An AI Agent and Large Language Model-Based Approach to Open Source Intelligence Analysis

Open Source Intelligence (OSINT) faces increasing challenges due to the massive scale, diversity, and veracity of publicly available information. In this paper, we propose a systematic methodology integrating AI agents and large language models (LLMs) to enhance OSINT analysis. Our approach specifies the architecture, workflow, mathematical modeling, and evaluation framework, providing a comprehensive and scalable solution. Experimental results demonstrate the superior performance of the proposed system compared to traditional OSINT methods.