Credit Card Number Validator

Secure and instant credit card number validation

Verify credit card numbers safely, privately, and fast right in your browser. This validator checks whether a card number is structurally valid using the Luhn algorithm, detects the likely card brand from the number’s prefix, and gives real-time feedback as you type. It’s perfect for developers testing payment forms, QA teams validating inputs, businesses reducing data-entry errors, or anyone who needs to confirm that a number is formatted correctly before it’s sent to a payment gateway. Note: This tool does not verify available funds, account status, fraud risk, or authorization it confirms structure only.

Because validation happens entirely on your device, nothing is transmitted or stored. You can safely test sample numbers, anonymized data, or real inputs in a private environment. The validator is designed to be forgiving with input formatting (spaces and dashes are okay) and strict about the math and brand rules that actually matter.

How it works: the Luhn algorithm and card structure

At its core, credit card number validation is a checksum problem. The Luhn algorithm (Mod 10) catches common mistakes like typos or transposed digits by applying a predictable mathematical test to the entire number. If the sum lands on a multiple of 10, the number passes the check. Combined with card brand and length rules, Luhn screening offers a strong signal that a number is well-formed before you submit it to a processor.

1. Normalize input:
   The validator strips spaces and dashes so users can type naturally (e.g., “4111 1111 1111 1111” or “4111-1111-1111-1111”).
2. Apply brand heuristics:
   Based on the starting digits (IIN/BIN), the tool infers a likely brand (e.g., Visa, Mastercard, American Express, Discover, RuPay, JCB, Diners Club, UnionPay, Maestro). It also checks typical length requirements for that brand.
3. Run the Luhn check:
   Starting from the rightmost digit (the check digit), double every second digit. If doubling yields a two-digit number, sum those two digits. Add all digits together; if the total is divisible by 10, the number passes.
4. Report results:
   Brand and validity status update instantly. The visual card display and status text provide clear feedback (green for valid, red for invalid).

Card number anatomy

• IIN/BIN (Issuer Identification Number): The first 6–8 digits identify the issuing network or bank and help detect the brand.
• Account identifier: The middle digits represent the individual account; formats vary by issuer.
• Check digit: The last digit is calculated from the preceding digits using the Luhn algorithm.

Key features of our validator

• Luhn algorithm check: Robust Mod 10 validation catches common entry mistakes and ensures structural integrity.
• Automatic brand detection: Identifies major brands by prefix and length patterns: Visa, Mastercard, American Express, Discover, JCB, Diners Club, UnionPay, RuPay, and more.
• Real-time feedback: Instant “Valid/Invalid” status with brand identification as you type or paste.
• Client-side privacy: All checks run in your browser. Your card number never leaves your device.
• Interactive card display: A visual card updates with masked number formatting and the detected brand logo.
• Input flexibility: Accepts spaces and dashes; automatically normalizes formatting for clarity.
• Edge-case handling: Alerts for wrong length or unsupported patterns, even when the Luhn passes.

How to use the credit card validator

1. Step 1: Enter the card number
   Type or paste the number into the field. The tool formats the number for readability (e.g., 4-4-4-4 groupings for Visa/MC, 4-6-5 for Amex).
2. Step 2: View instant results
   Watch the status indicator and brand logo update as you type. You’ll see “Valid” or “Invalid” plus the detected brand.
3. Step 3: Confirm structure
   If “Valid,” the number is structurally sound. Proceed with your payment workflow or next validation steps (expiry, CVV, ZIP) in your own system.

Brand detection and typical length rules

Brand detection is based on common IIN/BIN ranges and length rules. While issuers can evolve ranges, these patterns are widely used for client-side guidance.

