The number of the cyber-attacks has increased recently especially in the last few years since the Covid-19 various struck the whole world and these attacks are usually for demanding a ransom. This project aims to contribute overcoming this dilemma by building a deep learning model for ransomware detection. This project uses the convolutional neural network (CNN) as well as static analysis based on the literature review. The built model is evaluated using accuracy criteria, it has achieved a good result with 91% accuracy in addition, the model gives a multi-class analysis for the ransomware families. For literature review, we recommend using different datasets, also compare a different architectures of CNN would help building more ac- curate model..