The field of image forensics employs a range of techniques to confirm the integrity of images. Specific approaches are used to address particular problems. In this paper, our focus is on detecting copy-move forgery by using deep learning. To determine whether an image has been tampered with, we utilize a customized CNN model architecture and train it with images after performing error-level analysis on them within the images. Additionally, we use traditional method like feature extraction like the SIFT detector which extracts key-points invariant to any changes and by using DBSCAN algorithm we pinpoint areas of copy-move forgery.