How to analyse the results of cross-validation do determine overfitting
In short, k-fold CV is not about over-fitting. Your samples can never be ideally identical, so you can only conclude that your error is mean±std.
If your model training process is iterative, then you can detect overfitting by checking test score over the course of training.
If you're making hyper-parameter search with k-fold CV, perhaps with many steps, then you can eventually find out that holdout score is much worse than avg. test score. That would be an overfitting too.