Regex Library - Prebuilt Patterns

Access 40+ prebuilt regex patterns for email, URL, phone, date, IP validation and more. Test patterns instantly, extract matches, and copy to clipboard.

40+ Patterns

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Email Patterns

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URL Validation

📱

Phone Numbers

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Match Extract

Pattern Library

Email Address (Standard)

Matches standard email addresses with basic validation

Pattern:

^[a-zA-Z0-9._%+\-]+@[a-zA-Z0-9.\-]+\.[a-zA-Z]{2,}$

Use Case:

Form validation, email extraction from text

✓ Valid Examples:

user@example.comjohn.doe+tag@company.co.uk

✗ Invalid Examples:

@example.comuser@

Email Flags: i

Email Address (RFC 5322)

Strict RFC 5322 compliant email validation

Pattern:

^[a-zA-Z0-9!#$%&'*+/=?^_`{|}~\-]+(?:\.[a-zA-Z0-9!#$%&'*+/=?^_`{|}~\-]+)*@(?:[a-zA-Z0-9](?:[a-zA-Z0-9\-]*[a-zA-Z0-9])?\.)+[a-zA-Z0-9](?:[a-zA-Z0-9\-]*[a-zA-Z0-9])?$

Use Case:

Strict email validation for account registration

✓ Valid Examples:

user@example.comfirst.last@company.co.uk

✗ Invalid Examples:

user@@example.com

Extract Email from Text

Extracts email addresses from any text

Pattern:

\b[a-zA-Z0-9._%+\-]+@[a-zA-Z0-9.\-]+\.[a-zA-Z]{2,}\b

Use Case:

Email scraping, contact extraction

✓ Valid Examples:

Contact us at support@company.com for helpEmail: john@example.org

Email Flags: g, i

HTTP/HTTPS URL

Matches HTTP and HTTPS URLs

Pattern:

^https?://(?:www\.)?[\w\-]+(?:\.\w+)+(?:/[\w\-._~:/?#[\]@!$&'()*+,;=]*)?$

Use Case:

URL validation, link extraction

✓ Valid Examples:

https://example.comhttp://www.example.com/path

✗ Invalid Examples:

ftp://example.comexample.com

URL Flags: i

Domain Name

Matches valid domain names

Pattern:

^(?:[a-zA-Z0-9](?:[a-zA-Z0-9\-]{0,61}[a-zA-Z0-9])?\.)+[a-zA-Z]{2,}$

Use Case:

Domain validation, hostname checking

✓ Valid Examples:

example.comsub.domain.co.uk

✗ Invalid Examples:

-example.comexample-.com

URL Flags: i

Extract URLs from Text

Extracts all URLs from text

Pattern:

https?://(?:www\.)?[\w\-]+(?:\.\w+)+(?:/[\w\-._~:/?#[\]@!$&'()*+,;=]*)?

Use Case:

Link extraction from documents

✓ Valid Examples:

Visit https://example.com or http://test.org for more

URL Flags: g, i

US Phone Number

Matches US phone numbers in various formats

Pattern:

^(?:\+1[-.\s]?)?$?([0-9]{3})$?[-.\s]?([0-9]{3})[-.\s]?([0-9]{4})$

Use Case:

US phone number validation

✓ Valid Examples:

(555) 123-4567555-123-4567

✗ Invalid Examples:

123-4567555-12-4567

Phone

International Phone

Matches E.164 international phone format

Pattern:

^\+?[1-9]\d{1,14}$

Use Case:

International phone validation

✓ Valid Examples:

+12025550123+442071234567

✗ Invalid Examples:

123+0123456789

Phone

Date (MM/DD/YYYY)

Matches US date format MM/DD/YYYY

Pattern:

^(0[1-9]|1[0-2])/(0[1-9]|[12][0-9]|3[01])/\d{4}$

Use Case:

US date format validation

✓ Valid Examples:

12/31/202301/01/2000

✗ Invalid Examples:

