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63 Forensic Checks

How HTPBE? Proves a PDF Was Altered After It Was Issued

63 forensic checks run on every file you submit – catching structural manipulation that visual review and KYC platforms miss. Under 3 seconds per document, no original file required.

Why structural analysis

Visual tools check appearance. HTPBE? checks what the software wrote.

A growing class of document fraud detection tools operates on what a PDF looks like – scanning for pixel-level inconsistencies, lighting artifacts, or unusual noise patterns. For physical documents that have been photographed, this has genuine value. For native digital PDFs – the kind a bank, payroll platform, or accounting system generates directly – it addresses the wrong question.

Sophisticated document fraud does not alter the image of a number. It replaces the underlying data while leaving the visual presentation intact. The resulting document passes every pixel-level check cleanly, because visually nothing changed.

HTPBE? examines the internal revision history, the object structure, the font assembly records, the signature coverage maps – layers that rendering engines never expose to the eye. A document can look exactly right and be structurally compromised. We find the second kind.

This is what it means to verify a PDF is genuine at the file level. Not confirming the facts a document states — proving the file itself was not edited after it was issued. If you need to know whether a PDF was modified — a date moved, a number swapped, a signature stripped — that is the question answered here, from the file’s own structure.

Every check derives from the PDF specification itself — ISO 32000, the open ISO standard that defines how a conforming PDF is built. That is why a verdict is deterministic and explainable, not a probabilistic guess: the same file always yields the same result, traceable to a rule in the spec.

63
Forensic checks per document
131
Structural signals evaluated
< 3 sec
Median analysis time
8
Forensic domains analyzed
No original needed
to compare against

Detection coverage

What the 63 checks cover

Each domain below answers a question a fraud analyst would ask by hand – did the dates contradict each other on a bank statement? was a signature stripped after signing? — automated by 63 forensic checks that flag tampered documents in seconds.

Every document runs all checks independently. Multiple findings can fire simultaneously – each reported separately with its own confidence level. Under the hood, those 63 checks evaluate 131 distinct structural signals – independent conditions we test in the file’s bytes, structure, and metadata.

9

Metadata & Timestamps

2

Digital Signatures

3

Incremental Update History

19

Generator Fingerprinting

8

Document Assembly

13

Content Stream Analysis

5

Image Forensics

4

Structural Integrity

How it works

Three steps, under 3 seconds

1

Send a PDF URL

POST a publicly accessible URL to /api/v1/analyze. No file upload, no size limit for the API. You get back a check ID immediately.

2

8 forensic domains analyzed

All 63 checks run in parallel across metadata, structure, digital signatures, generator fingerprinting, document assembly, content streams, image forensics, and structural integrity.

3

Verdict + named markers

GET /api/v1/result/{id} for a structured verdict — intact, modified, or inconclusive — with every triggered finding named individually and confidence rated.

Example API response

What you get back

A bank statement with a removed digital signature and mismatched timestamps returns this. Each marker is a named, actionable forensic finding – not a score.

GET /api/v1/result/{id}
{
  "id": "9f3a2c1d-8b47-4e6f-a012-3d5e7f890123",
  "status": "modified",
  "modification_confidence": "certain",
  "modification_markers": [
    "HTPBE_SIGNATURE_REMOVED",
    "HTPBE_DATES_DISAGREE"
  ],
  "creator": "Adobe Acrobat Pro DC",
  "has_incremental_updates": true,
  "update_chain_length": 3,
  "xref_count": 4,
  "page_count": 12
}

Full schema and all marker descriptions in the API reference →

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Verdicts

Three possible outcomes

intact

No modification detected

No structural evidence of post-creation changes was found in the file.

Intact confirms the file was not modified. It does not guarantee the content is truthful – a document fabricated from scratch with false data can return intact.

inconclusive

Integrity couldn’t be determined

For some files the check cannot decide either way — it can’t confirm the document is unchanged, and it hasn’t found that it was changed.

For fraud teams: a missing flag here is not a clean result, and inconclusive is not by itself a judgment about the document. Weigh it against the document’s expected source, and for anything that matters, verify it with the issuer directly.

modified

Forensic evidence of tampering

One or more structural markers confirm post-creation modification. Confidence is either certain — reserved for the most unambiguous structural evidence, such as a removed signature or contradicting timestamps — or high for all other markers.

Regression testing

Every release is proved against several thousand forgeries first

Before any change to the algorithm ships, it runs against a regression corpus of several thousand synthetic PDFs built to cover every known method of document forgery — incremental-update edits, overlay patches, spliced page assemblies, template reuse, forged scans, and injected metadata among them.

A change is released only when it holds its verdict across the entire corpus. That is how a new rule can never quietly break an old one, and why the algorithm changelog moves forward without regressions.

Related

API DocumentationPricingFree PDF Metadata ViewerAlgorithm ChangelogService StatusStart Free – 5 Checks

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