Emerging technologies are making our life easier through digital! But as the coin had both sides, the same technology is being misused by the hackers on the so-called dark side of the internet making 24/7 several attempts to disguise us with aim of easy earning the lump sums. Today no work is possible without the internet, thus the major victims reported are also the ones who frequently be online. There is a huge need for cybersecurity to survive in this world. This triggered our interest to apply Machine Learning in this field to contribute our part in rescuing the people before the trap. We had designed a web-app that has an interface with two buttons - BotNet and Phishing. When we click on BotNet, an interface opens related to Twitterbot detection with user inputs. Whereas the phishing opens to an interface with a text box that asks the user to paste the URL. While working over the internet, if the user finds any pop-up emails with URLs to click kind of things or any suspicious accounts over social media like Twitter, he/she should always look for the second opinion before clicking on URL or accepting that particular account. Take a bit time and cross-check with our website which detects the particular cybercrime (Phishing URL/not, Twitterbot/not), even displays the probability respectively. The website designed by us predicts results with running trained models of Random Forest(for phishing-98%) and Decision Tree Classifier(for botnet-99%) over flask application. Hence, it could provide service to users.