Auto-Redact PII
Find and remove Aadhaar, PAN, cards, phones, emails…
How to use Auto-Redact PII
- 1Choose a PDF with text (scans need OCR first).
- 2Review what was found: Aadhaar, PAN, card and phone numbers, emails and more. Untick anything that should stay, or add your own words.
- 3Press “Redact selected” to download the cleaned PDF and a log of what was removed.
About this tool
Scans the text for personal data (Aadhaar, PAN, GSTIN, IFSC, UPI IDs, card numbers with checksum, phone numbers, emails, passport, bank accounts and more) plus any words you add, lets you review the matches, then permanently redacts them.
Your files stay on this device. SpitePDF opens and processes them inside your browser. The counter in the top bar shows how many bytes this page has sent to any server: it should read 0 B. How this works
Related tools
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- Remove PasswordUnlock a PDF you have the password for.
- Redact PDFBlack out areas permanently (text underneath is removed).
- Privacy Risk ScannerSee what personal data and hidden info a PDF contains.
- Remove Hidden DataStrip metadata, scripts, attachments, comments.
- Fingerprint PDFSHA-256, SHA-1 and MD5 hashes to prove a file is unchanged.
- Merge PDFCombine PDFs into one file, in the order you choose.
- Split PDFCut a PDF by page ranges, every N pages, or one file per page.
Questions
Is SpitePDF really free?
Yes. Every tool is free with no page limits, no sign-up and no watermark.
Are my files uploaded?
No. Files are opened and processed by your own browser. They never reach a server. The only things that use the network are optional: AI answers (if this site enables them) send the question plus relevant passages of text, never the file; P2P Share and the whiteboard connect two browsers directly.
Does it work offline?
Once a tool's engine has loaded, most tools keep working without a connection. OCR downloads its language data on first use and caches it.
Is there a file size limit?
No limit is imposed. Very large files are limited only by your device's memory; on phones, split or compress huge files first.