When AI Guesses and Security Pays: Choosing the Right Model for the Right Security Decision | A Brand Story Highlight Conversation with Michael Roytman, CTO of Empirical Security episode artwork

EPISODE · Dec 30, 2025 · 6 MIN

When AI Guesses and Security Pays: Choosing the Right Model for the Right Security Decision | A Brand Story Highlight Conversation with Michael Roytman, CTO of Empirical Security

from The ITSPmagazine Podcast · host Marco Ciappelli, Sean Martin, ITSPmagazine Their Story, Empirical Security

Title: The Right Model for the Right Security Task | A Brand Highlight Conversation with Michael Roytman, Co-Founder and CTO of Empirical SecurityIn this Brand Highlight conversation, Michael Roytman, Co-Founder and CTO of Empirical Security, joins Sean Martin to discuss why choosing the right AI model for the right task is essential for effective cybersecurity.Michael Roytman explains how Empirical Security takes a data-driven, Moneyball-style approach to preventative security. The company builds and maintains an ensemble of models, including the open EPSS model used by over 100 vendors, global models for vulnerability exploitation forecasting, and local models tailored to each customer's unique environment.The conversation explores a critical finding: LLMs perform poorly at predictive security tasks. Michael Roytman shares research he published in Forbes comparing EPSS to LLMs from Google, OpenAI, and Anthropic. While LLMs excel at summarization and classification, they struggle to predict future exploitation events. Purpose-built models like XGBoost consistently outperform LLMs for probability forecasting.Empirical Security positions itself as a data science company operating on security data rather than a traditional security vendor. With two-thirds of the founding team holding data science backgrounds, the company trains models from scratch and continuously retrains them as environments and threat landscapes evolve.This is a Brand Highlight. A Brand Highlight is a ~5 minute introductory conversation designed to put a spotlight on the guest and their company. Learn more: https://www.studioc60.com/creation#highlightGUESTMichael Roytman, Co-Founder and CTO of Empirical SecurityOn LinkedIn | https://www.linkedin.com/in/michael-roytman/RESOURCESLearn more about Empirical Security | https://www.empiricalsecurity.comAre you interested in telling your story?▶︎ Full Length Brand Story: https://www.studioc60.com/content-creation#full▶︎ Brand Spotlight Story: https://www.studioc60.com/content-creation#spotlight▶︎ Brand Highlight Story: https://www.studioc60.com/content-creation#highlightKEYWORDSEmpirical Security, Michael Roytman, data-driven security, vulnerability management, EPSS, risk-based vulnerability management, AI in cybersecurity, machine learning security, LLM limitations, predictive security models, XGBoost, local models, global models, preventative security, Moneyball security, cybersecurity AI, threat intelligence, security data science, model retraining, ITSPmagazine, Brand Highlight, Studio C60 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Episode metadata supplied by the publisher feed · Published Dec 30, 2025

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Security teams are overusing general purpose AI models for decisions they were never designed to make. This conversation explains why predictive security requires purpose built models, continuous retraining, and disciplined data science.

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When AI Guesses and Security Pays: Choosing the Right Model for the Right Security Decision | A Brand Story Highlight Conversation with Michael Roytman, CTO of Empirical Security

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