arXiv:2608. 05715v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as planners in robotic systems, where they translate natural-language commands into executable actions grounded in visual scene understanding.
By S. M . Bhagya P. Samarakoon, M. A. Viraj J. Muthugala, W. K. R. Sachinthana, Mohan Rajesh Elara
arXiv:2609.22949v1 Announce Type: cross
Abstract: Existing prompt injection research focuses on single-model chatbot scenarios, where an attacker manipulates one LLM through crafted input. Multi-agen...
By Rudrendu Kumar Paul, Sourav Nandy
arXiv:2504. 17070v3 Announce Type: replace-cross Abstract: Robots need task planning methods to achieve goals that require more than one action.
By Mohaiminul Al Nahian, Zainab Altaweel, David Reitano, Sabbir Ahmed, Shiqi Zhang, Adnan Siraj Rakin
The paper proposes universal, tool‑based defenses for large language model agents that use external tools, addressing four types of adversarial attacks: direct and indirect prompt injection, memory poisoning, and backdoor attacks. Two main defenses are introduced: Attacker Tool Filtering, which uses anomaly detection to remove suspicious tools, and Normal Tool Recalling, which restores the agent’s original toolset before planning. The authors also add prompt‑based defenses such as Chain‑of‑Thought prompting and self‑reflection, and demonstrate that these methods dramatically lower attack success rates—often to 0%—across multiple open‑source and proprietary LLMs while maintaining or improving task performance.
By Xiaoyan Li, Yunli Wang
The paper introduces covert indirect prompt injection (IPI) attacks on tool‑using large language model agents, distinguishing between covert and overt successes. It defines new metrics—Covert Success Rate (CSR) and Overt Success Rate (OSR)—to capture whether users notice the injection. The authors propose ICoA, an attack that steers agents back to the user’s task after executing the injection, achieving higher CSR than existing methods on four target models.
By Yunseok Lee, Yunji Kim, Woojin Lee
arXiv:2608.30362v1 Announce Type: new
Abstract: As LLM agents take real-world actions through tools, indirect prompt injection (IPI) has emerged as a serious threat. The standard metric, Attack Succe...
By Yunseok Lee, Yunji Kim, Woojin Lee