How to predict a continuous variable without any output data ? All i have is Input data
I may be misunderstanding but it appears that you don't have the necessary information to make the prediction.
My understanding is that you have category information but no other associations. For some categories you might be able to hard code your prediction based on expert opinion. Predicting a ping sweep is basically benign, for example, just by knowing what it's called. For anything more dynamic you're going to need more information than you listed.
I am working on a cyber security project wherein we have to prioritize vulnerabilities based on the existing features which are mostly categorical variables (also including couple of ordinal variables). 
The objective here is to detect vulnerability that is most likely to be exploited, and thereby prioritizing it. Hence we have to predict a score of 0-10 . Whichever is the highest rating that we predict (in this case 10), will be the most critical vulnerability that needs immediate attention.
All that we have are the categorical variables (as input features).
Once again summarizing the problem here :
Current Input features : All categorical variables (with couple of ordinal variables)
Current Output feature : DOES NOT EXIST
Expected Output : Predict a score in the range 0-10, with 10 being most critical vulnerability 
Never came across this kind of problem. It definitely looks like Regression is not the answer. Can you please share your thoughts on the same.