Emerging Threats in Artificial Intelligence

This technical report discusses the evolving risks associated with Artificial Intelligence (AI) in the context of cybersecurity. It outlines various threats posed by AI technologies, particularly focusing on Large Language Models (LLMs) and Generative AI (GenAI). The report details specific risks such as AI poisoning, where malicious actors may inject false data into AI systems, and model inversion attacks, which can lead to identity theft and intellectual property theft. Furthermore, it presents mitigation strategies including data validation, adversarial training, and the implementation of frameworks like the Adversarial Threat Landscape for Artificial-Intelligence Systems (ATLAS). The document emphasizes the importance of understanding these threats and the need for robust cybersecurity measures to protect organizations from potential financial harm and reputational damage. By addressing these emerging threats, organizations can better prepare for the challenges posed by the integration of AI technologies in their operations.