Data Masking Tool: Mask Emails, Phones & Card Numbers | Free

A Yes, all processing happens locally in your browser. No data is sent to any server.

A Yes, you can use any single character like *, X, #, or _ for masking.

A Yes.

A Even though this is a browser-based text tool, you can easily mask data from a CSV. Simply open your CSV file in a text editor or spreadsheet program, copy the column or rows containing sensitive information, paste them into the tool's input area, and click mask. The anonymized text can then be copied back into your CSV or used as needed for testing or sharing. This ensures your PII is protected.

A Data masking permanently replaces sensitive information like emails or credit card numbers with realistic, non-sensitive substitutes, making the original data irrecoverable. It's ideal for creating safe test environments, sharing datasets for analytics, or any scenario where actual PII is not required. Encryption, conversely, transforms data into an unreadable format that can be reversed with a key, primarily for secure storage or transmission when the original data must eventually be accessed.

A Yes, you can run already-masked text through the tool again. It will only replace unmasked patterns, leaving existing masks untouched. For example, if you have "j***@domain.com", the tool won't re-mask the asterisk. This is useful when combining data from multiple sources. Just paste and click mask.

A Right now it only catches US format numbers like (555) 123-4567 or 555-123-4567. International formats with country codes or different digit groupings won't trigger masking. If you're working with non-US data, a quick workaround is to normalize numbers into a US-like pattern first. For example, strip the country code and add dashes. The tool will then mask them fine. This limitation is common among browser-based maskers that rely on simple pattern matching.

A It works on plain text only—PDFs can't be dropped in directly. But here's a trick: copy the text from your PDF, paste it into the tool, mask it, then paste back into the PDF viewer or editor. This takes about 30 seconds for a typical page. Just don't forget to check that the original layout isn't mangled after the swap.

A Paste the raw export text into the tool and click mask. It only replaces recognized patterns—emails, phones, credit cards, SSNs—so JSON keys, column headers, and XML tags stay intact. For example, "email": "john@example.com" becomes "email": "j***@e******.com". The structure survives. One caveat: if your export uses non-standard delimiters, test a small batch first. Works best with plain text formats like CSV, SQL dumps, or JSON.

A That's not a bug—it's a deliberate design choice. The first 6 digits of a credit card identify the issuer (like Visa or Mastercard), so they're left unmasked when you want to keep that info for testing. The tool defaults to masking everything after digit 6, ending with the last 4 digits visible. For example, 4111111111111111 becomes 411111******1111. You can override this by pasting individual numbers and manually editing the result, but the default saves time for most QA teams.