Rich Harang

Rich Harang is a Principal Security Architect at NVIDIA, specializing in ML/AI systems, with over a decade of experience at the intersection of computer security, machine learning, and privacy. He received his PhD in Statistics from the University of California Santa Barbara in 2010. Prior to joining NVIDIA, he led the Algorithms Research team at Duo, led research on using machine learning models to detect malicious software, scripts, and web content at Sophos AI, and worked as a Team Lead at the US Army Research Laboratory. His research interests include adversarial machine learning, addressing bias and uncertainty in machine learning, and ways to use machine learning to support human analysis. Richard’s work has been presented at USENIX, BlackHat, IEEE S&P workshops, and DEF CON AI Village, among others, and has also been featured in The Register and KrebsOnSecurity.
Rich Harang

Posts by Rich Harang

Generative AI / LLMs

Best Practices for Securing LLM-Enabled Applications

Large language models (LLMs) provide a wide range of powerful enhancements to nearly any application that processes text. And yet they also introduce new risks,... 11 MIN READ
Picture of the ML security training classroom at Black Hat USA

AI Red Team: Machine Learning Security Training

At Black Hat USA 2023, NVIDIA hosted a two-day training session that provided security professionals with a realistic environment and methodology to explore the... 4 MIN READ

Securing LLM Systems Against Prompt Injection

Prompt injection is a new attack technique specific to large language models (LLMs) that enables attackers to manipulate the output of the LLM. This attack is... 15 MIN READ
Letters, numbers, and padlocks on black background

Improving Machine Learning Security Skills at a DEF CON Competition

Machine learning (ML) security is a new discipline focused on the security of machine learning systems and the data they are built upon. It exists at the... 8 MIN READ