UniGuard: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Models

Mar 3, 2025·
Sejoon Oh
Yiqiao Jin
Yiqiao Jin
,
Megha Sharma
,
Donghyun Kim
,
Gaurav Verma
,
Eric Ma
,
Srijan Kumar
· 1 min read
Abstract
Multimodal LLMs are vulnerable to jailbreak attacks that exploit cross-modal interactions. We introduce UniGuard, a universal safety guardrail framework that defends multimodal LLMs against jailbreak attacks across image and text channels, providing strong resistance with low utility cost.
Type
Publication
AAAI 2025 Workshop on Deployable AI (DAI)

Abstract

Multimodal LLMs are vulnerable to jailbreak attacks that exploit cross-modal interactions. We introduce UniGuard, a universal safety guardrail framework that defends multimodal LLMs against jailbreak attacks across image and text channels.

Yiqiao Jin
Authors
Ph.D. Candidate in Computer Science
My research sits at the intersection of multimodal foundation models, intelligent agents, and spatial/physical intelligence. I build general-purpose models that perceive, reason, learn, and act in interactive virtual and physical environments.