What does all zero mean decrease in accuracy (MDA/permutation importance) signify?
I am assuming MDA means Mean Decrease Accuracy. Generally speaking, a good performance on a validation/testing dataset means that your model generalizes well.
On the other hand MDAs of all exactly zero means either the model always needs just one variable to get its best performance no matter what variable that is (very unlikely), or that you plain simply calculated the MDAs wrong. This is impossible to tell without code/examples/etc.