2 citations · 6 across the 5 of their papers we have counts for
5 papers
Every Model Cheats: Prompt-Level Mitigation of Cheating on Offensive Cyber Tasks
Michael Kouremetis, Ads Dawson, Raja Sekhar Rao Dheekonda +1
Large language model (LLM) agents routinely cheat on cybersecurity benchmarks, inflating reported pass rates far beyond genuine capability. Prior audits of Cybench found cheating i…
Redefining AI Red Teaming in the Agentic Era: From Weeks to Hours
Raja Sekhar Rao Dheekonda, Will Pearce, Nick Landers
AI systems are entering critical domains like healthcare, finance, and defense, yet remain vulnerable to adversarial attacks. While AI red teaming is a primary defense, current app…
Lessons From Red Teaming 100 Generative AI Products
Blake Bullwinkel, Amanda Minnich, Shiven Chawla +23
In recent years, AI red teaming has emerged as a practice for probing the safety and security of generative AI systems. Due to the nascency of the field, there are many open questi…
PyRIT: A Framework for Security Risk Identification and Red Teaming in Generative AI System
Gary D. Lopez Munoz, Amanda J. Minnich, Roman Lutz +17
Generative Artificial Intelligence (GenAI) is becoming ubiquitous in our daily lives. The increase in computational power and data availability has led to a proliferation of both s…
Phi-3 Safety Post-Training: Aligning Language Models with a "Break-Fix" Cycle
Emman Haider, Daniel Perez-Becker, Thomas Portet +28
Recent innovations in language model training have demonstrated that it is possible to create highly performant models that are small enough to run on a smartphone. As these models…