Brendan Dolan-Gavitt
AI Researcher at XBOW
Brendan Dolan-Gavitt is a distinguished engineer and AI researcher at XBOW, where he builds AI agents that find and fix software vulnerabilities before attackers can exploit them. He spent roughly a decade before that as an associate professor at NYU Tandon School of Engineering, researching software security and the security implications of AI-assisted coding tools such as GitHub Copilot. He holds a PhD from Georgia Tech and has previously worked at Columbia University, MIT Lincoln Laboratory and Microsoft Research. He co-authored StarCoder, a large language model for code generation, and helped build the AI system that became the first to reach number one on HackerOne's US leaderboard. On Secured by Galah Cyber, he discussed how AI penetration testing actually works and where it breaks down.
Career
- Now AI Researcher · XBOW
- Earlier Associate Professor · NYU Tandon School of Engineering
Sources: smashingsecurity.com
Key moments
Jump straight to the part of How AI Pen Testing Actually Works (and Where It Breaks) you want.
- 3:10 From academia to building autonomous security tools
- 5:00 Human pen testers vs AI agents: what is actually different
- 6:40 Where AI helps most: boring tasks and low hanging fruit
- 8:30 Scale: a thousand targets vs hiring a thousand testers
- 10:20 Accessibility, economics, and Jevons paradox
- 12:30 Accountability: audit evidence, traces, and “who signs off”
- 14:40 Scope control: avoiding prod and preventing out-of-scope actions
- 16:20 Safety checkers, overseer agents, and persuasion resistance
- 18:40 The cost question: VC money, inference pricing, and efficiency
- 21:20 When AI wastes money and why prioritisation matters
Connections
Spot something wrong? Suggest a correction Updated 25 September 2026
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