​Description

​TBD

​​Agenda

​18:00 Doors open

​18:30 - 20:00 Speakers and Topics TBD

​20:00 - 21:00 Networking

​21:00 Doors close

​Speakers

​Talk 1 - Cybersecurity in the era of LLMs and agents

​Speakers: Ramy Aouinet (Co-founder, Antitech)

​Abstract: Modern threats such as jailbreaks, prompt injection, model poisoning, and data exfiltration are already actively targeting every AI deployment, while traditional security tools remain reactive and outdated. The core problem is that there is no unified, end-to-end security infrastructure designed specifically for AI agents from the framework layer (how agents are built and orchestrated), to continuous testing (red teaming), to real-time protection (defensive layers against injections and leaks).

​Bio: I’m Ramy Aouinet, co-founder of Antitech, AI engineer. Recognized among the top 8 in Africa in AI, I focus on building robust and scalable intelligent systems, with expertise in reinforcement learning (RL), LLM infrastructure, and product architecture. I’ve worked on designing end-to-end AI pipelines, from research to production. I also served as an NVIDIA DLI instructor, where I taught topics ranging from deep learning to AI agents and anomaly detection. My work further extends into applying AI to neuroimaging, particularly for Autism Spectrum Disorder (ASD) and stroke research.

​Talk 2 - TBD

​Speakers: Yury Leonychev (VP of Technology, Wallarm)

​Abstract: to fill

​Bio: to fill

​Talk 3 - Open Source Security at Scale: Automating Vulnerability Detection and Hardening in Top GitHub Repositories

​Speakers: Arpit Jain (Independent, ex-KPMG Ignite)

​Abstract: Many of the most popular projects on GitHub ship with unresolved security gaps in their CI/CD workflows and dependency configurations, often hiding in plain sight under inadequate code scanning practices. Drawing on five years of open source contributions, including merged pull requests in Kubernetes and Mermaid, I built an intelligent agent that systematically scans top repositories, detects security workflows that need hardening, and opens targeted pull requests to fix them. The focus is on small but high-impact changes: enforcing least-privilege permissions on GitHub Actions workflows and flagging vulnerable dependencies.

​The results challenge the assumption that automated contributions are noise. Roughly ninety percent of the reviewed pull requests have been merged, with over 150 accepted across:

• ​Organizations like Google, Microsoft, and AWS

• ​Projects like NumPy, Vue.js, Node.js, Rust, LLVM, and the Kubernetes ecosystem

• ​Major Apache Software Foundation projects like Kafka, Airflow, and Tomcat.

​This talk will walk through how the agent works, what patterns it detects, how it generates pull requests that pass human review, and what the high merge rate reveals about the current state of open source security. Attendees will leave with a practical model for using automation to close security gaps across the ecosystem at scale.

​Bio: Arpit is a freelance developer improving the security posture of major projects on GitHub. Alongside his open source contributions, he is exploring indie hacking, with a particular focus on data engineering and connecting disparate data sources. Arpit has presented on open source security at the Open Source Security Foundation (OpenSSF) conference organized by the Linux Foundation in 2025. Previously, he led a team of four as an Engineering Manager at KPMG Ignite Tokyo.

​​Organizers

​Ilya Kulyatin is an entrepreneur with work and academic experience in the US, Netherlands, Singapore, UK, and Japan. He holds a BA in Economics, an MA in Finance, and an MSc in Machine Learning. He's a 3x founder, now helping Japan grow the local AI ecosystem through a not-for-profit community, Tokyo AI (TAI), while building an AI-native system integrator and solutions provider, Foundry Labs株式会社.

​​Supporters

​Tokyo AI (​​​TAI) is the biggest AI community in Japan, with 4,000+ members mainly based in Tokyo (engineers, researchers, investors, product managers, and corporate innovation managers).

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