Attackers move at machine speed. Can you prove what's actually exposed?

About this event

How security leaders are cutting real exposure at the fundamentals, before automated exploitation turns a known weakness into a breach, a board problem, and an audit finding. The gap between disclosure and exploitation keeps shrinking. Attackers can now reverse-engineer a patch, find the weakness, and start exploiting it before many teams have deployed the fix. For anyone still carrying a long vulnerability queue, legacy systems, cloud sprawl, and a monthly patch cycle, the question has changed. It is no longer how many findings are open. It is which weaknesses are actually reachable, what an attacker could do with them, and how fast that exposure is coming down. AI is raising the stakes on both sides. The same capability that helps defenders find, prioritize, and fix risk also helps attackers find, chain, and exploit it at machine speed. That makes the fundamentals more important, not less: asset visibility, patching, identity controls, configuration, segmentation, and attack-path reduction. But those fundamentals now have to be prioritized around real exposure, not dashboard volume. For US security leaders, this is now a board, audit, and regulatory conversation as much as a technical one. Whether you are working to NIST CSF, SOC 2 or ISO 27001, NIST's AI Risk Management Framework, or your own internal risk frameworks, you are increasingly expected to show what is exposed, what matters most, what has been reduced, and how fast you are closing the gap. Chaired by Michael York, VP of Information Security and DevOps at SavvyMoney, this peer-led roundtable looks at how security leaders are moving from vulnerability volume to exposure reduction.

• Where the disclosure-to-exploit window is changing the math, and how teams separate genuinely reachable exposure from dashboard noise.
• How leaders prioritize the fundamentals that buy back time: patching, identity blast radius, cloud configuration, segmentation, and attack-path reduction.
• What boards, auditors, and regulators now expect teams to prove about real exposure, remediation speed, and resilience, including how AI governance frameworks are shaping those expectations.