Exaggeration-based Fake Cybersecurity News Detection

We address the challenge of detecting exaggeration in cybersecurity tweets on X, where misinformation spreads rapidly. Our novel framework uses local Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) to gather evidence and assess tweets' rhetorical intensity, offering graded exaggeration scores. Validated through a human study and a pilot that matches LLM results with human labels, this work lays the groundwork for improved misinformation detection tools.