Linoy Levy

If you had to pick one file format that carries the bulk of your organization’s most sensitive documents, it would be PDF.

Contracts and NDAs, medical records, financial statements, invoices, tax forms, legal filings, HR packets - all of them default to PDF, and all of them tend to be copied, emailed, uploaded, and archived far beyond the systems where they originated. Adobe estimates there are trillions of PDFs in circulation; for most enterprises, a non‑trivial percentage of those live in cloud storage with overly broad access controls.

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Despite that, many data security programs still treat PDF scanning as an afterthought. Tools that are perfectly happy parsing an email body or a CSV row suddenly become half‑blind when you hand them a complex multi‑page PDF,  and completely blind if that PDF is just a scanned image.

That is exactly the gap we set out to close with PDF scanning for data security in Sentra.

Why PDFs Are a First‑Class Data Security Risk

PDFs sit at the intersection of three uncomfortable truths:

• They are the default format for high‑risk documents like contracts, patient records, tax filings, and financial reports.
• They are easy to copy and spread - attached to emails, dropped into shared drives, uploaded to SaaS tools, and mirrored into backups.
• They are often opaque to legacy DLP and discovery tools, especially when content is embedded in images or complex layouts.

From a risk perspective, treating PDFs as “less important than databases” makes no sense. If anything, the opposite is true: a single mis‑shared PDF can expose entire customer lists, PHI packets, or undisclosed financials in one move.

How Sentra Scans PDFs for Sensitive Data

Sentra’s PDF scanning is built on the same file parser framework we use for other unstructured formats, with specialized handling for both native text PDFs and image‑based PDFs. Our engine operates in two complementary modes.

Text Mode: Deep Inspection of Native PDF Content

In text mode, we extract all embedded text from each page and separately detect and pull out tables.

That distinction matters. In invoices, financial statements, and tax forms, the critical data often lives in rows and columns, not in narrative paragraphs. Sentra:

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• Detects table boundaries in PDFs.
• Extracts cell values into a tabular representation.
• Treats those cells as structured data, not just part of a flat text blob.

Once extracted, this structured view flows into Sentra’s classification engine, which analyzes it with specialized classifiers for:

• PII such as names, email addresses, national IDs, and phone numbers.
• Financial data such as account numbers, routing codes, and transaction details.
• Regulated records such as tax identifiers or health‑related codes.

This approach is far more precise than a naive “search the whole document for 16‑digit numbers” method. It lets you distinguish, for example, between a random ID in the footer and a full set of cardholder details in an itemized table.

Image Mode: Solving the Scanned PDF Problem

A huge fraction of enterprise PDFs are actually just images of paper forms: patient intake sheets, signed contracts, faxed tax returns, screenshots dumped into PDF containers. To a legacy DLP engine, those documents are empty. To Sentra, they are just another OCR input.

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Sentra:

• Detects embedded images in PDF pages.
• Extracts those images safely, including JPEG‑compressed content.
• Processes them through our ML‑based OCR pipeline built on transformer‑style models.
• Passes the resulting text into the same classifier stack we use for native text.

The result is that a scanned W‑2 receives the same depth of inspection as a digitally generated one. No practical difference, no exceptions.

Metadata, Encryption, and Hidden Exposure

Most tools stop at visible text. Sentra goes further.

PDF Metadata as a Data Source

PDF metadata can leak far more than people expect:

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• Author names and usernames
• Internal file paths and system details
• Document titles and descriptions that reference customers or projects

Sentra parses this metadata, normalizes it, and runs it through the same unstructured classification engine we use for body text and document context. That makes it possible to surface cases where you are unintentionally exposing sensitive details in fields that almost never get reviewed.

Encrypted and Password‑Protected PDFs

Password‑protected or encrypted PDFs are not invisible to Sentra. When our scanners encounter PDFs that cannot be opened for content inspection, we still:

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• Identify them as PDFs.
• Record their location and basic properties.
• Surface them in your inventory so you can see where opaque, potentially sensitive PDFs are accumulating, instead of silently skipping them.

In practice, a cluster of unreadable encrypted PDFs in an unexpected bucket is often a sign of data hoarding, shadow IT, or deliberate attempts to evade controls.

Security Architecture – Scanning Inside Your Cloud

All of this processing happens inside your cloud environment, using Sentra’s agentless, in‑cloud scanners rather than shipping PDFs out to a third‑party service. Our parser framework is designed around streaming and format‑aware readers, which means:

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• Files are processed as streams, not as long‑lived replicas.
• PDF contents are analyzed in memory by the scanner, avoiding new long‑term copies in external systems.
• The same engine powers analysis across databases, object storage, file systems, and SaaS sources.

The net effect is that Sentra reduces your blind spots around PDFs without turning the security solution itself into a new source of data exposure.

Regulatory Reality – PDFs Are Always in Scope

From a regulatory standpoint, PDFs are undeniably in scope. Frameworks and regulations such as:

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• GDPR for data subject rights, record‑keeping, and deletion
• HIPAA for PHI in healthcare organizations
• PCI DSS for cardholder data stored in receipts, statements, and chargeback files
• SOX and other financial reporting controls

do not distinguish between data in databases and data in documents. A stack of PDFs in cloud storage, email archives, or shared drives counts just as much as a customer table in a production database when regulators and auditors review your posture. If your data security strategy covers only structured data and a narrow slice of text documents, you are leaving a disproportionate share of your most sensitive content unprotected.

Bringing PDFs into Your DSPM Strategy

PDFs are not going away. Digital‑first operations guarantee we will see more of them every year, not fewer. That makes them a natural priority for any serious Data Security Posture Management (DSPM) program.

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Sentra’s PDF scanning is designed to make PDFs a first‑class citizen in your data security strategy:

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• Native text and scanned PDFs both receive full, ML‑powered inspection.
• Tables and forms are treated as structured data for higher‑fidelity classification.
• Metadata and unreadable encrypted PDFs are surfaced instead of ignored.
• Everything runs inside your cloud, alongside support for 100+ other file formats.

You can explore how we extend the same approach across the rest of your data estate, or see it in action by requesting a demo.

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