Security teams today are inundated with vulnerability data and threat alerts, yet lack the contextual intelligence to filter signal from noise. In this session, we introduce an AI-powered approach (and decidedly not just another chatbot) to continuously scour the web and threat feeds to collect the latest vulnerability and exploit intel. By aggregating data from dozens of government, open-source, and vendor sources into a unified feed, you can eliminate manual research and never miss a critical update. By focusing on real-world exploitation: you can pin-point which vulnerabilities are actively targeted or likely to be exploited, rather than blindly following static severity scores. 

This talk will demonstrate how to operationalize AI-driven insights in your Vulnerability Management to supercharge your existing processes. You’ll see how security practitioners can automatically flag truly critical threats, filter out false alarms, and accelerate remediation through intelligence designed for action and not Q&A. Attendees will come away with a strategic understanding of leveraging AI-based vulnerability intelligence to reduce risk at scale, along with a glimpse of Nucleus Security’s latest tool in action through a live demo.

What You Will Learn

• Cutting through noise with AI: How an AI-driven engine can automatically aggregate and distill threat and vulnerability intelligence from across the web  saving analysts countless hours of manual data collection[3].
• From severity to risk context: How real-world exploit data can override or refine traditional severity ratings. Learn how the platform flags vulnerabilities exploited in the wild or by malware to correct outdated or misleading scores, ensuring teams focus on what’s actively dangerous – not just what a CVSS chart says is “critical”.
• Operationalizing AI insights in VM workflows: Practical ways to integrate exploitability insights and threat ratings into your vulnerability management lifecycle. See how you can use its intelligence fields in search filters, automation rules, and risk models (for example, auto-ticketing exploitable bugs or combining AI insights with frameworks like EPSS) to drive faster, risk-based remediation. 

Each takeaway is illustrated with a live demo, showing the new product augmenting the Nucleus platform to elevate your vulnerability management program from reactive to truly proactive.