Extract Emails, Phones & IBANs - Free Online Browser Tool

Pull every email address, phone number and IBAN out of a PDF into a report. Runs in your browser, nothing is uploaded.

A PDF that has been emailed around for three years accumulates contact details in its margins. Finding them means reading every page and typing them out by hand, which is where transposed digits come from. This tool reads the text layer and lists what is actually there: every email address, every phone-shaped run of digits, and every IBAN - each with the page it came from, so a result can be checked before anyone is sent something. Output is a readable report and a spreadsheet, so it can go straight into the sheet you are already working in. Two things are handled with more care than a plain search would. An IBAN is only reported if it passes its own mod-97 check digit, which is why the tool does not hand you an account reference that merely looks like one. And a phone number is the weak spot of any such scan: a long digit run can be an invoice number, an order number or a timestamp. Those are listed too, but marked so you can read them rather than trust them. The text layer is what gets searched. A scan has nothing to read until OCR has run on it, and the tool says so rather than quietly returning an empty report that looks like the document contains no contacts at all.

This extract emails, phones & ibans utility runs completely inside your web browser. Your document is opened locally and processed on your own device using JavaScript and WebAssembly, so your file is never uploaded to any server. There is no signup, no watermark and no limit on how many documents you can handle.

  • 100% client-side - files never leave your device
  • Instant processing, no upload wait
  • Works on desktop, tablet and mobile
  • Free forever, no account required

Common next steps: Extract Plain Text, Search Text in PDF, Extract Metadata.

How to Use the Extract Emails, Phones & IBANs Tool

Four steps, and the whole thing runs locally on your own device.

  1. Load the PDF

    Every page is read. A scan has no text to find, so run OCR first and the same document will give up its contacts.

  2. Choose what to look for

    All three, or just emails, just phone numbers, or just IBANs. Narrowing it makes a long report far easier to read.

  3. Read what came back before you use it

    Every entry names the page it was found on, and the phone numbers are marked for checking - a run of digits can be an invoice number rather than a telephone number.

  4. Download the report and the sheet

    A report to read and a CSV to import, both listing the page each item came from so a result can be verified.

Frequently Asked Questions

Why are so many "phone numbers" wrong?

Because a run of seven digits or more is not always a phone number - it is often an invoice number, a customer reference or a timestamp. Those are included rather than hidden, and flagged, so you can read them instead of trusting them.

What makes an IBAN reliable enough to report?

Its own check digits. Every IBAN carries a mod-97 value in its last two characters, and only a number that produces the right answer is a real one. The tool runs that test, which is why a reference like NOTANIBAN1234567890 never appears in the results.

Will this find addresses in an image of a page?

No. It reads the text layer, and a scan or a photographed page has none until OCR has added one. Run OCR PDF on the document first, then this tool will find everything in it.

What format comes out?

Both: a readable .txt report grouped by kind, and a .csv with the type, the value and the page number, ready to import into a spreadsheet.

Is my document uploaded to look for contacts?

No. The text is read in this tab and the results are written here. Nothing about the document or what was found in it travels anywhere.