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2026-02-25 23:23:23 -06:00

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XRayPDF

XRayPDF is a web app for sanitizing PDFs by extracting suspicious hidden content and producing cleaner outputs.

Instead of only "finding" hidden text, the pipeline is designed to help you remove or neutralize hidden layers by generating processed page images and exportable PDFs.

What the app does

Uploads a PDF (up to 10MB)
Renders each page server-side into images
Runs pixel sanitization on each page to neutralize low-contrast/hidden overlays
Runs per-page Tesseract OCR for text verification
Lets you review outputs in a 3-panel viewer (Original / Pixel / OCR)
Lets you download per-page files or convert processed pages into a single PDF

Extraction + removal workflow

Render original pages
- Each PDF page is rasterized to a PNG on the server.
- This gives a deterministic image baseline for analysis.
Pixel sanitization (removal path)
- Every rendered page goes through image processing (sharp):
  - flatten alpha to white background
  - grayscale
  - normalize contrast
  - sharpen edges
- Goal: make suspicious low-contrast hidden layers obvious and easier to remove/ignore in sanitized exports.
OCR verification (trust but verify)
- Tesseract runs page-by-page on server-rendered images.
- OCR text output helps validate what was present, even when visuals are ambiguous.
- If a processed image is not convincing, use OCR text as the secondary evidence channel.
Download + PDF conversion
- Download all per-page PNG/TXT files directly.
- Use the PDF button (Original and Pixel panels) to convert page images into one downloadable PDF.

How to use OCR output to find hidden text

If the image result looks unclear:

Open the OCR panel and inspect text per page.
Check low-confidence pages manually in the image panels.
Compare OCR text against expected visible text from the original.
Unexpected words, extra lines, or mismatched answers can indicate hidden content that the eye missed.

Stack

Next.js App Router
Prisma + PostgreSQL
NextAuth (Google)
pdfjs-dist for PDF parsing
@napi-rs/canvas for server-side rendering
sharp for image processing
tesseract.js for OCR
pdf-lib for image-to-PDF export

Local development

cd client
npm install
npm run dev

Open http://localhost:3000

Production Docker

Build:

cd client
docker build -t xraypdf:latest .

Run:

docker run --rm -p 3000:3000 \
  -e DATABASE_URL="postgresql://user:pass@host:5432/db" \
  -e NEXTAUTH_SECRET="your-secret" \
  -e NEXTAUTH_URL="http://localhost:3000" \
  -e GOOGLE_CLIENT_ID="your-google-client-id" \
  -e GOOGLE_CLIENT_SECRET="your-google-client-secret" \
  xraypdf:latest

Notes

OCR is designed as a verification step and should be reviewed with page images.
For best results, re-run analysis on a fresh upload if source PDF structure changes.

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