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Kurtis Shelton

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Principal AI Researcher

Kurtis plays a pivotal role as an AI/ML Security Engineer, where his expertise is central to guiding clients through the intricate process of identifying and neutralizing security threats in their machine learning infrastructures. As the architect behind NetSPI's AI/ML service line, he now spearheads the division and manages its operations. His responsibilities include executing comprehensive security assessments and penetration tests, meticulously analyzing system vulnerabilities, and formulating strategic recommendations for robust remediation. Furthermore, Kurtis is a leading figure in the research domain of adversarial machine learning, continually pushing the boundaries of security in the field.

More by Kurtis Shelton

AI/ML Pentesting

Balancing Security and Usability of Large Language Models: An LLM Benchmarking Framework

Explore the integration of Large Language Models (LLMs) in critical systems and the balance between security and usability with a new LLM benchmarking framework.

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Adversarial Machine Learning

Ask These 5 AI Cybersecurity Questions for a More Secure Approach to Adversarial Machine Learning

These questions will kickstart your journey into Adversarial Machine Learning and AI security with key considerations from the start.

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eBooks & Whitepapers

The CISO’s Guide to Securing AI/ML Models 

Empower your AI journey with security from the start. Learn how to navigate the nuances of Adversarial Machine Learning (AML) and safeguard your LLMs.

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Adversarial Machine Learning

Common Terminology in Adversarial Machine Learning

Learn about common terminology used in artificial intelligence, machine learning, and adversarial machine learning from NetSPI.

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Videos & Livestreams

How AI and ML Help Evolve Cybersecurity

NetSPI security consultant Kurtis Shelton shares in this fireside chat with SmartBrief’s Susan Rush how AI and ML can evolve approaches to cybersecurity by accelerating coding and other rote tasks, freeing up human resources for creativity, research, and testing that advances the work of both attackers and defenders.

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