2 citations · 5 across the 16 of their papers we have counts for
7 papers · 1 filter
Breaking and Fixing Defenses Against Control-Flow Hijacking in Multi-Agent Systems
Rishi Jha, Harold Triedman, Justin Wagle +1
Control-flow hijacking attacks manipulate orchestration mechanisms in multi-agent systems into performing unsafe actions that compromise the system and exfiltrate sensitive informa…
MillStone: How Open-Minded Are LLMs?
Harold Triedman, Vitaly Shmatikov
Large language models equipped with Web search, information retrieval tools, and other agentic capabilities are beginning to supplant traditional search engines. As users start to…
Approximating Language Model Training Data from Weights
John X. Morris, Junjie Oscar Yin, Woojeong Kim +2
Modern language models often have open weights but closed training data. We formalize the problem of data approximation from model weights and propose several baselines and metrics…
Harnessing the Universal Geometry of Embeddings
Rishi Jha, Collin Zhang, Vitaly Shmatikov +1
We introduce the first method for translating text embeddings from one vector space to another without any paired data, encoders, or predefined sets of matches. Our unsupervised ap…
Universal Zero-shot Embedding Inversion
Collin Zhang, John X. Morris, Vitaly Shmatikov
Embedding inversion, i.e., reconstructing text given its embedding and black-box access to the embedding encoder, is a fundamental problem in both NLP and security. From the NLP pe…
Multi-Agent Systems Execute Arbitrary Malicious Code
Harold Triedman, Rishi Jha, Vitaly Shmatikov
Multi-agent systems coordinate LLM-based agents to perform tasks on users' behalf. In real-world applications, multi-agent systems will inevitably interact with untrusted inputs, s…
Rerouting LLM Routers
Avital Shafran, Roei Schuster, Thomas Ristenpart +1
LLM routers aim to balance quality and cost of generation by classifying queries and routing them to a cheaper or more expensive LLM depending on their complexity. Routers represen…