The purpose of developing social networking platforms such as Facebook, Twitter, and LinkedIn, as well as other web-based apps, is to make individual users more productive. This goal is also driving the development of additional web-based applications. There is a large opportunity for unauthorized access to sensitive user data, as well as the likelihood that this data will be released, if customers are not aware of the security hazards they face. In addition, there is the possibility that this data may be disclosed. This research aims to develop ways for mitigating a wide variety of security issues in order to protect the information that is gathered via the utilization of social media platforms. The research's primary objective is to achieve this objective. We keep an eye out for and make an effort to fight against things like SQL injection, distributed denial of service attacks (DDoS), cross-browser attacks (XSS), phishing efforts, cross-browser request forgery (CSRF), clickjacking, and inference attacks. The objective of this research is to construct a probability model that may be utilized to depict the actions of a user when that person is participating in a social network and making reference to other users. In addition, we provide a way for anticipating the emergence of a new topic by examining the anomalies that are discovered by this model. This method can be found in the following paragraph. The methodology being described here is known as the anomaly detection method. We are able to demonstrate our capacity to discover issues that were not previously known about by comparing the ratings of a considerable number of users to the patterns of answers and references found in postings made on social networking sites. We use a range of real-world data sets that we obtained from the social networking website Twitter in order to demonstrate how effective our methodology is. These data sets come from Twitter because we obtained them there. The recommended mention-anomaly-based access strategy has the potential to find fresh themes at least as early, and in some cases much sooner, as strategies that are based on text anomalies can. This is the case regardless of whether or not the text content of the postings provides an explicit definition of the issue