• Visa: Starts with 4; typical length 16 (sometimes 13 or 19 for legacy/issuer-specific cards).
• Mastercard: Typically starts with 51–55 or 2221–2720; length 16.
• American Express (Amex): Starts with 34 or 37; length 15; grouping often 4-6-5.
• Discover: Commonly starts with 6011, 622126–622925, 644–649, or 65; length 16.
• JCB: Often 3528–3589; length 16.
• Diners Club: Varies by region; many begin 300–305, 3095, 36, 38–39; length commonly 14 or 16.
• UnionPay: Typically starts with 62; lengths vary (16–19), depending on issuer.
• RuPay: Common Indian network; often starts 60, 65, 81, 82, 508; length usually 16.
• Maestro: Broad range (50, 56–69); lengths can vary (12–19); many modern Maestro cards are 16–19 digits.

Note: Passing Luhn with a matching prefix and length strongly suggests brand validity but does not guarantee card activation or acceptance. Issuer policies and gateways provide final validation at authorization time.

What this tool does and doesn’t validate

• Validates structure: Confirms number format via Luhn and checks brand/length heuristics.
• Does not verify funds or status: It cannot confirm balance, activation, fraud status, or whether the card will be authorized.
• No CVV/expiry check: The validator focuses on the primary account number. CVV, expiry date, ZIP/postcode, and address checks happen elsewhere.
• Not a BIN database: Brand detection relies on patterns, not a full issuer directory; exact issuer details are not provided.

Privacy and security

• Local-only processing: No network calls, no server storage. All logic executes in your browser.
• No tracking: The tool requires no sign-in and does not collect analytics tied to entered numbers.
• Masking and formatting: The UI can mask digits while preserving readable groupings to reduce over-shoulder exposure.
• Safe for testing: Use published test numbers or anonymized samples to validate your own forms and flows.

Developer-friendly behaviors

• Flexible input parsing: Accepts pasted numbers with spaces/dashes. Non-digit characters are ignored for validation.
• Live events: As you type, the validator emits updated state (brand guess, length, Luhn pass/fail) to guide UI.
• Brand-specific formatting: Applies grouping patterns by detected brand (e.g., 4-4-4-4 vs 4-6-5) to improve readability.
• Error states: Distinguishes “failed Luhn,” “wrong length,” and “unsupported pattern” so you can tailor messages.

Form UX best practices

• Auto-advance intelligently: Group digits and move cursor across groups without forcing users into separate fields.
• Inline validation: Provide gentle hints (brand icon, partial match) before final “valid/invalid” states to reduce friction.
• Clear error copy: Prefer specific, helpful messages like “Check the last two digits” over generic “Invalid number.”
• Secure display: Mask digits by default; reveal briefly on press-and-hold if needed for confirmation.
• Accessible labels: Associate inputs with clear labels and ARIA live regions for validation status.

PCI considerations and safe handling

• Do not store PANs: Unless you have a compelling compliance-compliant reason, avoid persisting full card numbers.
• Prefer tokenization: Use your payment processor’s client-side tokenization or hosted fields for production forms.
• Mask aggressively: Show only the final 4 digits whenever practical; log redacted data in test environments.
• HTTPS always: Serve forms over secure connections and avoid third-party scripts that don’t meet your security standards.

Test numbers and safe sandboxing

Most payment gateways publish test card numbers that always pass Luhn and simulate various outcomes. Use those in staging to exercise your flows without touching live networks. Examples vary by processor; never post real PANs in screenshots, tickets, or logs. If you need to demonstrate validation patterns, redact except the last 4 digits.

Common pitfalls and how to avoid them

• Luhn passes, brand fails: A number can pass the checksum but not match a brand’s length/prefix; show a brand-specific hint.
• Prefix updates: Networks occasionally expand BIN ranges; keep your detection rules updated to reduce false negatives.
• Whitespace-only errors: Some inputs copy “thin spaces” or non-breaking spaces; the validator normalizes them, but be cautious when pre-validating server-side.
• Localized digits: Users may paste numerals from non-Latin scripts; normalize if you accept global inputs.
• Transposed digits: Luhn will often catch “12” vs “21” mistakes; prompt users to re-check the last few digits.

