Uday Bhaskar Seelamantula
Uday Bhaskar Seelamantula is a security professional at Autodesk with a focus on innovative approaches to application security. With extensive experience in both offensive security and secure development practices, Uday is passionate about bridging the gap between traditional security concerns and the emerging risks presented by AI technologies. Currently working on novel fuzzing techniques and static analysis, Uday has a deep interest in how security can evolve to address the unique challenges posed by AI integrations in desktop applications.
Having collaborated with teams on projects that span across security incident response, threat modeling, and secure software development lifecycle practices, Uday brings a well-rounded perspective to the conversation on how organizations can better secure the applications we rely on. When not researching the latest vulnerabilities or AI threats, Uday enjoys mentoring colleagues and sharing knowledge to help shape the next generation of security professionals.
Outside of work, Uday keeps sharp by playing CTF challenges and running fuzz farms, while unwinding with snowboarding as a favorite way to relax.
Session
Everyone’s talking about securing cloud-native AI—but what about desktop applications, the unsung workhorses powering critical workflows in design, engineering, finance, and content creation? Often seen as “legacy,” today’s desktop apps are evolving—embedding local LLMs, enabling predictive UIs, intelligent automation, and offline inference.
This talk reframes the AI security conversation by spotlighting threats that emerge when AI meets the desktop. We’ll explore how these integrations open up new attack surfaces—prompt injection in embedded models, adversarial inputs, abuse of local inference, and vulnerable plugin ecosystems. These risks don’t replace traditional issues—they amplify them. Longstanding flaws like memory corruption, unsafe file parsing, and protocol-level bugs remain highly relevant.
We’ll demo two real-world attacks: prompt injection on a local model, and file-format fuzzing exposing a legacy crash. Then we’ll look at AI-aware threat modeling for desktop apps, including edge cases like tampered models and insecure automation. Finally, we’ll share practical strategies to integrate validation, fuzzing, and modeling into your secure SDLC.
If you thought desktop security was yesterday’s problem—think again. With AI in the mix, it’s more relevant, more complex, and more important than ever.