In this paper, we propose a deep learning convolutional neural network (CNN-1D) model to detect illegitimate URLs. To evaluate the performance of the model, we carried out few experiments using a benchmarked dataset. We used two evaluation measures: accuracy and the area under the receiver operating characteristic (ROC) curve (AUC). The proposed CNN-1D model was able to achieve good performance for predicting the unseen URLs and detecting illegitimate websites. In the testing phase, the classifier achieved an accuracy rate of 94.31% and an overall performance (AUC) rate of 91.23%.