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Control evaluation · Practical playbook

Evaluate text PDFs and scanned PDFs separately

PDF is a container, not a guarantee of readable text. A selectable document, an image-only scan and a mixed PDF can expose different inspection paths. Evaluate each required form without assuming OCR is present or equally effective.

For Document security owners and technical evaluators

Synthetic example

Three versions of a fictional service report

A facilities team wants an AI summary of a synthetic service report. The same fictional identifiers appear in a text export, a scanned copy and a PDF containing both forms.

What you are working with

  • A text-based PDF with selectable synthetic identifiers in paragraphs, tables and page headers.
  • A scanned counterpart containing only fictional values, with its image quality recorded in the test plan.
  • A mixed PDF with a text page, an image page and a documented expected-removal checklist.

A safer approach

  • Confirm text extraction and any OCR scope with the vendor before choosing the acceptance boundary.
  • Use synthetic scans and mark poor-quality variants as separate tests instead of silently changing the fixture.
  • Inspect the final file's visible content and available text layer; do not accept a colored overlay as sufficient proof.

Expected outcome: Each PDF class has a supported result or an explicit restriction, and any sanitized output satisfies both confidentiality and readability requirements.

Put it into practice

Work through the procedure

  1. Classify the source PDF

    Check whether representative text can be selected and searched, then inspect which pages are scans. Record mixed content and other agreed features such as annotations. A filename ending in PDF is not enough information to choose a reliable test or infer extraction coverage.

  2. Run comparable document variants

    Process each version through the same agreed provider path and policy. Record whether the system accepts, rejects, flags or modifies it. If OCR is outside the supported workflow, evaluate the required user restriction rather than expecting a scanned fixture to be recognized.

  3. Check removal beyond appearance

    Inspect sanitized outputs where available using a PDF viewer and an approved text-extraction method. Search for the synthetic protected values and review the affected pages. If these inspection methods disagree, stop the conclusion and investigate the output representation with engineering.

  4. Review degraded and mixed cases

    Add a controlled lower-quality scan only if it reflects a genuine requirement. Check the mixed PDF page by page and inspect allowed content for readability. Record failure handling separately from detection quality so an honest rejection is not mistaken for a missed scan.

Evidence before approval

What to check before proceeding

1. PDF structure coverage

Ready when
Text, scanned and mixed variants each have a documented result matching the agreed scope.
If the check fails
Restrict the unsupported class or add a separate approved preparation workflow.

2. Recoverable content

Ready when
Agreed protected fixtures are absent from the inspected visible and extractable output content.
If the check fails
Do not share the output; investigate incomplete removal or an insufficient verification method.

3. Readable retained content

Ready when
Permitted sections remain legible and preserve the relationships needed for the summary.
If the check fails
Revise the fixture preparation or choose a more suitable document source.

Common mistakes to avoid

  • Assuming the ability to redact a text PDF establishes OCR coverage for every scanned page.
  • Checking that a name is visually obscured without testing whether it remains selectable or searchable.
Workforce AI Security

Evaluate this workflow with Aona

Where Aona can help

Bring synthetic text and scanned examples to Aona and agree the currently supported PDF inspection and redaction behavior.

What to confirm

Do not infer OCR, annotation, attachment or image-layer coverage from a generic PDF-support statement; validate the required components.

Evaluating a control for your organization?

Bring your target AI tool, device and acceptance criteria. Review the supported control path, the evidence you need and any limitations before deciding on a pilot.

FAQ

Questions about this workflow

No. It checks one representation. A scan may contain visible sensitive text without selectable characters, while a mixed document can contain both. Review every relevant representation.
Technical evaluation

Evaluating a control for your organization?

Bring your target AI tool, device and acceptance criteria. Review the supported control path, the evidence you need and any limitations before deciding on a pilot.

Verify PDF Redaction for Text and Scans | Aona AI