India’s escalating teenage substance abuse crisis, with an estimated five million unrecognized heroin users, underscores the urgent need for effective intervention strategies. Social media platforms have become a breeding ground for illicit drug trafficking, posing a significant challenge to public health agencies and law enforcement. This research explores the potential and limitations of using social media data to identify and disrupt drug trafficking networks. While social media data offers a rich source of information, privacy concerns and the diverse nature of drug dealing practices present significant technical hurdles. This research proposes a novel system that leverages BERT and YOLOv5 to identify drug-related content by analyzing user posts, profiles, and online interactions. Adapting the system for use on other social media platforms and conducting user studies with law enforcement agencies and social media platform moderators will provide valuable feedback for system improvement. This research aims to contribute to the fight against drug trafficking by developing a more effective and efficient system for identifying illicit drug dealers on social media platforms.