The rapid growth of online job portals and digital recruitment platforms, job scams have become increasingly prevalent, leading to financial loss and data theft among job seekers. This project, Job Shield proposes a machine learning-based system to detect fraudulent job postings. The system analyses job descriptions, recruiter details, and behavioural patterns to classify listings as legitimate or fraudulent.

The proposed model utilizes Natural Language Processing (NLP) techniques along with supervised machine learning algorithms such as Logistic Regression, Random Forest, and Support Vector Machines. By training on labelled datasets of real and fake job postings, the system learns patterns indicative of scams. The application provides real-time detection and alerts users, thereby enhancing