5 papers · 1 filter
Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs
Giulio Zizzo, Giandomenico Cornacchia, Kieran Fraser +7
As large language models (LLMs) become integrated into everyday applications, ensuring their robustness and security is increasingly critical. In particular, LLMs can be manipulate…
Towards Assuring EU AI Act Compliance and Adversarial Robustness of LLMs
Tomas Bueno Momcilovic, Beat Buesser, Giulio Zizzo +2
Large language models are prone to misuse and vulnerable to security threats, raising significant safety and security concerns. The European Union's Artificial Intelligence Act see…
Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs
Tomas Bueno Momcilovic, Dian Balta, Beat Buesser +2
This paper presents an approach to developing assurance cases for adversarial robustness and regulatory compliance in large language models (LLMs). Focusing on both natural and cod…
MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks
Giandomenico Cornacchia, Giulio Zizzo, Kieran Fraser +3
The proliferation of Large Language Models (LLMs) in diverse applications underscores the pressing need for robust security measures to thwart potential jailbreak attacks. These at…
Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI
Ambrish Rawat, Stefan Schoepf, Giulio Zizzo +10
As generative AI, particularly large language models (LLMs), become increasingly integrated into production applications, new attack surfaces and vulnerabilities emerge and put a f…