Thorsten Eisenhofer

ML & Computer Security


About Me


I'm a tenure-track faculty member at CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. Before joining CISPA, I was a postdoctoral researcher in the Machine Learning and Security group at BIFOLD & TU Berlin working with Konrad Rieck. I completed my PhD at Ruhr University Bochum, advised by Thorsten Holz and as part of the Cluster of Excellence CASA. My dissertation was recognized by the faculty for outstanding achievements.

My research focuses on machine learning and computer security. I'm interested in a all kinds of attacks on learning models and defenses to improve their robustness. This often means looking beyond the model itself and examining the entire computational pipeline, including pre-processing, post-processing, and the underlying hardware and software stack. I'm also interested in how learning-based approaches, including modern LLM and agent systems, can support core security tasks such as vulnerability analysis, fuzzing, and malware classification.

Along the way, I interned with the SecLab at UC Santa Barbara, working with Giovanni Vigna and Christopher Kruegel and joining Shellphish at the DEF CON CTF finals in Las Vegas. I have also been a visiting researcher at the Cleverhans Lab at the Vector Institute in Toronto, working with Nicolas Papernot. I hold a B.Sc. in Computer Science from Paderborn University and an M.Sc. in Computer Security from Ruhr University Bochum, where I graduated top of my class.

I'm currently looking for PhD students, postdocs, and research interns in machine learning + security. If you're interested joining my group, please reach out through the CISPA Career Portal and indicate that you'd like to work with me. If you're a student seeking a summer internship, you may want to have a look at our CISPA Summer Research Internship Program.


Publications


2026

Jonathan Evertz, Niklas Risse, Nicolai Neuer, Andreas Müller, Philipp Norman, Gaetano Sapia, Srishti Gupta, David Pape, Soumya Shaw, Devansh Srivastav, Christian Wressnegger, Erwin Quiring, Thorsten Eisenhofer, Daniel Arp, and Lea Schönherr

Chasing Shadows: Pitfalls in LLM Security Research

Network and Distributed System Security Symposium (NDSS) (to appear)

Felix Weissberg, Lukas Pirch, Erik Imgrund, Jonas Möller, Thorsten Eisenhofer, and Konrad Rieck

LLM-based Vulnerability Discovery through the Lens of Code Metrics

IEEE/ACM International Conference on Software Engineering (ICSE)
[pdf] [code]

2025

Erik Imgrund, Thorsten Eisenhofer, and Konrad Rieck

Adversarial Observations in Weather Forecasting

ACM Conference on Computer and Communications Security (CCS)
[pdf] [code] [poster] [arxiv]
Distinguished Paper Award

Jonas Möller, Lukas Pirch, Felix Weissberg, Sebastian Baunsgaard, Thorsten Eisenhofer, and Konrad Rieck

Adversarial Inputs for Linear Algebra Backends

International Conference on Machine Learning (ICML)
[pdf] [code]

Felix Weissberg, Jan Malte Hilgefort, Steve Grogorick, Daniel Arp, Thorsten Eisenhofer, Martin Eisemann, and Konrad Rieck

Seeing Through: Analyzing and Attacking Virtual Backgrounds in Video Calls

USENIX Security Symposium
[pdf] [code] [poster]

David Pape, Sina Mavali, Thorsten Eisenhofer, and Lea Schönherr

Prompt Obfuscation for Large Language Models

USENIX Security Symposium
[pdf] [code] [arxiv]

Thorsten Eisenhofer, Doreen Riepel, Varun Chandrasekaran, Esha Ghosh, Olga Ohrimenko, and Nicolas Papernot

Verifiable and Provably Secure Machine Unlearning

IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
[pdf] [code] [slides] [poster] [arxiv]

David Beste, Grégoire Menguy, Hossein Hajipour, Mario Fritz, Antonio Emanuele Cinà, Sébastien Bardin, Thorsten Holz, Thorsten Eisenhofer, and Lea Schönherr

Exploring the Potential of LLMs for Code Deobfuscation

Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA)
[pdf] [code]

Roei Schuster, Jin Peng Zhou, Thorsten Eisenhofer, Paul Grubbs, and Nicolas Papernot

Learned-Database Systems Security

Transactions on Machine Learning Research (TMLR)
[pdf] [arxiv]

2024

Joel Frank, Franziska Herbert, Jonas Ricker, Lea Schönherr, Thorsten Eisenhofer, Asja Fischer, Markus Dürmuth, and Thorsten Holz

A Representative Study on Human Detection of Artificially Generated Media Across Countries

IEEE Symposium on Security and Privacy (S&P)
[pdf] [preregistration] [code] [arxiv]

Jonathan Evertz, Merlin Chlosta, Lea Schönherr, and Thorsten Eisenhofer

Whispers in the Machine: Confidentiality in LLM-integrated Systems

Computing Research Repository (CoRR)
[pdf] [code] [arxiv]