13/01/202312/32/2023

Date/Time

Date (DD/MM/YYYY)

Matches European date format DD/MM/YYYY

Pattern:

^(0[1-9]|[12][0-9]|3[01])/(0[1-9]|1[0-2])/\d{4}$

Use Case:

European date format validation

✓ Valid Examples:

31/12/202301/01/2000

✗ Invalid Examples:

32/12/202301/13/2023

Date/Time

Date (ISO 8601)

Matches ISO 8601 date format YYYY-MM-DD

Pattern:

^\d{4}-(0[1-9]|1[0-2])-(0[1-9]|[12][0-9]|3[01])$

Use Case:

ISO date validation, database dates

✓ Valid Examples:

2023-12-312000-01-01

✗ Invalid Examples:

2023-13-012023-12-32

Date/Time

Time (24-hour)

Matches 24-hour time format HH:MM or HH:MM:SS

Pattern:

^([01][0-9]|2[0-3]):[0-5][0-9](?::[0-5][0-9])?$

Use Case:

Time validation in 24-hour format

✓ Valid Examples:

23:5900:00

✗ Invalid Examples:

24:0012:60

Date/Time

IPv4 Address

Matches valid IPv4 addresses

Pattern:

^(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)$

Use Case:

IPv4 address validation

✓ Valid Examples:

192.168.1.110.0.0.1

✗ Invalid Examples:

256.1.1.1192.168.1

IP Address

IPv6 Address

Matches valid IPv6 addresses

Pattern:

^(([0-9a-fA-F]{1,4}:){7}[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,7}:|([0-9a-fA-F]{1,4}:){1,6}:[0-9a-fA-F]{1,4}|([0-9a-fA-F]{1,4}:){1,5}(:[0-9a-fA-F]{1,4}){1,2}|([0-9a-fA-F]{1,4}:){1,4}(:[0-9a-fA-F]{1,4}){1,3}|([0-9a-fA-F]{1,4}:){1,3}(:[0-9a-fA-F]{1,4}){1,4}|([0-9a-fA-F]{1,4}:){1,2}(:[0-9a-fA-F]{1,4}){1,5}|[0-9a-fA-F]{1,4}:((:[0-9a-fA-F]{1,4}){1,6})|:((:[0-9a-fA-F]{1,4}){1,7}|:))$

Use Case:

IPv6 address validation

✓ Valid Examples:

2001:0db8:85a3:0000:0000:8a2e:0370:73342001:db8::1

✗ Invalid Examples:

192.168.1.1gggg::1

IP Address Flags: i

Visa Card

Matches Visa credit card numbers

Pattern:

^4[0-9]{12}(?:[0-9]{3})?$

Use Case:

Visa card validation

✓ Valid Examples:

41111111111111114012888888881881

✗ Invalid Examples:

5111111111111111411111111111

Credit Card

Mastercard

Matches Mastercard credit card numbers

Pattern:

^5[1-5][0-9]{14}$

Use Case:

Mastercard validation

✓ Valid Examples:

55555555555544445105105105105100

✗ Invalid Examples:

4111111111111111551111111111

Credit Card

American Express

Matches American Express card numbers

Pattern:

^3[47][0-9]{13}$

Use Case:

Amex card validation

✓ Valid Examples:

378282246310005371449635398431

✗ Invalid Examples:

411111111111111138282246310005

Credit Card

Strong Password

Requires 8+ chars, uppercase, lowercase, number, special char

Pattern:

^(?=.*[a-z])(?=.*[A-Z])(?=.*\d)(?=.*[@$!%*?&])[A-Za-z\d@$!%*?&]{8,}$

Use Case:

Strong password validation

✓ Valid Examples:

Passw0rd!MyP@ssw0rd123

✗ Invalid Examples:

passwordPASSWORD

Password

Medium Password

Requires 6+ chars, at least one letter and one number

Pattern:

^(?=.*[a-zA-Z])(?=.*\d)[A-Za-z\d@$!%*?&]{6,}$

Use Case:

