Lukas Pirch
Lukas Pirch
Doctoral Researcher
Affiliation: BIFOLD
Lukas Pirch is a PhD candidate at the research group of Prof. Dr. Konrad Rieck. His main interest is about finding vulnerabilities in source code and he uses graph-based machine learning approaches.
Recent Projects:
- VAMOS
- IVAN
Graph-based machine learning Vulnerability Discovery
Lukas Pirch, Micha Horlboge, Patrick Großmann, Syeda Mahnur Asif, Klim Kireev, Thorsten Holz, Konrad Rieck
Toward Securing AI Agents Like Operating Systems
Felix Weissberg, Lukas Pirch, Erik Imgrund, Jonas Möller, Thorsten Eisenhofer, Konrad Rieck
LLM-based Vulnerability Discovery through the Lens of Code Metrics
Jonas Möller, Lukas Pirch, Felix Weissberg, Sebastian Baunsgaard, Thorsten Eisenhofer, Konrad Rieck
Adversarial Inputs for Linear Algebra Backends
Jonas Möller, Felix Weißberg, Lukas Pirch, Thorsten Eisenhofer, Konrad Rieck
Cross-Language Differential Testing of JSON Parsers
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
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.