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Drop a PDF to scan for metadata

Scanning...

About Privacy Scanner

PDFs quietly carry metadata — author names, software versions, timestamps, and even GPS coordinates — that can reveal more than you intend. ILikePdf Privacy Scanner inspects a file locally and reports the embedded metadata so you know exactly what is inside before sharing. Pair the scan with the Flatten tool to strip discovered data and produce a clean copy. The scan never uploads your document, which makes it safe even for sensitive files.

How to scan a PDF for hidden data Privacy Scanner

Step 1: Upload the PDF you want to inspect.
Step 2: The scanner analyzes the file locally for embedded metadata.
Step 3: Review findings: author names, software used, timestamps, GPS data, and hidden text.
Step 4: Use the report to decide what to clean before sharing.
Step 5: Pair with the Flatten tool to strip discovered metadata.

Common use cases for Privacy Scanner

Pro tips

Frequently Asked Questions

What does a PDF privacy scanner check for?

The scanner analyses your PDF for hidden metadata: author names, document revision history, hidden layers, embedded files, comments and annotations, form data, geolocation tags, and invisible text or images.

Can I remove detected privacy risks?

Yes. After scanning, you can selectively remove each risk category — strip all metadata, delete hidden layers, remove annotations, and purge embedded files with one click.

Does the privacy scanner process files locally?

Yes. All scanning and sanitization runs locally in your browser. Your document never leaves your device, ensuring maximum privacy during the privacy check itself.

What metadata is commonly found in PDFs?

Most PDFs contain author name, software version, creation/modification timestamps, and sometimes document serial numbers. Corporate PDFs often include editor names from tracked changes.

Can I scan PDFs in batch?

Yes. Upload multiple PDFs and scan them simultaneously. Each file gets a detailed privacy risk report with severity levels for each type of hidden data found.

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