3 papers
cs.CR2025
Super Suffixes: Bypassing Text Generation Alignment and Guard Models Simultaneously
Andrew Adiletta, Kathryn Adiletta, Kemal Derya +1
The rapid deployment of Large Language Models (LLMs) has created an urgent need for enhanced security and privacy measures in Machine Learning (ML). LLMs are increasingly being use…
cs.CR2025
Rubber Mallet: A Study of High Frequency Localized Bit Flips and Their Impact on Security
Andrew Adiletta, Zane Weissman, Fatemeh Khojasteh Dana +2
The increasing density of modern DRAM has heightened its vulnerability to Rowhammer attacks, which induce bit flips by repeatedly accessing specific memory rows. This paper present…
cs.CR2025
Spill The Beans: Exploiting CPU Cache Side-Channels to Leak Tokens from Large Language Models
Andrew Adiletta, Berk Sunar
Side-channel attacks on shared hardware resources increasingly threaten confidentiality, especially with the rise of Large Language Models (LLMs). In this work, we introduce Spill…