Munish Walther-Puri
Munish Walther-Puri is a seasoned risk advisor and security strategist with two decades of experience translating complex cybersecurity and geopolitical realities into actionable frameworks. His expertise lies in identifying critical blind spots for decision-makers and developing innovative risk assessment methodologies. Currently, he serves as Interim Deputy CISO for a major manufacturer, building enterprise IT GRC programs and uplifting cybersecurity maturity. Munish's career spans diverse roles, including VP of Cyber Risk at Exiger, first Director of Cyber Risk at NYC Cyber Command, and Chief Research Officer at a dark web monitoring startup. His academic engagements include adjunct faculty positions at NYU, Columbia, and IANS Research, as well as a focus on the nexus of cyber, tech, national security, and industrial policy. He is a Life Member of the Council on Foreign Relations and a Senior Fellow at the Institute for Security and Technology. With a keen interest in the intersection of cyber, geopolitical, and supply chain risks, Munish is committed to bridging theory and practice, contributing to academic discourse, and advancing cutting-edge research in interconnected risk.
Sessions
This talk explores how energy infrastructure forms the backbone of resilient and robust AI ecosystems and challenges like transformer shortages and foreign dependencies threaten AI ecosystems and national security. We'll examine how disruptions in the energy sector can cascade across AI development, national security, and global competitiveness. By focusing on the often-overlooked role of power infrastructure, including the critical shortage of domestic sourced electrical equipment such as transformers, we'll reveal how energy resilience is the true key to AI dominance beyond algorithms and computing power.
What if cybersecurity’s biggest challenges—supply chain vulnerabilities, dark web economies, critical infrastructure risks—already have solutions? The problem isn’t finding new answers; it’s identifying existing ones systematically. This talk introduces TRIZ (Theory of Inventive Problem Solving), an engineering-based methodology that resolves contradictions and forecasts innovation patterns to tackle complex problems effectively. Think of the contradiction matrix as a “decision tree for conflicts,” helping you navigate dilemmas like "secure but open" or "privacy vs functionality." Patterns of evolution act as “forecasting the weather in technology,” enabling professionals to anticipate emerging risks and opportunities.
Attendees will learn how TRIZ can be applied to secure software supply chains, analyze underground economies on the dark web, design resilient critical infrastructure during natural disasters, and protect sensitive data while balancing privacy concerns. Through vivid case studies—including anti-phishing strategies and internal data leakage prevention—participants will gain actionable insights into integrating TRIZ into their analytical processes. By adopting this mindset, cybersecurity professionals can anticipate emerging threats, minimize surprises, and lead teams toward innovative solutions.