The last point is a correct method if you’re accepting the theoretical risk that it could run forever. In case of an uniform distribution on the original range the probabilities converge to an uniform distribution on the smaller range. For non-uniform distributions you also get a distribution where the new probabilities are scaled sums of the original probabilities.
In reality you should probably introduce a maximum number of rerolls. In that case you have your issue again but you can easily calculate error estimates to choose a good tradeoff limit for your purposes.
The last point is a correct method if you’re accepting the theoretical risk that it could run forever. In case of an uniform distribution on the original range the probabilities converge to an uniform distribution on the smaller range. For non-uniform distributions you also get a distribution where the new probabilities are scaled sums of the original probabilities.
In reality you should probably introduce a maximum number of rerolls. In that case you have your issue again but you can easily calculate error estimates to choose a good tradeoff limit for your purposes.