Topological approach detects adversarial attacks in multimodal AI systems

New vulnerabilities have emerged with the rapid advancement and adoption of multimodal foundational AI models, significantly expanding the potential for cybersecurity attacks. Researchers at Los Alamos National Laboratory have put forward a novel framework that identifies adversarial threats to foundation models—artificial intelligence approaches that seamlessly integrate and process text and image data. This work empowers system developers and security experts to better understand model vulnerabilities and reinforce resilience against ever more sophisticated attacks.