Bulk Email Validator & Verification API [50K Emails] 🚀 (2026)

Built by Clearpath, creators of Email Finder, with 130,000+ lifetime runs, and Newsletter List Cleaner. Find, validate and clean your contacts with one specialist suite.

Why choose this actor?

Check large lists for more than invalid addresses. Validate 50,000 emails from a CSV with the bulk settings below. Get a status and score for each address, plus flags for disposable emails, catch-all domains, role accounts, disabled mailboxes and full inboxes.

Get the results in useful groups. Export individual email records and a summary with score-based clean, risky and invalid lists. Separate status groups and the safe_to_send field help you choose which contacts to keep or review.

Start with your existing CRM export. Upload a CSV or provide its URL. The actor finds the email column, can combine multiple email columns, and removes duplicate addresses across your file and direct input.

Quick start

Upload your own CSV in the input form, or replace the example URL below with your file URL in the JSON input. Start with 10 addresses to inspect the output.

{
  "csvFile": "https://example.com/contacts.csv",
  "maxItems": 10
}

Open actor input to provide your list. For a 50,000-address run, use CSV input and set "maxItems": 50000 in the JSON input. This requires a paid Apify plan and a sufficient run budget; leaving maxItems out defaults to 1,000 addresses.

Free-tier accounts have one trial run of up to 10 addresses. A run budget below $1 also caps processing at 10 addresses. Results describe validation signals, not a guarantee that a message will reach the inbox.

Clearpath · Email Tools
Email Validator You are here	Email Finder Find business emails	Newsletter Cleaner Score subscribers	Business Leads Find local contacts	Account Checker Check registrations

Copy to your AI assistant

Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor.

clearpath/email-validation-api on Apify. Call: ApifyClient("TOKEN").actor("clearpath/email-validation-api").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items for results. Key inputs: emailAddresses (array of strings), csvFile (string, file upload), csvEmailColumn (string, optional). Full actor spec (input schema with all params/enums/defaults, output dataset fields, README): GET https://api.apify.com/v2/acts/clearpath~email-validation-api/builds/default (Bearer TOKEN) → inputSchema, actorDefinition.storages.dataset, readme. Pricing: $6-$8 per 1,000 emails depending on plan. Get token: https://console.apify.com/account/integrations

Why Your Domain Reputation Depends on This

Every bounced email is a strike against your domain reputation. Too many strikes? Your legitimate emails start landing in spam folders—or worse, your domain gets blacklisted.

This Email Validator prevents that disaster before it happens.

The Hidden Cost of Invalid Emails:

• 5% bounce rate = Mail services flag you as risky
• 10% bounce rate = Your domain reputation plummets
• 15% bounce rate = Welcome to the blacklist

Why Choose This Email Validator?

🛡️ Protect Your Domain Reputation

Your domain is your digital identity. High bounce rates destroy it. We validate emails BEFORE you send, keeping your bounce rate under 2%.

📈 Save Your Email Campaigns

Invalid emails don't just bounce—they poison your entire campaign. Clean lists mean better deliverability for ALL your emails.

🚫 Stop Fraud & Fake Signups

Detect disposable emails, role accounts, and honeypots before they infiltrate your database.

🎯 Enterprise-Grade Accuracy

Multiple verification layers ensure confidence in every validation. No guesswork, just data.

⚡ Bulk Processing Power

Validate up to 50,000 emails in a single batch. Perfect for large-scale list cleaning.

Features

• ✅ 15+ Validation Checks: Comprehensive verification including syntax, SMTP, MX records, and catch-all detection
• ✅ Smart Email Classification: Instantly identify free, disposable, and role-based emails
• ✅ Quality Scoring System: 0-100 confidence scores help you make informed decisions
• ✅ Catch-All Detection: Know when domains accept all emails (high-risk for bounces)
• ✅ Full MX Records: Complete mail exchange server information for transparency
• ✅ Spamtrap Detection: Avoid emails that damage sender reputation
• ✅ Risk Assessment: Clear categorization (safe/risky/invalid/disposable/catch-all)
• ✅ Bulk Processing: Handle massive email lists efficiently
• ✅ No Cookies Required: Clean, straightforward validation

Input

Simple and straightforward - just provide your email list:

{
    "emailAddresses": [
        "john.doe@company.com",
        "support@business.org",
        "test@disposable-email.com",
        "admin@catch-all-domain.com"
    ]
}

With optional parameters:

