This dataset addresses the lack of public botnet datasets, particularly for the Internet of Things. It suggests real-world traffic statistics collected from 9 commercial IoT devices infected with Mirai and BASHLITE. Since the dataset consists of CSV files, in pre-processing stage, first - different types of csv files read. after that, we divided the csv file into 10 attacks carried by 2 botnets. Next step, shuffle the whole dataset and distinguish outputs from inputs. Normalization and one-hot encoding have been applied to label multiple classes. After finishing the preprocessing, ML classifiers used for multi-class classification. As a matter of fact, The dataset can be used for multi-class classification : 10 classes of attacks plus one class of benign. Number of Instances of the dataset is 7062606, while the "Real number of attributes" are 115.