Talk Title: Human Tradecraft at Machine Speed: Traditional vs. AI-Assisted Red Teaming

Abstract

Traditional red teams emulate human adversaries through manual and tool enabled reconnaissance, social engineering, exploitation, lateral movement, persistence, and data exfiltration. Artificial intelligence does not eliminate these fundamentals, but it is changing their speed, scale, adaptability, and accessibility.

This session compares a conventional red-team engagement with an AI-assisted operation across the same attack lifecycle. It examines how generative and agentic AI can support target research, tailored phishing, vulnerability analysis, payload development, evasive code modification, attack-path exploration, and campaign orchestration. The session also addresses the expanding role of red teams in evaluating AI applications themselves, including prompt injection, sensitive-data exposure, retrieval manipulation, excessive agency, insecure tool use, and compromised autonomous agents.

Recent, documented examples of adversarial AI use will be used to distinguish demonstrated capabilities from speculation. Attendees will leave with a practical understanding of where AI provides attackers with a meaningful advantage, where skilled human operators remain essential, and how security teams should evolve testing, telemetry, identity controls, and incident response for attacks conducted at machine speed.

Speaker Bio

Dr. Saylor is 30-year IT/Cyber veteran and 26 years as a University Professor of Cyber and Digital Forensics & Incident Response (DFIR) – currently at The University of Texas at San Antonio.  24-year FBI InfraGard member, past president, and current Healthcare Sector Chief of the N. Texas Chapter, North Texas Crime Commission member, and a Fusion Liaison officer for the North Texas Fusion Center.   Past vCIO at the League, current CEO and incident response lead for Blackswan Cybersecurity, and Executive Director for the US Cyber Defense Center - focused on cybersecurity workforce development.