{
    "emailAddresses": [
        "contact@business.com",
        "fake.email@notreal",
        "temp@10minutemail.com"
    ],
    "maxItems": 5000,
    "proxyConfiguration": {
        "useApifyProxy": true
    }
}

CSV File Support

📝 Combining CSV and Direct Input

You can provide emails through BOTH methods simultaneously! When you supply both emailAddresses and csvFile, the actor automatically merges them:

• CSV emails are processed first (given priority)
• Direct input emails are added next (from emailAddresses parameter)
• Duplicates are automatically removed (case-insensitive matching)
• Perfect for adding specific emails to your CSV list

Example:

{
    "csvFile": "your-bulk-list.csv",
    "emailAddresses": ["priority@vip.com", "test@specific.com"],
    "maxItems": 10000
}

🎯 Automatic Email Column Detection

The actor automatically detects your email column! No configuration needed - just upload your CSV and let the intelligent detection system handle the rest. The actor will fail gracefully with a clear error message if no email column can be detected, ensuring you're always aware of any issues.

📤 Upload Your CRM Exports

Upload your CSVs with leads from Apollo, HubSpot, Salesforce, or any other CRM tool! This validator is designed to work seamlessly with exports from popular sales and marketing platforms:

• Apollo.io: Direct support for contact export format
• HubSpot: Works with contact and company exports
• Salesforce: Compatible with lead and contact reports
• LinkedIn Sales Navigator: Process your saved lead lists
• Any CSV format: Supports comma, semicolon, tab, and pipe delimiters

How to Use CSV Files

1. Upload directly: Use the file upload button in Apify Console
2. Provide a URL: Link to your CSV file hosted anywhere
3. Auto-detection: The actor scans your file and identifies email columns by:
   • Common header names (email, contact_email, primary_email, etc.)
   • Content analysis (looking for @ symbols and email patterns)
   • Smart pattern matching across multiple languages
4. Validation: All detected emails are validated comprehensively
5. Results: Get detailed validation results for each email address

CSV Input Example

{
    "csvFile": "Upload your CSV file or provide URL",
    "maxItems": 10000
}

With advanced options:

{
    "csvFile": "https://your-domain.com/emails.csv",
    "csvEmailColumn": "primary_email",  // Optional: specify column
    "csvMergeMultipleColumns": true,     // Optional: merge all email columns
    "maxItems": 50000
}

Supported CSV Formats

• File Types: .csv files with various encodings (UTF-8, ASCII, Latin-1)
• Delimiters: Automatically detects comma (,), semicolon (;), tab (\t), or pipe (|)
• Headers: Works with or without headers - the actor adapts automatically
• Quoted Fields: Handles complex CSVs with quoted fields containing delimiters

Output Examples

Individual Email Results

Each email gets detailed validation data:

// ✅ Valid email
{
    "email": "john.doe@company.com",
    "status": "safe",
    "score": 98,
    "username": "john.doe",
    "domain": "company.com",
    "mx_records": ["mail.company.com", "backup-mx.company.com"],
    "smtp_connection_success": true,
    "mx_accepts_mail": true,
    "valid_syntax": true,
    "deliverable": true,
    "safe_to_send": true,
    "catch_all": false,
    "disposable": false,
    "role_account": false,
    "free_email": false,
    "spamtrap": false,
    "disabled": false,
    "inbox_full": false
}

// ❌ Invalid email
{
    "email": "fake.email@notreal",
    "status": "invalid",
    "score": 0,
    "username": "fake.email",
    "domain": "notreal",
    "mx_records": [],
    "smtp_connection_success": false,
    "mx_accepts_mail": false,
    "valid_syntax": true,
    "deliverable": false,
    "safe_to_send": false,
    ...
}

// ❓ Unknown status
{
    "email": "john@enterprise-corp.com",
    "status": "unknown",
    "score": 50,
    "username": "john",
    "domain": "enterprise-corp.com",
    "mx_records": ["mail.enterprise-corp.com"],
    "smtp_connection_success": false,
    "mx_accepts_mail": true,
    "valid_syntax": true,
    "deliverable": null,
    "safe_to_send": null,
    "reason": "Server timeout or anti-validation measures",
    ...
}

// 🗑️ Disposable email
{
    "email": "temp@10minutemail.com",
    "status": "disposable",
    "score": 25,
    "username": "temp",
    "domain": "10minutemail.com",
    "mx_records": ["mx.10minutemail.com"],
    "smtp_connection_success": true,
    "mx_accepts_mail": true,
    "valid_syntax": true,
    "deliverable": true,
    "safe_to_send": false,
    "catch_all": false,
    "disposable": true,
    ...
}

