my k-fold validation is giving a lot of 100% in the concatenated confusion matrix, is it because of overfitting?

The confusion matrix is a concatenated one from a 5-fold stratified cross-validation of my data set. I used rbf kernel for the svm classifier. Is it telling me the classifier is overfitting? Plus when I plot the confusion matrix from the training datasets ( 70% training 30% testing ), it is giving pretty much the same confusion matrix as the cross-validation one. The unseen testing datasets is also giving pretty much the same confusion matrix. should I worry about overfitting?