collaborators

5 papers

cs.CR2026

Fingerprinting Inference Systems of Large Language Models

Anna Wimbauer, Jonas Möller, Erik Imgrund +1

The behavior of LLMs does not depend solely on the model itself. Components of the inference system, such as the inference engine, attention backend, and hardware platform, subtly…

cs.LG2026

Hardware-Triggered Backdoors

Jonas Möller, Erik Imgrund, Thorsten Eisenhofer +1

Machine learning models are routinely deployed on a wide range of computing hardware. Although such hardware is typically expected to produce identical results, differences in its…

cs.CR2025

LLM-based Vulnerability Discovery through the Lens of Code Metrics

Felix Weissberg, Lukas Pirch, Erik Imgrund +3

Large language models (LLMs) excel in many tasks of software engineering, yet progress in leveraging them for vulnerability discovery has stalled in recent years. To understand thi…

cs.CR2025

Dancer in the Dark: Synthesizing and Evaluating Polyglots for Blind Cross-Site Scripting

Robin Kirchner, Jonas Möller, Marius Musch +3

Cross-Site Scripting (XSS) is a prevalent and well known security problem in web applications. Numerous methods to automatically analyze and detect these vulnerabilities exist. How…

cs.SE2025

SoK: Where to Fuzz? Assessing Target Selection Methods in Directed Fuzzing

Felix Weissberg, Jonas Möller, Tom Ganz +6

A common paradigm for improving fuzzing performance is to focus on selected regions of a program rather than its entirety. While previous work has largely explored how these locati…