// 🎣 Catch-all domain
{
    "email": "anything@catch-all-domain.com",
    "status": "catch_all",
    "score": 71,
    "username": "anything",
    "domain": "catch-all-domain.com",
    "mx_records": ["mail.catch-all-domain.com"],
    "smtp_connection_success": true,
    "mx_accepts_mail": true,
    "valid_syntax": true,
    "deliverable": true,
    "safe_to_send": false,
    "catch_all": true,
    ...
}

📊 Summary Report (Final Dataset Entry)

After all emails are processed, you'll get a summary report with cleaned lists:

{
    "type": "summary_report",
    "timestamp": "2025-08-21T10:00:00Z",
    "total_processed": 100,
    "clean_emails": [
        "john.doe@company.com",
        "alice@business.org",
        "contact@enterprise.com"
    ],
    "risky_emails": [
        "info@catch-all-domain.com",
        "support@sample-company.net"
    ],
    "invalid_emails": [
        "fake@notreal",
        "broken@",
        "test@disposable.com"
    ],
    "statistics": {
        "deliverable": 75,
        "undeliverable": 20,
        "catch_all": 5,
        "disposable": 8,
        "average_score": 82.5
    },
    "emails_by_status": {
        "safe": ["john.doe@company.com", "alice@business.org"],
        "risky": ["info@domain.com"],
        "invalid": ["fake@notreal"],
        "catch_all": ["admin@catch-all.com"],
        "disposable": ["temp@10minute.com"]
    }
}

Pricing

Simple, transparent pricing based on volume:

Volume	Price per 1000 emails
Standard	$8.00
Bronze Discount	$7.50
Silver Discount	$7.00
Gold Discount	$6.00

Contact us for custom enterprise pricing on volumes above 1M emails.

Understanding Your Results

Status Indicators

Status	Symbol	Meaning	Action
safe	✅	Email is valid and safe to send	Send with confidence
risky	⚠️	Email might have deliverability issues	Consider removing
invalid	❌	Email will bounce	Remove immediately
unknown	❓	Validation couldn't be completed	See section below
disposable	🗑️	Temporary email address	Remove for quality
catch_all	🎣	Domain accepts all emails	Use with caution

Understanding "Unknown" Status

What does "unknown" mean? The validation service couldn't definitively verify this email address. This doesn't mean the email is invalid - it means verification couldn't be completed due to the recipient server's security measures.

Common reasons for "unknown" status:

• Corporate firewalls - Enterprise domains might block validation attempts
• Greylisting - Servers temporarily reject checks to prevent spam
• Anti-validation measures - Some mail systems intentionally hide mailbox existence
• Strict security policies - Government, financial, and healthcare domains might often return unknown

How to handle unknown emails: These emails often belong to legitimate business contacts, especially from large corporations. Consider your use case:

• B2B outreach: Often worth keeping (many corporate emails return unknown)
• Consumer marketing: Higher risk, consider your tolerance
• Critical communications: Test with a small batch first

Quality Score Interpretation

• 90-100: Excellent quality, definitely send
• 70-89: Good quality, safe to send
• 50-69: Moderate risk, review before sending
• 30-49: High risk, likely to bounce
• 0-29: Do not send, will damage reputation

Validation Checks Explained

Check	What It Means	Why It Matters
valid_syntax	Email format is correct	Malformed emails always bounce
mx_accepts_mail	Domain can receive emails	No MX records = guaranteed bounce
smtp_connection_success	Mail server responds	Confirms server is active
deliverable	Email can be delivered	Combined validation result
safe_to_send	Low risk of bounce/spam	Protects your reputation
catch_all	Domain accepts any address	Higher bounce risk
disposable	Temporary email service	Often used for fraud/spam
role_account	Generic address (info@, admin@)	Lower engagement rates
free_email	Gmail, Yahoo, etc.	May indicate personal vs business
spamtrap	Honeypot address	Sending here = instant blacklist
inbox_full	Mailbox at capacity	Temporary delivery failure

Use Cases by Industry

📧 Email Marketing Teams

Clean your lists before every campaign. A 2% reduction in bounce rate can improve overall deliverability by 15%.

🚀 SaaS Companies

Validate emails at signup to prevent fake accounts and improve user quality metrics.

