The Automated Android Malware Detection introduces a technique to identify the malware in Android in the domain of cybersecurity. As it is the world’s mostly used operating system, it has come out with the attention of the cyber criminals with the help of wide dispersion of the malicious applications. Nowadays Android has became a target of malware. Even after providing the security mechanisms, the news over the malicious applications and activities points to the significance of the development of frameworks and methods to improve its security. In this project, we are proposing an effective approach for Android based on machine learning. The cyber threats are analyzed using two techniques, static and dynamic. Static Analysis: This type of analysis includes methods which helps to get the details regarding the software which we are supposed to examine without even executing. One of the best examples is studying the code lines, resources and their function callings etc. Dynamic analysis: This is a second approach where the main objective is to identify threat during the execution. In other words, by knowing about its functioning, getting its information and also by knowing some of the features of the net flows.