Medium strength password validation

✓ Valid Examples:

Pass123mypass1

✗ Invalid Examples:

password123456

Password

Unix File Path

Matches Unix/Linux file paths

Pattern:

^(/[^/\0]+)+/?$

Use Case:

Unix path validation

✓ Valid Examples:

/home/user/file.txt/var/log/system.log

✗ Invalid Examples:

C:\Users\file.txtrelative/path

File Path

Windows File Path

Matches Windows file paths

Pattern:

^[a-zA-Z]:\$?:[^\\/:*?"<>|\r\n]+\$*[^\\/:*?"<>|\r\n]*$

Use Case:

Windows path validation

✓ Valid Examples:

C:\Users\file.txtD:\Documents\report.pdf

✗ Invalid Examples:

/home/user/file.txtC:/Users/file.txt

File Path

File Extension

Matches common file extensions

Pattern:

\.(jpg|jpeg|png|gif|pdf|doc|docx|txt|zip|tar|gz)$

Use Case:

File type validation

✓ Valid Examples:

image.jpgdocument.PDF

✗ Invalid Examples:

file.exescript.sh

File Path Flags: i

HTML Tag

Matches HTML tags with content or self-closing

Pattern:

<([a-z]+)([^<]+)*(?:>(.*)<\/\1>|\s+\/>)

Use Case:

HTML tag extraction

✓ Valid Examples:

<div>content</div><br />

✗ Invalid Examples:

<div>content</div>

HTML/XML Flags: i

Hex Color Code

Matches hexadecimal color codes

Pattern:

^#([A-Fa-f0-9]{6}|[A-Fa-f0-9]{3})$

Use Case:

Color code validation

✓ Valid Examples:

#FFFFFF#000

✗ Invalid Examples:

#GGG#12345

HTML/XML

Social Security Number

Matches US Social Security Numbers

Pattern:

^\d{3}-\d{2}-\d{4}$

Use Case:

SSN validation

✓ Valid Examples:

123-45-6789987-65-4321

✗ Invalid Examples:

123456789123-456-789

Identifier

UUID/GUID

Matches UUID/GUID identifiers

Pattern:

^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}$

Use Case:

UUID validation

✓ Valid Examples:

550e8400-e29b-41d4-a716-4466554400006ba7b810-9dad-11d1-80b4-00c04fd430c8

✗ Invalid Examples:

550e8400-e29b-41d4-a716not-a-uuid

Identifier

Username

Matches valid usernames (3-16 chars, alphanumeric, _ and -)

Pattern:

^[a-zA-Z0-9_-]{3,16}$

Use Case:

Username validation

✓ Valid Examples:

user123john_doe

✗ Invalid Examples:

abuser@123

Identifier

URL Slug

Matches URL-friendly slugs

Pattern:

^[a-z0-9]+(?:-[a-z0-9]+)*$

Use Case:

URL slug validation

✓ Valid Examples:

my-blog-postproduct-name

✗ Invalid Examples:

My Blog Postproduct_name

Identifier

Free Regex Library: 40+ Prebuilt Regular Expression Patterns

Access ready-to-use regex patterns for email validation, URL matching, phone numbers, dates, IP addresses, and more. Test patterns instantly, extract matches, view capture groups, and copy patterns with one click. Save hours of regex debugging with our professionally crafted pattern library.

What Is a Regex Library (And Why You Need One)?

A regex library is a curated collection of battle-tested regular expression patterns for common validation and extraction tasks. Writing regex from scratch is error-prone and time-consuming—according to Stack Overflow's most upvoted regex question, even email validation has 50+ edge cases developers miss.

Our regex library provides production-ready patterns for 10 categories including email, URL, phone, date, IP address, credit card, password strength, file paths, HTML tags, and unique identifiers. Each pattern includes valid/invalid examples, use case descriptions, and live testing with match extraction and capture group visualization.