🛒 E-commerce Platforms

Stop fraudulent orders by detecting disposable emails used for one-time purchases.

📊 CRM Managers

Maintain database hygiene by regularly validating and removing invalid contacts.

🎯 Lead Generation Agencies

Qualify leads instantly by validating emails in real-time during collection.

🏢 Enterprise Sales Teams

Verify prospect emails before outreach to maximize connection rates.

Performance & Limits

• Batch Size: Up to 2,500 emails per run
• Accuracy Rate: 99%+ for syntax, 95%+ for deliverability
• Response Time: Results typically available within a few minutes for 1000 emails

Security & Compliance

• ✅ GDPR Compliant
• ✅ No data retention after processing
• ✅ Encrypted data transmission
• ✅ No cookies or tracking

Pro Tips for Best Results

1. Clean regularly: Validate your entire list quarterly to maintain hygiene
2. Pre-campaign validation: Always validate before major email campaigns
3. Real-time validation: Integrate validation at the point of email collection
4. Score thresholds: Set minimum score requirements (we recommend 70+)
5. Segment by status: Create separate lists for safe, risky, and invalid emails

When to Use This Validator

Before You Send

• Email marketing campaigns
• Cold outreach sequences
• Newsletter distributions
• Transactional email batches

During Collection

• User registration forms
• Lead capture pages
• Webinar signups
• Newsletter subscriptions

For Maintenance

• Quarterly list cleaning
• Database migration
• CRM deduplication
• Post-campaign hygiene

Programmatic Access - Get Your Clean Email List

Accessing the Summary Report

The validator creates a special summary_report entry at the end of the dataset containing your cleaned email lists. Here's how to access it programmatically:

JavaScript/Node.js

const { ApifyClient } = require('apify-client');

// Initialize the client
const client = new ApifyClient({
    token: 'YOUR_APIFY_TOKEN',
});

// Get the dataset
const dataset = await client.dataset('DATASET_ID').listItems();

// Find the summary report
const summary = dataset.items.find(item => item.type === 'summary_report');

// Extract clean emails (score >= 70)
const cleanEmails = summary.clean_emails;
console.log('Clean emails ready to use:', cleanEmails);

// Or get emails by specific status
const safeEmails = summary.emails_by_status.safe;
const riskyEmails = summary.emails_by_status.risky;

Python

from apify_client import ApifyClient

# Initialize the client
client = ApifyClient('YOUR_APIFY_TOKEN')

# Get the dataset
dataset = client.dataset('DATASET_ID').list_items()

# Find the summary report
summary = next(item for item in dataset['items'] if item.get('type') == 'summary_report')

# Extract clean emails (score >= 70)
clean_emails = summary['clean_emails']
print(f'Clean emails ready to use: {clean_emails}')

# Or get emails by specific status
safe_emails = summary['emails_by_status']['safe']
risky_emails = summary['emails_by_status']['risky']

Direct API Access

# Get all dataset items
curl "https://api.apify.com/v2/datasets/DATASET_ID/items" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN"

# The summary report will be the last item with type: "summary_report"

Using the Clean List

Once you have the clean emails, you can:

• Import directly into your email marketing platform
• Filter further by specific criteria (e.g., only non-catch-all)
• Export to CSV for manual review
• Integrate into your CRM or automation workflows

Quick Copy-Paste

The clean_emails array is ready to copy and paste into any email platform that accepts comma-separated or line-separated email lists.

ROI Calculator

For every 1000 emails validated:

• Prevent ~50-200 bounces (5-20% typical invalid rate)
• Save domain reputation from damage
• Improve deliverability for ALL future emails
• Avoid blacklist recovery costs ($1000s in lost revenue)

Get Started

1. Add your email list to the input
2. Configure your validation preferences
3. Run the validator
4. Download your clean, validated list
5. Send with confidence!

Related Actors

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• Phone Number Active Status Checker - Bulk carrier-level active, inactive, or unknown status checks.
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• Social & Crypto Phone Number Checker - Bulk account checks across 25 platforms (Instagram, Facebook, Binance, and more).

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Support

• 📧 Email: max@mapa.slmail.me
• 🐛 Issues: Use the Issues tab for bug reports and feature requests
• 💬 Response time: Usually within 24 hours
• 🔧 Custom features: Available upon request

Stop guessing. Start knowing. Your domain reputation is too valuable to risk on unvalidated emails.

🚀 Start Validating Your Email List