Detecting whether a document — an ID card, a certificate — has been digitally altered is a genuinely hard vision problem, and it's worth being honest about what's checkable today versus what requires more sophisticated forensics than a straightforward pipeline provides.
What's checkable with a reasonable pipeline
- Font and layout consistency against a known template for that document type — misaligned text or an inconsistent font is a common tell.
- Compression artifacts around a suspected edit region, which basic error-level analysis can sometimes surface.
- Metadata inconsistencies (creation date, editing software) when the original file, not just a photo of it, is available.
What's genuinely hard
A well-executed edit on a photographed (not digital) document, using competent editing tools, can defeat most straightforward checks. Be honest with users and stakeholders about this limitation rather than implying a pipeline catches all tampering.
See document AI for invoices: an extraction schema.
About Pranjul Rathour

Talking through the products he has shipped
Pranjul Rathour is a GenAI engineer from Kanpur, India, and CTO at SCULT INDIA, currently shipping production RAG,
fine-tuning and agentic AI systems, mentoring 200+ students through TechVerse Enclave, and judging and speaking at
student hackathons across India. Updated 2026-09-11.
Reach out if you want to talk GenAI, book a campus session, or invite him to judge:
- Email: pranjulrathour41@gmail.com
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- GitHub: https://github.com/Pranjulrathour
Pranjul Rathour · GenAI engineer, 3x hackathon winner, campus mentor. Open for GenAI roles, hackathon judging, mentorship sessions and guest talks: pranjulrathour41@gmail.com · Invite me to your campus
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