The rogue agent problem: A conversation with Gil Elbaz at the Hg Digital Summit
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What is Gil Elbaz’s background and how did he end up founding ONIX?
Agents, they are in many ways, they're as capable as employees, and at the same time, they're not accountable for their own actions. And so if you yell at an agent, it will respond, oh, you're right. I'm sorry for deleting that database, right? So essentially, they are employees on one hand, and the other hand, they're not accountable for their actions. And so they require a different level of oversight to what we did with employees. So with employees, we created bounds from an identity perspective. And those are still good tools to have in general for agents as well, but they're not enough. And so with agents, And this is an opinionated observation, right? But with agents, we do think that runtime protection is critical.
And so runtime protection means literally looking at any token or any text, any context that is hitting the LLM of the agent, the brain, and anything that is coming out of that LLM, validating it before it hits our systems.
I'm John Cranmer, part of HG's tech team, and my guest today is Gil Abaz, co-founder and chief AI officer at ONIX. Gil started in academia at Technion, was the CTO and co-founder at Datagen, creating data to train AI systems, pioneering synthetic data for visual AI. He then joined NVIDIA, working as a direct report to the CTO, working on AI agents. Today, he's building ONIX, a secure AI control plane for the agentic era. Many organizations are now operating their own AI agents, and ONIX is helping them identify, monitor, and control their usage. Gil, great to have you here today. It's a pleasure
to
be here. Thank you very much. Could you give us a bit about your background and essentially how you reached this point with ONIX today?
I started off early on in the machine learning space at a time where we couldn't even say the words AI. People would laugh you out of the room. And essentially, we were building out these very early models. Since then, we've gone through machine learning models that have been able to produce high quality capabilities that were very specific, that were very well defined workflows. But today, we're seeing now with AI, of course, and AI agents that are all capable, that understand images, that understand video, that understand code, and that are able to produce all of these things in seamless ways. We see these general systems that are now applicable to everything, essentially, and can actually impact in positive ways almost every human workflow today.
and are becoming more and more integral in every single product, every single application, every single workflow internally and also externally. And so this has been quite a revolution right now.
Brilliant. Because I think we really are seeing a complete shift in this old attack surface that we used to see. You know, in the past, well, you know, if you go back 20 years ago, there was always a very clear boundary between what was yours and what wasn't. And that was blurred very rapidly, you know, in the SaaS era. But now that has compounded even more because everything pretty much is now attack surface. It's your agents, it's your data that your agents interact with. Anything can start to introduce issues and vulnerabilities. And I think that really shifts the way we're thinking about cybersecurity and specifically from a AI perspective. Sort of see it in two or three different buckets. It's the It's the external attack bucket, which has always existed, but now have more opportunities than before.
But then you've got these two interesting internal dynamics. Your users, again, always been there, but now they've got different tools and mechanisms that they can seize upon. But also, it's the actual AI itself. It can drift out of alignment. It can do something that is unexpected, not on purpose, just because it doesn't know better and it doesn't have the right controls in place. I'd be really interested to see what you're seeing in those areas and the sort of experience. Is that something you agree with?
From my time in NVIDIA, I was in the CTO office of NVIDIA working on AI agent infrastructure, a few pretty large multi-agent projects.
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Chapters
5 chapters
1
What is Gil Elbaz’s background and how did he end up founding ONIX?
0:03–6:46
2
How has the AI attack surface changed and why does the old “perimeter” no longer exist?
6:46–15:25
3
What are “rogue agents” and what destructive actions can they take without being prompted?
15:25–24:50
4
How do agents communicate invisibly through Slack, email, and other channels?
24:50–32:44
5
Why is visibility of shadow AI tools essential for enterprise security?
32:44–34:07
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