6 papers
When Prompts Control Robots: Prompt Injection Attacks in Multi-Agent Robotic Systems
Neha Nagaraja, Amisha Bagari, Hayretdin Bahsi
Large language models are increasingly integrated into autonomous robotic systems for task planning and control, but this integration exposes them to prompt injection attacks that…
From Prompt to Physical Actuation: Holistic Threat Modeling of LLM-Enabled Robotic Systems
Neha Nagaraja, Hayretdin Bahsi, Carlo R. da Cunha
As large language models are integrated into autonomous robotic systems for task planning and control, compromised inputs or unsafe model outputs can propagate through the planning…
Where Do LLM-based Systems Break? A System-Level Security Framework for Risk Assessment and Treatment
Neha Nagaraja, Hayretdin Bahsi
Large Language Models (LLMs) are increasingly integrated into safety-critical workflows, yet existing security analyses remain fragmented and often isolate model behavior from the…
Image-based Prompt Injection: Hijacking Multimodal LLMs through Visually Embedded Adversarial Instructions
Neha Nagaraja, Lan Zhang, Zhilong Wang +2
Multimodal Large Language Models (MLLMs) integrate vision and text to power applications, but this integration introduces new vulnerabilities. We study Image-based Prompt Injection…
Goal-Driven Risk Assessment for LLM-Powered Systems: A Healthcare Case Study
Neha Nagaraja, Hayretdin Bahsi
While incorporating LLMs into systems offers significant benefits in critical application areas such as healthcare, new security challenges emerge due to the potential cyber kill c…
To Protect the LLM Agent Against the Prompt Injection Attack with Polymorphic Prompt
Zhilong Wang, Neha Nagaraja, Lan Zhang +3
LLM agents are widely used as agents for customer support, content generation, and code assistance. However, they are vulnerable to prompt injection attacks, where adversarial inpu…