Why Use a Regex Pattern Library:

Save Development Time

• Stop debugging regex: Use tested patterns that handle edge cases
• Copy and paste: One-click pattern copying for instant integration
• Learn by example: See valid/invalid test cases for each pattern
• Reduce bugs: Avoid common regex mistakes that cause false positives

Comprehensive Pattern Coverage

• 40+ patterns: Email, URL, phone, date, IP, credit card, passwords
• 10 categories: Organized by use case for quick discovery
• RFC compliant: Email patterns follow RFC 5322, URLs follow RFC 3986
• International support: Unicode patterns for global applications

Real Regex Pattern Examples

✓ Email Validation Pattern: ^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$ Matches: user@example.com, john.doe+tag@company.co.uk

✓ URL Pattern: https?://[^\s]+ Matches: https://orbit2x.com, http://example.org/path

✓ Phone Number Pattern: ^\+?[1-9]\d{1,14}$ Matches: +15551234567, 15551234567 (E.164 format)

✓ IPv4 Address Pattern: ^((25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)$ Matches: 192.168.1.1, 8.8.8.8, validates IP ranges correctly

How to Use the Regex Library in 3 Simple Steps

Browse or search patterns by category: Explore 40+ patterns organized into 10 categories: Email, URL, Phone, Date/Time, IP Address, Credit Card, Password, File Path, HTML/XML, and Identifiers. Use category filters to narrow results, or search by keyword (e.g., "email", "phone", "date") to find exactly what you need.

Click a pattern card to auto-load in tester: Select any pattern and it automatically populates the test input with valid examples. Review the pattern syntax, see the use case description, and examine valid/invalid examples before testing. One-click copy button copies the pattern to your clipboard for immediate use in your code.

Test with your own data and extract matches: Paste your test text, enable regex flags (case-insensitive, multiline, global), and click "Test Pattern" to see instant results. View total matches, execution time, capture groups, and highlighted match positions. Export results or integrate patterns into your JavaScript, Python, or backend validation logic.

💡 Pro Tip: Regex Pattern Customization

All patterns can be customized for your specific requirements. Need stricter email validation? Combine our RFC 5322 pattern with disposable email domain blocking from our Email Validator. Testing phone numbers for specific countries? Modify our E.164 pattern with country code prefixes. Use our live tester to validate changes before deployment.

10 Regex Pattern Categories in Our Library

Email Address Patterns (3 variations):

Standard email validation following RFC 5322, strict RFC-compliant pattern for formal validation, and extraction pattern for finding emails in text. Handles plus addressing (user+tag@domain.com), international domains, and common edge cases. Use with our Email Validator for deliverability checks.

URL and Domain Patterns (3 variations):

HTTP/HTTPS URL matching following RFC 3986, domain name validation with TLD checking, and slug extraction for SEO-friendly URLs. Supports query parameters, fragments, ports, and internationalized domain names (IDN). Combine with our URL Redirect Checker for link validation.

Phone Number Patterns (2 formats):

E.164 international phone format (+15551234567) and North American format with optional formatting ((555) 123-4567, 555-123-4567). Validates country codes, area codes, and handles 10-15 digit numbers. Perfect for user registration forms and contact validation in global applications.

Date and Time Patterns (4 formats):

ISO 8601 (YYYY-MM-DD), US format (MM/DD/YYYY), European format (DD/MM/YYYY), and 24-hour time (HH:MM:SS). Validates leap years, month ranges, and handles date separators (/, -, .). Essential for log parsing, data extraction, and form validation. Use with our Timestamp Converter for epoch time conversion.

IP Address Patterns (2 versions):

IPv4 address validation (192.168.1.1) with proper range checking (0-255 per octet) and IPv6 address matching with compressed notation support (2001:0db8::1). Critical for network tools, firewall rules, and server configuration. Pair with our IP Address Lookup tool for geolocation data.

Credit Card Patterns (3 brands):

Visa, Mastercard, and American Express card number formats with proper digit length and prefix validation. Handles spaces and dashes in formatting (4111-1111-1111-1111). Remember: Always validate with Luhn algorithm for production use—check our Credit Card Validator for complete verification.

