126 citations · 179 across the 16 of their papers we have counts for
12 papers · 1 filter
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…
Cochise: A Reference Harness for Autonomous Penetration Testing
Andreas Happe, Jürgen Cito
Recent work on LLM-driven autonomous penetration testing reports promising results, but existing systems often bundle architectural, prompting, and tool-integration choices togethe…
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…
Can LLMs Hack Enterprise Networks? -- Replicated Computational Results (RCR) Report
Andreas Happe, Jürgen Cito
This is the Replicated Computational Results (RCR) Report for the paper ``Can LLMs Hack Enterprise Networks?" The paper empirically investigates the efficacy and effectiveness of d…
Towards Reliable Local Security Agents: Verifiable Post-Training for Linux Privilege Escalation
Philipp Normann, Andreas Happe, Jürgen Cito +1
LLM agents are becoming increasingly important in the security domain, but leading systems are often closed-source, cloud-based, hard to reproduce or use with sensitive code. This…
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,…
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…
Advances in Security in Computing and Communications
Jaydip Sen, Javier Franco-Contreras, Gouenou Coatrieux +15
In the era of Internet of Things (IoT) and with the explosive worldwide growth of electronic data volume, and associated need of processing, analysis, and storage of such humongous…