When does boosting overfit more than bagging?
I read your question as: 'Is boosting more vulnerable to overfitting than bagging?'

Firstly, you need to understand that bagging decreases variance, while boosting decreases bias. 

Also, to be noted that under-fitting means that the model has low variance and high bias and vice versa for overfitting.

So, boosting is more vulnerable to overfitting than bagging.