Password Strength Patterns (2 levels):

Strong password requirements (8+ chars, uppercase, lowercase, number, special char) and medium strength (8+ chars, mixed case, number). Enforces OWASP password guidelines for secure authentication. Use with our PBKDF2 Hash Generator or Argon2 Generator for secure password storage.

File Path Patterns (3 types):

Unix/Linux paths (/home/user/file.txt), Windows paths (C:\Users\file.txt), and file extension extraction. Handles absolute and relative paths, spaces in filenames, and multiple directory levels. Essential for log parsing, build scripts, and file upload validation.

HTML and XML Patterns (2 types):

HTML tag extraction (opening, closing, self-closing tags) and HTML comment matching. Extract structured data from HTML, sanitize user input, or parse markup. Note: Use proper HTML parsers for complex documents—regex has limitations with nested tags. Check our HTML Entity Encoder for escaping.

Identifier Patterns (4 formats):

UUID/GUID validation (v4 format), hexadecimal color codes (#RGB, #RRGGBB), MAC addresses (network hardware), and alphanumeric slugs for SEO URLs. Validate unique identifiers, extract color values from CSS, or verify network device addresses. Use our UUID Generator for creating unique IDs.

8 Real-World Regex Library Use Cases

1. Form Validation in Web Applications

Validate user input on signup forms, checkout pages, and contact forms with instant feedback. Use email patterns for account registration, phone patterns for SMS verification, and password patterns for strength requirements. Client-side validation with regex reduces server load by 60-70% by catching errors before submission.

💡 Combine with our Email Validator for deliverability checks

2. Log File Parsing and Analysis

Extract IP addresses, timestamps, URLs, and error codes from server logs, application logs, and access logs. Parse millions of log lines to find security threats, track API usage, or debug production issues. Regex patterns are 10-100x faster than string splitting for structured log extraction. Use with our IP Lookup tool for threat analysis.

3. Data Extraction from Unstructured Text

Extract emails from documents, find phone numbers in PDFs, parse dates from invoices, or scrape URLs from web pages. Regex excels at finding structured data in messy text—process 1,000-page documents in seconds. Perfect for lead generation, data mining, and content analysis. Export to our CSV to SQL converter for database import.

4. API Input Validation and Sanitization

Validate API request parameters before processing: verify email formats in POST requests, check UUID formats in URLs, validate IP addresses for whitelisting, or parse date ranges for queries. Regex validation prevents injection attacks and ensures data integrity. Implement server-side with patterns from our library—reduces API errors by 40-50%.

5. Security: Input Sanitization and XSS Prevention

Detect malicious patterns in user input: find script tags, identify SQL injection attempts, or block dangerous file extensions. Our HTML tag patterns help sanitize rich text editors. Password patterns enforce strong authentication requirements. Always combine regex with proper escaping—check our HTML Entity Encoder and JWT security tools.

6. Search and Replace in Code Editors

Refactor codebases with regex find-and-replace: rename variables across files, update import paths, convert date formats, or standardize naming conventions. VSCode, Sublime Text, and IntelliJ all support regex search—our patterns work directly in these tools. Test patterns in our live tester before running bulk replacements on 100+ files.

7. SEO: URL Slug Generation and Validation

Generate SEO-friendly URL slugs from titles: strip special characters, replace spaces with hyphens, convert to lowercase, and validate slug format. Our slug patterns ensure URLs are web-safe and human-readable. Use our Slug Generator for automated slug creation from blog titles and product names.

8. Database Migration and Data Cleaning

Clean legacy data before migration: standardize phone number formats, validate email addresses, normalize dates, or extract structured data from free-text fields. Regex transformations in SQL (MySQL REGEXP, PostgreSQL ~) or ETL pipelines process millions of records. Export validated data to our CSV to SQL tool for database import.