Accessibility and usability

• Keyboard navigation: Fully operable with keyboard; no forced mouse usage for grouping or deletion.
• Screen reader support: Live region announcements for brand detection and validity changes.
• Color + text cues: Never rely on color alone; pair green/red with explicit “Valid/Invalid” text.
• Readable contrast: High-contrast design for digits and grouping to minimize visual strain.

Behavior with partial input

• Progressive detection: As digits increase, the brand guess stabilizes and formatting adapts accordingly.
• Deferred strictness: Only apply “invalid” state after enough digits are present to evaluate length and checksum meaningfully.
• Graceful fallback: If the brand can’t be inferred, default to generic formatting and Luhn-only validation.

Performance and limits

• Instant feedback: Luhn and brand checks are constant-time and efficient even on low-power devices.
• Large pastes: The validator trims input to a sane maximum length (e.g., 19 digits) to prevent UI glitches.
• No network dependency: With no external calls, validation remains responsive even offline.

Troubleshooting

• Valid format, declined later: Structure is fine, but the issuer declined authorization. Check expiry, CVV, and billing details or contact the bank.
• Brand mismatch: If the logo doesn’t match expectation, verify the first digits and full length; try re-entering without spaces.
• Copy/paste artifacts: Hidden characters can sneak in from documents. Type the number directly to rule this out.
• Unsupported range: Some regional or corporate cards use less-common patterns. Proceed to gateway authorization for a definitive result.

Frequently asked questions

• Does this tool check if the card is active or has funds? No. It only validates structure using Luhn and brand/length rules.
• Can I rely on this for fraud screening? No. Use your payment processor’s risk tools and 3-D Secure where appropriate.
• Is CVV or expiration verified? Not here. Validate those fields separately in your form or via your processor.
• Are numbers sent to a server? No. Validation runs locally in your browser, and inputs are not uploaded or stored.
• Why does a number pass Luhn but still show invalid? It may have the wrong length for the detected brand or an unsupported prefix.
• Does spacing matter? No. The validator ignores spaces and dashes; they’re just for readability.
• What about new BIN ranges? We use widely accepted patterns. For production forms, keep BIN detection rules updated to the latest network guidance.

Developer tips for integration

• Validate progressively: Show brand and partial validity early, final validity on blur/submit to reduce noise.
• Don’t block submit on brand guess: If Luhn passes but brand is unknown, let the gateway make the final call.
• Normalize before sending: Strip non-digits and send only the numeric PAN to your tokenization endpoint (or better use hosted fields).
• Log safely: Never log full PANs. If you must log, mask all but last 4 digits and avoid storing CVV altogether.

Responsible use

• User trust: Be transparent tell users you’re validating format locally and not storing data.
• Error empathy: When invalid, offer concise guidance like “Check the last digit” rather than generic warnings.
• Respect privacy: Mask digits promptly and avoid displaying full numbers in confirmation screens or emails.

Localization and regional considerations

• RuPay and domestic networks: Ensure your brand detection includes common Indian ranges where applicable.
• Number script normalization: If serving multilingual audiences, normalize non-Latin numerals to standard digits for validation.
• Address and ZIP rules: Pair PAN validation with region-appropriate postal formats and AVS checks downstream.

Security reminders

• Transport security: Always serve forms over HTTPS and use secure headers (CSP, HSTS) in production.
• Content security: Limit third-party scripts to trusted sources; avoid inlining untrusted code that can read inputs.
• Session hygiene: Don’t persist PANs in localStorage/sessionStorage. If you must hold them briefly, keep them in memory and discard on submit.

Find our tool with these keywords

Credit Card Validator, Luhn Algorithm Check, Validate Card Number, BIN Checker, Credit Card Test Tool, Mod 10 Validator, Check Credit Card Validity, Visa Validator, Mastercard Validator, Amex Validator.