7 citations · 8 across the 15 of their papers we have counts for
6 papers · 1 filter
Beyond Predictable Paths: Redefining AI Security Incident Reporting for Agents
Anastasia Pustozerova, Eugene Bagdasarian, Luca Beurer-Kellner +22
AI agents are being deployed rapidly, accompanied by a growing number of AI-specific attacks and corresponding incidents. As incident reporting becomes increasingly important for l…
AI Agents May Always Fall for Prompt Injections
Sahar Abdelnabi, Eugene Bagdasarian
Prompt injection is the most critical vulnerability in deployed AI agents. Despite recent progress, we show that the prevailing defense paradigm (data-instruction separation) both…
Contrastive Privacy: A Semantic Approach to Measuring Privacy of AI-based Sanitization
George Bissias, Eugene Bagdasarian, Brian Neil Levine
AI-based sanitization can remove concepts from images and text, but privacy evaluation remains largely ad hoc. We propose contrastive privacy, a formal definition that yields a qua…
Disappearing Ink: Obfuscation Breaks N-gram Code Watermarks in Theory and Practice
Gehao Zhang, Mingzhe Li, Eugene Bagdasarian +2
Large language models (LLMs) are increasingly used for code generation, making reliable identification of machine-generated code important for attribution, tracking, and misuse det…
Contextual Agent Security: A Policy for Every Purpose
Lillian Tsai, Eugene Bagdasarian
Judging an action's safety requires knowledge of the context in which the action takes place. To human agents who act in various contexts, this may seem obvious: performing an acti…
Self-interpreting Adversarial Images
Tingwei Zhang, Collin Zhang, John X. Morris +2
We introduce a new type of indirect, cross-modal injection attacks against visual language models that enable creation of self-interpreting images. These images contain hidden "met…