Felix Weissberg, Jonas Möller, Tom Ganz, Erik Imgrund, Lukas Pirch, Lukas Seidel, Moritz Schloegel, Thorsten Eisenhofer, and Konrad Rieck

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

ACM Asia Conference on Computer and Communications Security (ASIACCS)
[pdf] [code] [arxiv]

Jonas Möller, Felix Weissberg, Lukas Pirch, Thorsten Eisenhofer, and Konrad Rieck

Cross-Language Differential Testing of JSON Parsers

ACM Asia Conference on Computer and Communications Security (ASIACCS)
[pdf] [code]

2023

Thorsten Eisenhofer

Security of Machine Learning Systems

Dissertation
[pdf] [slides]
Faculty Award for Outstanding Achievement

Thorsten Eisenhofer, Erwin Quiring, Jonas Möller, Doreen Riepel, Thorsten Holz, and Konrad Rieck

No more Reviewer #2: Subverting Automatic Paper-Reviewer Assignment using Adversarial Learning

USENIX Security Symposium
[pdf] [slides] [examples] [code] [arxiv]

Hojjat Aghakhani, Lea Schönherr, Thorsten Eisenhofer, Dorothea Kolossa, Thorsten Holz, Christopher Kruegel, and Giovanni Vigna

VenoMave: Targeted Poisoning Against Speech Recognition

IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
[pdf] [code] [arxiv]

Nico Schiller, Merlin Chlosta, Moritz Schloegel, Nils Bars, Thorsten Eisenhofer, Tobias Scharnowski, Felix Domke, Lea Schönherr, and Thorsten Holz

Drone Security and the Mysterious Case of DJI's DroneID

Network and Distributed System Security Symposium (NDSS)
[pdf] [code]

David Pape, Sina Däubener, Thorsten Eisenhofer, Antonio Emanuele Cinà, and Lea Schönherr

On the Limitations of Model Stealing with Uncertainty Quantification Models

European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)
[pdf] [arxiv]

2022

Michel Abdalla, Thorsten Eisenhofer, Eike Kiltz, Sabrina Kunzweiler, and Doreen Riepel

Password-Authenticated Key Exchange from Group Actions

Annual International Cryptology Conference (CRYPTO)
[pdf]

Lea Schönherr, Maximilian Golla, Thorsten Eisenhofer, Jan Wiele, Dorothea Kolossa, and Thorsten Holz

Exploring Accidental Triggers of Smart Speakers

Computer Speech & Language (CSL)
[pdf] [website] [arxiv]

2021

Thorsten Eisenhofer, Lea Schönherr, Joel Frank, Lars Speckemeier, Dorothea Kolossa, and Thorsten Holz

Dompteur: Taming Audio Adversarial Examples

USENIX Security Symposium
[pdf] [talk] [slides] [code] [arxiv]

2020

Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, and Thorsten Holz

Leveraging Frequency Analysis for Deep Fake Image Recognition

International Conference on Machine Learning (ICML)
[pdf] [slides] [code] [arxiv]

Lea Schönherr, Thorsten Eisenhofer, Steffen Zeiler, Thorsten Holz, and Dorothea Kolossa

Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems

Annual Computer Security Applications Conference (ACSAC)
[pdf] [talk] [examples] [arxiv]


Keynotes, Panels and Talks




Teaching


Instructor

  • Security and Privacy of AI, TU Berlin
    Master・Seminar・Summer 2025

  • Reproducing AI Attacks and Defenses, TU Berlin
    Master・Hands-on class・Winter 2024/25

  • Privacy and Security in Learning, TU Berlin
    Master・Seminar・Summer 2024

  • Security Playground for Generative Agents, TU Berlin
    Master・Hands-on class・Summer 2024

  • ML & Computer Security, Ruhr University Bochum
    Master・Hands-on class・Winter 2021/22

  • ML & Computer Security, Ruhr University Bochum
    Master・Hands-on class・Summer 2021

  • ML & Computer Security, Ruhr University Bochum
    Master・Hands-on class・Winter 2020/21

Teaching Assistant

  • Machine Learning for Computer Security, TU Berlin
    Master・Lecture・Summer 2025

  • Adversarial Machine Learning, TU Berlin
    Master・Lecture・Winter 2024/25

  • Machine Learning for Computer Security, TU Berlin
    Master・Lecture・Summer 2024

  • System Security, Saarland University
    Bachelor・Lecture・Summer 2021

  • System Security, Ruhr University Bochum
    Bachelor・Lecture・Summer 2020

  • Operating System Security, Ruhr University Bochum
    Master・Lecture・Winter 2019/20

  • System Security, Ruhr University Bochum
    Bachelor・Lecture・Summer 2019


News Coverage


Drone Security

Accidental Trigger