email-finder

name	email-finder
description	Find email addresses for a domain by combining website scraping, search dorking, pattern guessing, DNS analysis, and SMTP verification. Use when prospecting leads, finding contact emails for outreach, or building contact lists from a company domain. Optionally provide a person's name to generate and verify common email patterns.

Email Finder

Discover email addresses associated with a domain using multiple methods.

How It Works

1. Website Scraping — Fetches homepage, /contact, /about, /team pages and extracts emails via regex
2. Search Dorking — Searches for published emails in directories and search engines
3. Pattern Guessing — If a name is provided, generates common patterns (first@, first.last@, flast@, etc.)
4. DNS Hints — Checks MX/SPF/DMARC records to identify the email provider
5. SMTP Verification — Verifies all found/guessed emails using RCPT TO

Dependencies

pip3 install dnspython

Usage

Basic domain search

python3 scripts/find_emails.py example.com

With name for pattern guessing

python3 scripts/find_emails.py example.com --name "John Smith"

Skip SMTP verification

python3 scripts/find_emails.py example.com --no-verify

Options

• --name "First Last" — Enable pattern guessing for a specific person
• --no-verify — Skip SMTP verification step
• --timeout SECONDS — Connection timeout (default: 10)

Output

JSON to stdout:

{
  "domain": "example.com",
  "provider": "Google Workspace",
  "mx": ["aspmx.l.google.com"],
  "spf": "v=spf1 include:_spf.google.com ~all",
  "dmarc": "v=DMARC1; p=reject; rua=mailto:[e-mail]",
  "emails_found": 2,
  "emails": [
    {
      "email": "[e-mail]",
      "source": "scraped",
      "deliverable": "yes",
      "smtp_detail": "2.1.5 OK"
    },
    {
      "email": "[e-mail]",
      "source": "guessed"
       
       
    
  

Source values

Value	Meaning
scraped	Found on the domain's website
searched	Found via search/directory lookup
guessed	Generated from name patterns
dns	Found in DNS records (DMARC reports, etc.)

Deliverable values

Value	Meaning
yes	Server accepted the recipient
no	Server rejected the recipient (invalid)
catch-all	Server accepts all addresses
unknown	Could not determine
not_checked	Verification was skipped

Rate Limiting

The script includes built-in rate limiting at every stage to protect your IP:

# Defaults: 0.5s between page fetches, 2s between SMTP checks, max 15 SMTP checks
python3 scripts/find_emails.py example.com --name "John Smith"

# Conservative settings for sensitive environments
python3 scripts/find_emails.py example.com --scrape-delay 1.0 --smtp-delay 4 --max-smtp-checks 8

# Just scrape, no SMTP (zero risk)
python3 scripts/find_emails.py example.com --no-verify

Options

• --scrape-delay SECONDS — Pause between website page fetches (default: 0.5)
• --smtp-delay SECONDS — Pause between SMTP verification checks (default: 2.0)
• --max-smtp-checks N — Max SMTP verifications per run (default: 15). Remaining emails get not_checked status.

Why rate limiting matters

This tool hits both web servers and mail servers. Without rate limiting:

• Web scraping — Aggressive crawling gets your IP blocked by WAFs (Cloudflare, etc.) and makes you look like a bot. Respectful delays avoid this.
• SMTP verification — Mail servers flag IPs making rapid RCPT TO requests. Your IP can get blacklisted, affecting your ability to send real email.
• Residential IPs are fragile — Unlike datacenter IPs, your home/office IP is shared across all your internet activity. Getting it blacklisted affects everything.

Guidelines for agents

Scenario	Recommended approach
Single domain lookup	Defaults are fine
Domain + name pattern guessing	Defaults are fine (15 SMTP checks covers all patterns)
Multiple domains in sequence	Add 5-10s pause between domains. Don't run more than 20 domains/day
Just need the email provider	Use --no-verify — DNS-only, zero risk
Bulk prospecting (50+ domains)	Use a paid service (Hunter.io, Apollo) or spread across multiple days

Key principle: The script is designed for targeted lookups, not mass scraping. If you need to process hundreds of domains, use a dedicated service with proper IP reputation management.

Limitations

• Website scraping depends on emails being visible in page source (won't find obfuscated/JS-rendered emails)
• Search engines may block automated queries
• SMTP verification requires outbound port 25 access
• Catch-all domains accept all addresses — can't confirm real inboxes
• Be respectful: the script adds delays between requests but don't run it in tight loops