AI-Accelerated Exploits and the Case for Pre-Disclosure Virtual Patching in OT
About This Session
Nearly one in four vendor vulnerability advisories publish with no patch available at all, and 85% of OT organizations do not patch regularly even when patches exist.
Virtual patching against known CVEs addresses the patch window problem. It does not address the window before the CVE exists.
AI-powered vulnerability research has fundamentally changed how quickly vulnerabilities are discovered and weaponized.
How do critical infrastructure organizations protect their OT assets from a vulnerability that has been discovered privately before disclosed publicly?
We will walk through the mechanics of pre-disclosure virtual patching protection—how vulnerability intelligence shared ahead of public disclosure can be translated into network-level enforcement that protects critical assets before a patch is available, without exposing details that could enable a malicious actor to develop an exploit during the pre-disclosure window. This includes the “vaulted protection” model, where detection logic is delivered to enforcement points in a way that prevents adversaries from reverse-engineering the coverage to learn what vulnerability they are up against.
Virtual patching against known CVEs addresses the patch window problem. It does not address the window before the CVE exists.
AI-powered vulnerability research has fundamentally changed how quickly vulnerabilities are discovered and weaponized.
How do critical infrastructure organizations protect their OT assets from a vulnerability that has been discovered privately before disclosed publicly?
We will walk through the mechanics of pre-disclosure virtual patching protection—how vulnerability intelligence shared ahead of public disclosure can be translated into network-level enforcement that protects critical assets before a patch is available, without exposing details that could enable a malicious actor to develop an exploit during the pre-disclosure window. This includes the “vaulted protection” model, where detection logic is delivered to enforcement points in a way that prevents adversaries from reverse-engineering the coverage to learn what vulnerability they are up against.
Speaker
Daniel Paré
Principal Product Manager, Industrial OT Security - Palo Alto Networks
Daniel Paré is a Principal Product Manager, Industrial OT Security at Palo Alto Networks where he focuses on building tools to help industrial organizations maintain operational uptime by securing their mission critical systems. Prior to joining Palo Alto Networks Daniel spent time at GE and Siemens building Industrial IoT systems and software. Daniel completed his graduate engineering work at Stanford University and undergraduate work at the University of California, Davis.