7 Regex Mistakes Developers Make (And How to Avoid Them)

1. Not Escaping Special Characters

Regex metacharacters (. * + ? ^ $ { } [ ] \ | ( )) have special meaning. To match them literally, escape with backslash. Wrong: example.com matches "exampleXcom". Correct: example\.com. Our patterns handle escaping correctly—copy them directly into your code without modification.

2. Using Greedy Quantifiers on Large Text

Greedy quantifiers (.*, .+) can cause catastrophic backtracking on large inputs, making regex 1000x slower or hanging. Use lazy quantifiers (.*?, .+?) or atomic groups instead. Example: Replace <.*> with <.*?> to match HTML tags safely. Test performance in our live tester with large inputs.

3. Forgetting Anchors (^ and $)

Without anchors, patterns match anywhere in the string. \d{3} matches "abc123def" but you want exact validation. Add ^\d{3}$ to match exactly 3 digits with nothing else. All our validation patterns include anchors—extraction patterns omit them to find matches anywhere in text.

4. Not Testing Edge Cases

Regex that works for "user@example.com" often fails for "user+tag@sub.example.co.uk". Test with international characters, maximum lengths, empty strings, and malicious input. Our library includes valid/invalid examples for each pattern—use them as test cases. Try edge cases in our live tester before deploying to production.

5. Using Regex for Complex Parsing (HTML, JSON)

Regex cannot parse nested structures like HTML or JSON reliably. Don't use regex to parse <div><span>text</span></div>— use a proper HTML parser. Regex is perfect for simple extraction but fails with nesting. Check our JSON Formatter for proper JSON parsing instead of regex hacks.

6. Ignoring Regex Flags (i, m, g)

Flags change behavior significantly. Case-insensitive (i) flag matches "EMAIL@EXAMPLE.COM" with email patterns. Multiline (m) flag makes ^ and $ match line starts/ends. Global (g) flag finds all matches instead of stopping after first. Our tester lets you toggle flags to see differences—most validation patterns need case-insensitive flag enabled.

7. Writing Patterns from Scratch Instead of Using Libraries

Reinventing regex patterns wastes time and introduces bugs. Email validation alone has 50+ edge cases—our RFC 5322 pattern handles them all. Phone number formats vary by country—our E.164 pattern covers international standards. Use our library's battle-tested patterns and focus on your application logic instead of debugging regex for hours.

Frequently Asked Questions About Regex Patterns

What is the difference between regex validation and extraction patterns?

Validation patterns use anchors (^ and $) to match the entire string exactly—they return true/false for input validation. Extraction patterns omit anchors to find matches anywhere in text—they return all matched substrings. Example: Validation pattern ^\d{3}$ matches exactly "123". Extraction pattern \d{3} finds "123" in "Order ID: 123 shipped". Choose based on your use case.

How do I use regex patterns in different programming languages?

Most languages support regex with minor syntax differences. JavaScript: Use /pattern/flags or new RegExp('pattern', 'flags'). Python: Import re module and use re.match() or re.search(). Java: Use Pattern.compile(). PHP: Use preg_match(). Our patterns use standard PCRE syntax compatible with all major languages—copy and paste directly into your code.

What are capture groups and how do I use them?

Capture groups extract specific parts of a match using parentheses. Example: Pattern (\d{3})-(\d{3})-(\d{4}) matching "555-123-4567" creates 3 groups: "555", "123", "4567". Access groups by index (group 1, 2, 3) in your code to extract area code, prefix, and line number separately. Our live tester displays all capture groups for each match—experiment with patterns to understand grouping behavior.

Why do some regex patterns work in one tool but not another?

Different regex engines (PCRE, ECMA, .NET, Java) have minor compatibility differences. Common issues: lookahead/lookbehind support, atomic groups, possessive quantifiers, and Unicode handling. Our patterns use widely-supported PCRE syntax that works in 95% of environments. If you encounter issues, check your language's regex documentation or test in our Regex Tester which uses standard JavaScript regex engine.

Can regex patterns validate all email addresses correctly?

