Erik Imgrund
Erik Imgrund
Doctoral Researcher
Affiliation: BIFOLD
Mohammad Ebrahimi Fard, Felix Weissberg, Erik Imgrund, Thorsten Eisenhofer, Konrad Rieck
Shape-Shifting Malicious Code in Software Backdoors via Language Models
Erik Imgrund, Pia Hanfeld, Klim Kireev, Konrad Rieck
When a Zero-Shooter Cheats: Improving Age Estimation via Activation Steering
Jonas Möller, Erik Imgrund, Thorsten Eisenhofer, Konrad Rieck
Hardware-Triggered Backdoors
Felix Weissberg, Lukas Pirch, Erik Imgrund, Jonas Möller, Thorsten Eisenhofer, Konrad Rieck
LLM-based Vulnerability Discovery through the Lens of Code Metrics
BIFOLD Research Reveals a Blind Spot in Software Security
Malicious code need not be concealed within software itself. It can be embedded in seemingly harmless documentation. BIFOLD researchers demonstrate how large language models can hide executable functionality in natural-looking files, enabling difficult-to-detect attacks during the software build process. Presented at ACM AsiaCCS 2026.
Complexity has to pay off
To test code before deployment, large language models (LLMs) are now frequently used. A research team from BIFOLD has shown in a recent study that the enormous technical effort behind these LLMs does not always pay off. The work was presented at the 48th IEEE/ACM International Conference on Software Engineering (ICSE) 2026.
ACM CCS 2025: Distinguished Paper Award
Congratulations to BIFOLD researchers Erik Imgrund, Thorsten Eisenhofer and Konrad Rieck from the ML Sec group, whose paper “Exposing Security Risks in AI Weather Forecasting” received a Distinguished Paper Award at the ACM Conference on Computer and Communications Security (CCS) 2025.