FbI is a plug-in for Facebook which analyses and identifies malicious posts in real time. The plug-in loads whenever a user opens her Facebook page, and extracts the post IDs of all public posts in the user's news-feed. The post IDs are then sent to our backend API. Our API fetches the post and user / page profile information and generates a feature vector, which is subjected to the two supervised learning models pre-trained on the two datasets. We use class probabilities to predict the class for the post instead of obtaining a class label directly. This is done to provide flexibility to applications which use our API directly, and enabling them to choose their own thresholds (depending on the use case) while making a decision on whether a post is malicious or not, according to the prediction probability values. In addition to a class label, we associate a confidence level (High / Low) with the assigned label.