Stepwise Model Selection in Logistic Regression in R - Cross Validated

Logistic regression in r studio. I'm implementing a logistic regression model in R and I have 80 variables to chose from. I need to automatize the process of variable selection of the model so I'm using the step function. I've no problem using the function or finding the model, but when I look at the final model I find that some of the variables chosen by the step function are not significant (I look at this using the summary function and looking at the fourth column in $coef, this is the Wald Test). This is a problem because I need all the variables included in the model to be significant. Is there any function or any way to get the best model based on AIC or BIC methods but that also consider that all the coefficients must be significant? Thanks.