Four different "document problems" — separate types in the data model?

At Landvex we've been lumping too much under "forged". In practice I keep seeing four different situations:

1. A wholly fabricated document
2. A genuine document that was later altered
3. A genuine document whose content was already false — the issuer wrote something untrue
4. A genuine, unaltered document used in a misleading way

Only the first two are classic forgery. The last two can sail through any vision model and still be exactly what a bank or authority gets wrong.

So… do you model these as first-class problem types from day one? Or start with visual/file integrity and bolt the rest on later?

Also: for 3 and 4, the system can't really decide from the file alone. You need external checks, case context, sometimes a human. How do you keep the API honest about that, instead of pretending a model "scored" something it never saw?

Curious whether this taxonomy matches what others use, or if we're over-splitting.