EMEA | WEBINAR
Rethinking Patient Zero Security: Cyber Defense Strategies for the AI Era
Wednesday, February 11
10 am GMT | 11 am CET | 3:30 pm IST
Learn how to move beyond patient‑zero detection with proactive, behavior-based strategies built for AI‑powered threats.
For decades, cybersecurity teams have relied on the “patient zero” model: one organization is hit first by a new attack, the industry studies it, and defenses are then deployed to protect others. This approach worked in a pre-AI threat landscape. In a post-AI world, however, it is increasingly ineffective. AI allows attackers to continuously mutate their techniques, so by the time an attack is analyzed, and defenses are rolled out, subsequent attacks look fundamentally different from the original. As a result, defenses based on prior incidents fail to keep up. Attacks now evolve at such speed that, in practice, every organization becomes patient zero. This session will take a technical deep dive into the limitations of patient zero detection in the face of AI-enabled adversaries. We’ll examine how threat actors use automation to launch simultaneous, polymorphic attacks and why organizations must shift toward preemptive defense models. Attendees will gain insight into the latest research and frameworks for building resilience against next-generation threats.
Meet the Presenters
Krupa Srivatsan
Senior Director, Product Marketing, Infoblox
Srikrupa has 23+ years of experience in technology in various roles including software development, product management and product marketing. Currently, as Senior Director of Product Marketing at Infoblox, she is responsible for messaging, positioning and bringing to market Infoblox’s preemptive security solutions that block sophisticated threats, including AI-driven attacks. She has an MBA from the University of California, Haas School of Business and a Computer Science Engineering degree.
Jeff Sims
Senior Data Scientist, Infoblox
Jeff Sims works at the intersection of frontier AI, cybersecurity, and adversarial risk, focusing on how advanced systems fail, are misused, and are operationalized in the real world. As an external expert to government agencies, frontier AI labs, and international organizations including the United Nations Office on Drugs and Crime, his work informs global guidance on AI-enabled cyber risk and strategic security implications. Jeff has served on confidential programs at frontier labs assessing national security–level harm scenarios and AI red teaming engagements, stress-testing prototype systems against high-consequence threats. He is widely cited for early research demonstrating LLM-driven offensive capabilities and autonomous malicious agents, and his work has shaped analysis across policy, research, and security communities. He is also a frequent speaker and commentator on emerging AI risk in major media and leading industry forums such as SecTor/Black Hat, BSides, and RSA.