Fake Certificate Detection API
Detect fake diplomas, forged professional credentials, and altered certificates of completion. One API call surfaces forensic evidence of PDF modification — before a candidate is hired.
HTPBE? analyzes the structural layer of the PDF file — the layer that records every edit, even invisible ones. We don’t inspect holograms, embossed seals, or physical paper. If your fraud problem is a digitally fabricated or tampered certificate, diploma, or transcript PDF, we’re the most specific tool for it.
When HTPBE? returns INCONCLUSIVE on a certificate or diploma, that’s itself a high-confidence fraud signal — real credentials come from registrar systems or accredited fraud-detection platforms (National Student Clearinghouse, Parchment, Digitary), never from a desktop tool. Combine with education-fraud-detection services where available; HTPBE? works on the file layer regardless.
The problem
Credential fraud is an unsolved problem in hiring
Research from the University of Portsmouth estimates that recruitment fraud costs UK employers £24 billion annually. In the United States, studies indicate that roughly 40% of resumes contain some form of misrepresentation, and fake credentials are the fastest-growing category.
The core problem is that PDF certificates look authentic when fraudulently modified. Free tools like iLovePDF, SmallPDF, and Adobe Acrobat can change any text in a PDF in under two minutes. The resulting file is visually indistinguishable from the original — but the binary structure tells a different story.
HTPBE? does not compare against a database. It analyzes the PDF’s own internal structure for signs of post-issuance modification, which means it works even for certificates from obscure or international institutions where no database record exists.
Most common certificate modifications
- Name field changed to the applicant’s name
- Graduation year changed from fail to pass
- Grade or GPA altered
- Issuing institution name changed
- Certificate date changed to appear more recent
- Real certificate of a different person reused
What this looks like
Document fraud in 2026 — three concrete patterns
Three real fraud mechanics we catch at the structural PDF layer.
Name field changed to the applicant’s name
Graduation year changed from fail to pass
Grade or GPA altered
Issuing institution name changed
Certificate date changed to appear more recent
Real certificate of a different person reused
The detection gap
KYC platforms check the document. HTPBE? checks the file.
Two different checks — both matter.
KYC & identity platforms
Plaid · Persona · Alloy · Jumio
- Is this a real bank statement template?
- Does the account number match the identity?
- Is the document format consistent with the issuing bank?
Detects fake documents. Does not detect edited real documents.
HTPBE? tamper detection API
Structural PDF integrity
- Was this specific PDF file modified after it was generated?
- Do metadata timestamps match the file structure?
- Were digital signatures valid at the time of signing?
What HTPBE? checks
Forensic signals analyzed in every certificate
No original document required — analysis is fully self-contained
Institutional producer check
Legitimate certificates from universities and professional bodies are generated by institutional document systems. A producer field showing “iLovePDF” or “PDF24” means the certificate was processed by an editing tool after issuance.
Incremental update detection
When a text field in a PDF is edited, the change is appended as an incremental update rather than rewriting the file. HTPBE? counts update chain length — genuine certificates have none.
Multiple xref tables
Each editing session adds a new cross-reference table to the PDF. A certificate with multiple xref tables was almost certainly modified after it was originally generated.
Modification date analysis
A certificate’s ModDate should equal its CreationDate if unmodified. A gap of months or years between creation and modification is a primary forgery signal.
Digital signature validation
Accredited institutions often digitally sign certificates. If a signature exists and content was modified after signing, HTPBE? returns “modified” with “certain” confidence.
Font and object consistency
Text substitutions in PDF certificates often introduce font subsets that were not part of the original document. HTPBE?’s content analysis layer detects inconsistent object origins.
Share with engineering
Wire this into your intake pipeline in under a day
Two API calls — one POST to submit the PDF, one GET to retrieve the verdict. Forward this page to your engineering team; the full API reference, quotas, and copy-paste examples in cURL, JavaScript, Python, PHP, Go, and Ruby are one click away.
Pricing
Self-serve plans, no sales call
All plans include the same forensic checks. Pick the quota that matches your monthly document volume.
manualStarter
$15/mo
30 checks/mo
Manual spot-checks and integration testing
most commonGrowth
$149/mo
350 checks/mo
Active document processing pipelines
high volumePro
$499/mo
1,500 checks/mo
High-volume automation and API integrations
Enterprise (unlimited, on-premise available) — see full pricing
API key on signup. Free test environment on every plan. No card required.
Customer Stories
Teams that stopped document fraud
Compliance, finance, and risk teams use HTPBE? to catch manipulated PDFs before they become costly mistakes.
Caught an invoice where the total had been changed by less than a thousand dollars. Without this I would have approved it without a second look.
Sarah M.
AP Manager
United States
We had three applicants in the same week with bank statements that looked completely fine. Two of them were flagged as modified. You simply cannot see this by reading the document — it is in the file structure.
Lars V.
Risk Analyst, Online Lending
Netherlands
Salary slips were coming with altered figures. We identified two problematic files before the placement was finalised.
Priya K.
HR Operations Lead
India
Since we started checking documents this way, we stopped two applications early in the process that would have been very difficult to reverse later.
Julien R.
Fraud Analyst, Fintech
France
Some applicants were sending PDFs that looked authentic but had been edited in ways not visible to the eye. We now ask for checked originals when something is flagged. Already saved us from a few bad decisions.
Marta S.
Compliance Coordinator
Spain
One invoice was caught because there was a mismatch between the document dates and structure. That particular case would have cost us significantly.
Tariq A.
Finance Manager
United Arab Emirates
FAQ
Frequently asked questions
How does it detect a fake diploma without the original?
Does it work for certificates from any country?
What does "inconclusive" mean for a certificate?
inconclusive means the certificate was created with consumer software: Microsoft Word, Google Docs, or a desktop PDF printer. These tools do not embed institutional metadata, so the file cannot be analyzed for tampering. For certificates, this verdict is particularly significant — legitimate university diplomas and professional accreditations are not generated by Word. Treat inconclusive as a prompt for manual review.Can it detect AI-generated fake certificates?
inconclusive because it was never "modified" — it was fabricated as a new file. However, the producer and creator fields in the response will reveal the generation tool, which is a risk signal for certificates that should come from institutional systems. Many AI-generated fakes are also subsequently edited, which adds detectable structural markers.Secure your workflow
Create your account — API key on signup, free test environment on every plan.
From $15/mo. No sales call. Cancel any time.