Trapdoor functions that depends only on NP-hard?
The crux of the problem lies in worst to average case reductions. The standard construction of a function which is average case hard is taking a function which is worst case hard and applying all kinds of fancy error correcting codes on its truth table. See Ta-Shma's notes sketching the STV construction. As far as I know, we don't know how to do that for NP (STV starts with a PSPACE hard function).
Even worse, we believe this can't be done for NP. See Bogdanov Trevisan, where it is shown that if an NP complete problem has a worst to average case reduction then the hierarchy collapses. Your problem is not exactly worst to average case reduction, but reducing an NP hard problem to inverting a one way function. However, these are related and Trevisan's paper also rules out such non-adaptive reductions.
More directly related to your question is AGGM, which also rules out adaptive reductions for the case where the size of the inverse image is easy to compute. You might also want to check out this paper. These results are 10-15 years old (STV is around 20), I have no idea if anything stronger was proven since.