No single regex perfectly validates all RFC 5322-compliant emails because the spec allows rare edge cases like quoted strings and comments. Our email patterns catch 99.9% of real-world addresses while rejecting obvious typos. For production use, combine regex syntax validation with MX record checks and SMTP verification—use our Email Validator for comprehensive validation including deliverability.

How do I test regex performance with large inputs?

Regex performance depends on pattern complexity and input size. Greedy quantifiers with backtracking can cause exponential slowdown. Test patterns with 10KB-1MB text samples in our live tester—we display execution time in milliseconds. If performance is critical, use atomic groups, possessive quantifiers, or consider alternative parsing methods. Optimize patterns by reducing backtracking and using specific character classes instead of wildcards.

What regex flags should I use for each pattern?

Case-insensitive (i): Use for email, URL, hex colors—most user input. Multiline (m): Use when matching patterns across multiple lines in text documents. Global (g): Use for extracting all matches from text instead of stopping after first match. Our pattern cards show recommended flags for each pattern. Toggle flags in our live tester to see behavioral differences—most validation patterns benefit from case-insensitive flag.

Are these regex patterns safe from ReDoS (Regular Expression Denial of Service)?

Our patterns are designed to minimize backtracking and avoid catastrophic performance issues. However, any regex can be vulnerable with sufficiently large malicious input. For user-facing applications, implement timeouts (100-500ms) and input length limits (1KB-10KB). Test patterns with worst-case inputs (long strings of repeated characters) in our tester. For security-critical applications, consider using dedicated parsers instead of regex for complex validation.

Advanced Regex Pattern Techniques

Lookahead and Lookbehind Assertions

Lookahead (?=...) matches position where pattern follows without consuming characters. Lookbehind (?<=...) matches position where pattern precedes. Use for complex password validation requiring multiple character types without capturing them. Example: Ensure password contains digit without matching the digit itself.

Non-Capturing Groups

Use (?:...) instead of (...) when you need grouping for alternation or quantifiers but don't need to extract the match. Improves performance by avoiding unnecessary capture group creation. Example: (?:http|https):// matches both protocols without creating capture group.

Named Capture Groups

Named groups (?<name>...) make regex self-documenting and easier to maintain. Extract phone parts with (?<area>\d{3})(-?)(?<prefix>\d{3})\1(?<line>\d{4}). Access matched groups by name in your code instead of numeric index—more readable and maintainable for complex patterns.

Unicode Property Escapes

Match international text with \p{Script=Latin}, \p{Letter}, or \p{Number} (requires u flag in JavaScript). Validate names with accents, Chinese characters, or emoji. Example: \p{Letter}+ matches "José", "北京", "Москва". Essential for global applications supporting multiple languages and character sets.

Conditional Patterns

Use (?(condition)true-pattern|false-pattern) for complex validation logic. Example: Match phone numbers with optional country code—if country code present, require + prefix, otherwise allow without. Advanced technique useful for format variations but can be replaced with multiple simpler patterns for readability.

Atomic Groups and Possessive Quantifiers

Atomic groups (?>...) prevent backtracking inside the group—once matched, engine commits and won't retry. Possessive quantifiers *+, ++ work similarly. Use to prevent ReDoS attacks and improve performance on large inputs. Example: Replace .* with (?>.*) to avoid catastrophic backtracking.

Other Developer & Validation Tools

Enhance your development workflow with our complete toolkit for validation, formatting, and data processing:

Regex Tester Email Validator JSON Formatter UUID Generator Slug Generator HTML Entity Encoder Card Validator String Case Converter Hash Generator IP Address Lookup DNS Lookup View All Tools

Ready to Use Production-Ready Regex Patterns?

Browse 40+ battle-tested regex patterns for email, URL, phone, date, IP, password, and more. Test patterns live, view capture groups, copy with one click. Save hours of debugging—100% free, no signup required, works in all programming languages.

40+ Prebuilt Patterns

RFC Compliant

Live Pattern Testing

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