Original title: LeakageBench: Document-Level Leakage Risk for Redacting Personally Identifiable Information in Document Images
Vishnu Prasad Vijaya Kumar, Santhosh Venkatesh, Ivan P. Yamshchikov · September 2026
When people black out private information in pictures of documents, missing just one detail leaves the entire page unsafe. Real document images, like scans or screenshots, have messy layouts and visual noise that make this hard. Researchers built a test called LeakageBench to see if modern tools can safely redact these files. The system checks whether tools successfully find private data and prevent leaks across entire pages, rather than just grading individual words. They tested standard scanners, commercial detectors, and advanced visual models. They found that giving a model like GPT-5.5 extra coding tools helped it locate private items better. However, it still leaked sensitive information on 0.968 of the tested pages. Better detection tools still fail to make most documents safe.
Imagine you are blacking out names in a group photo with a marker. If you miss even one small name, that person's identity is exposed. Here, redacting personal data from documents is similar, and the test checks if every piece of information is hidden across the whole page.
Companies redacting PII from scans and screenshots often assume a page is safe if most identifiers are hidden. This benchmark shows that missing even one makes the entire document a privacy risk, affecting anyone whose data appears in these images.
The abstract does not specify limitations beyond showing that current methods are ineffective for full redaction. It focuses on 500 document images and GDPR-aligned PII, so it might not cover all scenarios or regions.
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LeakageBench: Document-Level Leakage Risk for Redacting Personally Identifiable Information in Document Images — Vishnu Prasad Vijaya Kumar, Santhosh Venkatesh, Ivan P. Yamshchikov
Abstract licence: CC0
Explanation generated by Synthesis from the abstract — it is not the original paper. This is a preprint, so it hasn't necessarily been peer reviewed.