126 citations · 174 across the 16 of their papers we have counts for
17 papers
ATLAS: Discovering Agent Strategies through LLM-Guided Abstraction and Automata Learning
Ignacio D. Lopez-Miguel, Andreas Happe, Jürgen Cito +3
Large Language Model (LLM)-based agents are increasingly used for complex tasks such as software testing and cybersecurity assessment. While these agents demonstrate impressive cap…
The Ethics of Autonomous AI Agents for Offensive Security
Andreas Happe, Jürgen Cito, Jasmin Wachter
LLM-driven autonomous agents are reshaping offensive security. Unlike traditional penetration-testing tooling - deterministic, narrowly scoped, and operated by trained practitioner…
Reducing Token Usage of State-in-Context Agents using Minification
Nicolas Hrubec, Jürgen Cito
This paper presents a replication and extension of the recently introduced state-in-context agent framework. We independently re-implement the DirectSolve variant and evaluate it o…
Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents
Benjamin Probst, Andreas Happe, Jürgen Cito
Cloud-based Large Language Models (LLMs) can perform autonomous penetration-testing sub-tasks such as Linux privilege escalation, but raise security, privacy, and sovereignty conce…
Lost in Code Generation: Reimagining the Role of Software Models in AI-driven Software Engineering
Jürgen Cito, Dominik Bork
Generative AI enables rapid "vibe coding" and agentic software engineering, where natural-language prompts yield working software systems. This lowers barriers to software creation…
Online and Interactive Bayesian Inference Debugging
Nathanael Nussbaumer, Markus Böck, Jürgen Cito
Probabilistic programming is a rapidly developing programming paradigm which enables the formulation of Bayesian models as programs and the automation of posterior inference. It fa…
Adversarial Bug Reports as a Security Risk in Language Model-Based Automated Program Repair
Piotr Przymus, Andreas Happe, Jürgen Cito
Large Language Model (LLM) - based Automated Program Repair (APR) systems are increasingly integrated into modern software development workflows, offering automated patches in resp…
Static Factorisation of Probabilistic Programs With User-Labelled Sample Statements and While Loops
Markus Böck, Jürgen Cito
It is commonly known that any Bayesian network can be implemented as a probabilistic program, but the reverse direction is not so clear. In this work, we address the open question…
On the Surprising Efficacy of LLMs for Penetration-Testing
Andreas Happe, Jürgen Cito
This paper presents a critical examination of the surprising efficacy of Large Language Models (LLMs) in penetration testing. The paper thoroughly reviews the evolution of LLMs and…
Recognition Without Mitigation: Ethical Frameworks in Autonomous Offensive-LLM Agent Research
Andreas Happe, Jürgen Cito
Large language models have moved from advising on offensive security to autonomously conducting it. A growing literature presents agents that execute reconnaissance, exploitation,…
The Road to Hybrid Quantum Programs: Characterizing the Evolution from Classical to Hybrid Quantum Software
Vincenzo De Maio, Ivona Brandic, Ewa Deelman +1
Quantum computing exhibits the unique capability to natively and efficiently encode various natural phenomena, promising theoretical speedups of several orders of magnitude. Howeve…
Benchmarking Practices in LLM-driven Offensive Security: Testbeds, Metrics, and Experiment Design
Andreas Happe, Jürgen Cito
Large Language Models (LLMs) have emerged as a powerful approach for driving offensive penetration-testing tooling. Due to the opaque nature of LLMs, empirical methods are typicall…
Can LLMs Hack Enterprise Networks? Autonomous Assumed Breach Penetration-Testing Active Directory Networks
Andreas Happe, Jürgen Cito
Enterprise penetration-testing is often limited by high operational costs and the scarcity of human expertise. This paper investigates the feasibility and effectiveness of using La…
Got Root? A Linux Priv-Esc Benchmark
Andreas Happe, Jürgen Cito
Linux systems are integral to the infrastructure of modern computing environments, necessitating robust security measures to prevent unauthorized access. Privilege escalation attac…
LLMs as Hackers: Autonomous Linux Privilege Escalation Attacks
Andreas Happe, Aaron Kaplan, Juergen Cito
Penetration-testing is crucial for identifying system vulnerabilities, with privilege-escalation being a critical subtask to gain elevated access to protected resources. Language M…
Understanding Hackers' Work: An Empirical Study of Offensive Security Practitioners
Andreas Happe, Jürgen Cito
Offensive security-tests are a common way to pro-actively discover potential vulnerabilities. They are performed by specialists, often called penetration-testers or white-hat hacke…
Getting pwn'd by AI: Penetration Testing with Large Language Models
Andreas Happe, Jürgen Cito
The field of software security testing, more specifically penetration testing, is an activity that requires high levels of expertise and involves many manual testing and analysis s…