2 citations · 2 across the 3 of their papers we have counts for
7 papers
CaMeLs Can Use Computers Too: System-level Security for Computer Use Agents
Hanna Foerster, Tom Blanchard, Kristina NikoliÄ +6
AI agents are vulnerable to prompt injection attacks, where malicious content hijacks agent behavior. Among proposed defenses, architectural isolation provides the strongest guaran…
AI Agents Enable Adaptive Computer Worms
Jonas Guan, Tom Blanchard, Hanna Foerster +3
A computer worm is malware that spreads on a network by replicating itself from one machine to another. Traditional worms, like WannaCry, exploited predetermined vulnerabilities, a…
Quantamination: Dynamic Quantization Leaks Your Data Across the Batch
Hanna Foerster, Ilia Shumailov, Cheng Zhang +3
Dynamic quantization emerged as a practical approach to increase the utilization and efficiency of the machine learning serving flow. Unlike static quantization, which applies quan…
Thought-Transfer: Indirect Targeted Poisoning Attacks on Chain-of-Thought Reasoning Models
Harsh Chaudhari, Ethan Rathbun, Hanna Foerster +5
Chain-of-Thought (CoT) reasoning has emerged as a powerful technique for enhancing large language models' capabilities by generating intermediate reasoning steps for complex tasks.…
Reasoning Introduces New Poisoning Attacks Yet Makes Them More Complicated
Hanna Foerster, Ilia Shumailov, Yiren Zhao +4
Early research into data poisoning attacks against Large Language Models (LLMs) demonstrated the ease with which backdoors could be injected. More recent LLMs add step-by-step reas…
Hardware and Software Platform Inference
Cheng Zhang, Hanna Foerster, Robert D. Mullins +2
It is now a common business practice to buy access to large language model (LLM) inference rather than self-host, because of significant upfront hardware infrastructure and energy…