Automatically Redact Sensitive Data from PDFs and Save Them Securely

Jun 25, 2025·5 Minutes Read

What You'll Have When Done: An automated system that monitors Google Drive for confidential documents, redacts all sensitive information (SSN, credit cards, addresses, etc.), and saves the cleaned PDFs to a secure folder.

Prerequisites

Before you begin, make sure you have:

A PDF.co API Key
A Google Drive account with OAuth2 credentials in n8n
Two Google Drive folders:
- Source folder for confidential documents (Create one here)
- Destination folder for redacted documents
An n8n instance (cloud or self-hosted)
Sample employee records with sensitive data (Sample PDF)

Note: Some familiarity with regular expression (regex) is recommended to successfully redact documents.

Quick Start Options

Option A: I Want It Working Now

Import this workflow template → Download JSON File
Connect your Google Drive and PDF.co accounts
Set your source and destination folders
Test with a sample confidential document
Activate and run

Option B: I Want to Build It Step-by-Step

Follow the 6-step guide below to create the automation from scratch:

What This Automation Does (Overview):

Monitors a Google Drive folder for new confidential PDFs
Downloads each new document automatically
Uploads to PDF.co for processing
Redacts all sensitive data using regex patterns
Downloads the redacted PDF
Saves the clean document to a secure folder

IN THIS TUTORIAL

Monitor for New Confidential Documents

Download the Document

Upload to PDF.co

Redact Sensitive Information

Download Redacted PDF

Save to Secure Folder

Step 1: Monitor for New Confidential Documents

Node: Google Drive Trigger → File Created

Settings:

Trigger On: Changes Involving a Specific Folder
Folder to Watch: YOUR_CONFIDENTIAL_FOLDER
Watch For: File Created

Success Looks Like: The trigger fires whenever a new PDF is added to your confidential folder. The file metadata is passed to the next node.

Step 2: Download the Document

Node: Google Drive → Download

Settings:

Operation: Download
File by ID: {{ $json.id }}

Success Looks Like: The PDF file is downloaded as binary data, ready for processing.

Step 3: Upload to PDF.co

Node: PDF.co → Upload File

Settings:

Binary Data: True
File Name: file.pdf

Success Looks Like: The file is uploaded to PDF.co's temporary storage. You receive a URL for the uploaded file.

Step 4: Redact Sensitive Information

Node: PDF.co → Search & Replace Text or Delete

Settings:

Operation Type: Search and Delete Text
PDF URL:{{ $json.url }}
Add Search Patterns:

(?<=Name:\s)[A-Za-z\s]+(?=\s*Email)
(?<=Email:\s)[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}
(?<=Phone:\s)\([0-9]{3}\)\s[0-9]{3}-[0-9]{4}
(?<=SSN:\s)[0-9]{3}-[0-9]{2}-[0-9]{4}
(?<=Date of Birth:\s)[A-Za-z]+\s+\d{1,2},\s+\d{4}
(?<=Address:\s)[0-9]+\s[A-Za-z0-9\s,]+(?=\s*Credit Card)
(?<=Credit Card:\s)[0-9]{4}-[0-9]{4}-[0-9]{4}-[0-9]{4}
(?<=Employee ID:\s)EMP-[0-9]{4}-[0-9]{3}
(?<=Salary:\s)\$[0-9,]+

Advanced Options:
- Replacement Limit: 0
- Use Regular Expressions: True
- Custom Profiles: {"UsePatch": true, "PatchColor": "#000000"}

Success Looks Like: All sensitive data is replaced with black redaction boxes. The output URL points to the redacted PDF.

Note: These regex patterns are specifically designed for our sample employee record PDF. You’ll need to adjust them based on your document format and the fields you want to redact.

You can learn more about the PDF Search and Delete Text API at the API Docs.