Is a 100% model accuracy on out-of-sample data overfitting?
High validation scores like accuracy generally mean that you are not overfitting, however it should lead to caution and may indicate something went wrong. It could also mean that the problem is not too difficult and that your model truly performs well. Two things that could go wrong:


You didn't split the data properly and the validation data also occured in your training data, meaning it does indicate overfitting because you are not measuring generalization anymore
You use some feature engineering to create additional features and you might have introduced some target leakage, where your rows are using information from it's current target, not just from others in your training set