127 citations · 308 across the 18 of their papers we have counts for
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cs.CR2024
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition
Edoardo Debenedetti, Javier Rando, Daniel Paleka +18
Large language model systems face important security risks from maliciously crafted messages that aim to overwrite the system's original instructions or leak private data. To study…
cs.CR2024★ 4 cited
Whispers in the Machine: Confidentiality in Agentic Systems
Jonathan Evertz, Merlin Chlosta, Lea Schönherr +1
Large language model (LLM)-based agents combine LLMs with external tools to automate tasks such as scheduling meetings, managing documents, or booking travel. While these integrati…