Automatically Dismantling Online Dating Fraud is positioned as a study of deceptive activity on dating platforms and a proposal for an automated approach to counter it. The article defines common fraud scenarios such as impersonation, romance scams, and fake profiles, and frames them within an information-forensics context that emphasizes detection, disruption, and deterrence. The work outlines an automated framework intended to identify indicators across profile creation, messaging behavior, account lifecycles, and cross-platform signals, with an emphasis on scalability and repeatability. It situates the problem within a broader security discipline and presents a structured discussion of system components, data needs, and deployment considerations, without presuming specific implementation details. The synopsis treats the contribution as methodological rather than empirical, focusing on architecture, goals, and potential impact. The piece surveys or proposes methods for automatic dismantling of fraud, including signal aggregation, pattern recognition of suspicious interactions, and automated enforcement actions such as quarantine, alerting, or removal of suspect profiles. The narrative notes trade-offs between detection effectiveness and user privacy, and