrive. The script sends the verification request directly to your backend. No clicking. No UI.

3. Automated browser behaviour: Headless browsers simulate human navigation. They scroll, type with synthetic pauses, and generate random cursor movement. This helps bypass simple behavioural checks.

4. Distributed infrastructure: IP rotation, device spoofing, and geolocation randomization make it difficult to link fraudulent activity together just from network data.

5. High volume and high reliability: Once set up, these systems can create thousands of confirmed accounts per hour at extremely low cost. Many of these accounts will never engage with your emails.

To understand how disposable and temporary inboxes hurt sender reputation, read How Disposable and Temporary Emails Are Quietly Hurting Your Deliverability.

Why confirmation links and OTPs fail from a technical perspective

Email confirmation and OTP flows confirm only one narrow condition. The email address was reachable at a particular moment. They do not validate long term control, legitimacy, or underlying infrastructure risks that matter for fraud detection and email deliverability.

1. SMTP acceptance does not prove mailbox existence: Many domains return a successful SMTP response even for nonexistent inboxes. These are known as accept-all or catch-all servers. A confirmation email sent to such an address will appear delivered. Engagement will fail later, harming deliverability and sender reputation.

2. Domain age and DNS posture remain unchecked: Fraud pipelines often create new domains daily or purchase cheap domains with no history. Basic confirmation flows do not analyze domain age, registrar risk, SPF, DKIM, DMARC, MX quality, or DNS completeness. Email Insights inspects these signals before you rely on the address.

3. Disposable inboxes disappear after verification: Temporary inboxes live for minutes. They complete verification, then disappear. These addresses never open future campaigns, drag down open rates, and make it harder to reduce bounce rate over time.

4. Confirmation links do not detect automation: Fraud tools parse inboxes automatically and call your verification endpoint directly. They do not interact with your UI and bypass most behavioural indicators. From your system’s perspective, these signups often look better than genuine users.

5. Spamtraps and abuse networks receive confirmations too: Some inboxes exist only to catch unsolicited email and identify senders with poor list hygiene. Sending confirmations to these addresses puts your domain and IP reputation at risk. Without deeper analysis, confirmation flows cannot distinguish a high value user from a trap.

Email Insights simplifies advanced analysis with risk levels

Email Insights collects dozens of signals across DNS, SMTP, domain reputation, inbox patterns, and infrastructure behaviour. Instead of forcing your team to interpret raw technical data, it summarizes everything into a single, reliable risk data point that can be used directly in your onboarding logic and marketing workflows.

For a deeper dive into how risk scoring works, see What Is an Email Risk Score and How to Use It to Protect Your Sender Reputation.

Email Risk Levels

With risk levels, teams can make onboarding decisions without reading DNS records or SMTP logs. The risk score acts as a consistent contract between engineering, marketing, and fraud teams.

The modern onboarding stack: layered signals

Modern onboarding works best when signals are combined. Confirmation links and OTPs are still useful, but only as part of a broader strategy that includes email intelligence and behaviour analysis.

1. Email Intelligence

Applied the moment the user submits an email address.

Detects:

• domain age and registrar trust
• DNS and MX posture
• disposable and temporary inbox patterns
• SMTP anomalies and accept-all behaviour
• spamtrap and blocklist risk

Why it matters: It protects email deliverability and keeps low quality or harmful addresses out of your CRM from the start. For bulk use cases, Email Insights can be applied through Bulk Email Validation & List Cleaning Tool.

2. Behavioural Intelligence

Observes how users interact with your onboarding flow.

Examples:

• form completion time that is too fast or too consistent
• unusual navigation patterns
• repeated flows with similar data
• mismatches between location and language

Why it matters: Bot driven behaviour often looks different from genuine human interaction, even when tokens are valid.

3. Device and Network Intelligence

Analyzes network and device level signals.

Signals include:

• datacenter or proxy IPs
• TOR or VPN routing
• repeated device fingerprints across many signups
• impossible location changes in short time windows

Why it matters: Fraud ecosystems often reuse infrastructure. Device and network telemetry help you see these links.

4. Dynamic Friction

Uses risk to guide how much friction you introduce.

Risk Level	Recommended Action
Lowest	Allow immediate onboarding.
Low	Normal onboarding with optional confirmation.
Medium	Trigger confirmation email or OTP and monitor.
High	Require additional verification or step up checks.
Highest	Block or restrict access and review.

Why it matters: Good users enjoy a smooth experience. Suspicious users face additional checks. The risk score from Email Insights becomes the starting point for these decisions.

5. Continuous Trust Monitoring

Risk does not end at signup.

Examples of ongoing checks include:

• unusual login times or locations
• device changes associated with high value actions
• sudden shifts in email engagement or complaint rates
• anomalies in purchase or usage behaviour

This protects lifecycle performance, not just the first interaction.

Real world example

A subscription platform noticed a sudden spike in new signups with perfect confirmation rates but extremely poor engagement. Email Intelligence revealed most addresses came from domains less than 48 hours old with weak DNS setups and elevated risk scores. Filtering these emails before confirmation protected deliverability and improved campaign performance within a few send cycles.

Key takeaway and next steps

Email confirmation and one time codes are useful building blocks, but they validate only reachability. Modern fraud systems are designed to pass these checks at scale. A layered onboarding strategy that evaluates email infrastructure, behaviour, device context, and risk scoring offers a stronger foundation and makes it easier to maintain healthy email deliverability over time.

If you want to see how these signals look in practice, explore the product overview at Email Insights AI-Driven Data Validation & Fraud Prevention.