Automated Target Profiling: Leveraging Artificial Intelligence for Open-Source Intelligence Collection

The emergence of Artificial Intelligence (AI) and the growing complexity of cyber threats have created new prospects for automating cybersecurity functions. A pivotal domain that gains from this innovation is Open-Source Intelligence (OSINT), an essential element of threat intelligence. This paper details the design and execution of an AI-driven solution that automates the creation of extensive target profiles through the integration of social media data collecting and large language model (LLM) processing. The application uses RapidAPI to consolidate publicly accessible information from social media platforms, including Facebook, Twitter, and LinkedIn, and applies OpenAI’s GPT-4o model to transform that data into organized intelligence reports. The system also integrates computer vision models, YOLOv8 and DeepFace, for facial recognition and verification. The platform, hosted on a secure AWS cloud instance, provides a scalable and interactive online interface for users to enter data and obtain downloadable reports. This research illustrates how the integration of AI with OSINT procedures can improve the efficiency, depth, and accessibility of operational threat intelligence collection, while also identifying existing deficiencies in AI incorporation within the cybersecurity domain.