The browser is now the de facto enterprise operating system -- and it is also the primary attack surface for both humans and AI agents. Ed Wright of Menlo Security breaks down why the security controls organizations built for people are falling short in the age of agentic AI, and what a unified approach to browser security actually looks like in practice.
At RSAC Conference 2026, the floor at Moscone Center was buzzing with talk of AI -- but underneath the excitement, a sharper question was forming: are enterprises actually ready to secure the AI systems they are rushing to deploy? Ed Wright, VP of Product Marketing at Menlo Security, joined Sean Martin on-site to dig into exactly that question. With 85 percent of knowledge workers now operating primarily through a browser, Menlo Security has spent 13 years building the infrastructure to protect that surface -- and the threat landscape has just taken a significant turn.
The traditional browser threat model centers on humans: phishing links, malicious downloads, social engineering, deepfake video scams. Enterprises have spent billions on SSE stacks and endpoint protection stacks. Yet attacks continue to multiply. What Menlo Security is now tracking is a second threat model layered on top -- one designed specifically for AI agents. Agents use browsers to acquire data and complete tasks, often spinning up hundreds or thousands of headless browser sessions outside the enterprise perimeter, invisible to network security tools that only monitor the wire.
The threat profile for agents is distinct. Where a human might miss a suspicious link, an agent reads white-on-white text and zero-font-size characters embedded in web pages -- classic prompt injection techniques. Agents are maniacally focused on task completion and do not naturally separate instructions from data. A co-opted agent, redirected through hidden instructions, will pursue its new goal with the same single-mindedness as its original one. Ed Wright notes that the top concern among CISOs at the RSAC Conference CISO bootcamp -- confirmed by a live audience poll -- is data exfiltration from agents: an agent accessing files, scraping internal pages, passing data to external LLMs, and moving sensitive information outside the organization.
Menlo Security's response is a unified browser security platform that applies a single policy framework to both human and agentic workloads. The platform is built on four pillars: threat prevention including zero-day protection, secure application access, data security through AI Adaptive DLP, and file security. AI Adaptive DLP is the capability Ed Wright emphasizes most -- it functions as a combination of DLP and DSPM, discovering and classifying sensitive data across the organization and masking it in real time rather than blocking access. When traditional DLP blocks a human, they call IT. When it blocks an agent, the workflow silently fails. AI Adaptive DLP eliminates that failure mode entirely, keeping workflows uninterrupted while sensitive data stays protected at the source.
The unification argument cuts through a crowded point-solution market. Rather than deploying separate tools for prompt injection, file security, and application access, Menlo Security delivers a single layer of visibility and observability across the entire workforce. Single policies. Single set of capabilities. No stitching together of forensic data from disconnected systems. Ed Wright points to a Fortune 500 customer that deployed 20,000-plus agents in a short window after a board mandate -- and quickly realized they had no security guardrails in place for browser-based agentic activity. The emergency call to Menlo Security was not the first of its kind, and it will not be the last.
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Ed Wright, VP of Product Marketing, Menlo Security
LinkedIn: https://www.linkedin.com/in/edwardwright1/
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Menlo Security: https://www.menlosecurity.com
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KEYWORDS
Ed Wright, Menlo Security, Sean Martin, browser security, agentic AI security, AI agents, headless browsers, prompt injection, data exfiltration, AI Adaptive DLP, DSPM, zero-day threats, enterprise browser, SSE, RSAC Conference 2026, brand spotlight, brand story, brand marketing, marketing podcast
When the Browser Becomes the Battlefield: Human and Agentic Security in the Age of AI | A Brand Spotlight at RSAC Conference 2026 with Ed Wright, VP of Product Marketing at Menlo Security
[00:00:10] Sean Martin: Ah, my gosh, I can't remember where we are.
[00:00:16] Ed Wright: I think we're at RSA,
[00:00:17] Sean Martin: I think we're at RSA. Ed Wright, how are you?
[00:00:19] Ed Wright: Yeah, I'm doing great.
[00:00:20] Sean Martin: Doing good. Good to see you. Good to see you. We are in the heart of San Francisco, downtown Moscone Center, the place is buzzing with everybody looking at how do we overcome our security challenges
[00:00:33] Ed Wright: Yep.
[00:00:33] Sean Martin: And enable business to operate.
[00:00:35] Ed Wright: That's right. And I don't know if you've heard anything about AI out here, but I hear
[00:00:39] Sean Martin: there a lot, a lot of AI
[00:00:40] Ed Wright: anywhere there's like a little bit of that going around.
[00:00:42] Sean Martin: It's all a black box AI stuff. No, it's, uh, I love seeing innovations. I love being able to see inside the innovation to understand how it works, to find the proof that this stuff actually exists and can achieve an outcome. And hopefully we're gonna talk a little bit about that today.
[00:00:59] Ed Wright: Yeah. Sounds great.
[00:01:00] Sean Martin: With Menlo Security.
[00:01:01] Ed Wright: Yep.
[00:01:01] Sean Martin: And, uh, before we get into that, maybe a quick word about your role and a little bit about Menlo so folks have that as a background.
[00:01:08] Ed Wright: Sure. Yeah. So I'm Ed Wright. I'm the VP of Product Marketing at Menlo. Menlo has been around for 13 years now and we've been laser focused on browser security through the whole span of the company.
And a good way to think about it is historically Menlo has been the go-to for companies that really care about browser security, right? So for instance, Department of Defense, almost 3 million daily users on Menlo, eight of the 10 largest financial institutions in the world running Menlo, multiple government agencies all around the world.
And so we've been pretty laser focused on that. And what's happened over time is that the market has come to us almost, in that the browser has transformed over time into really the place where work gets done, right? It's sort of the almost de facto enterprise operating system.
And so 85% of knowledge workers' work is happening in the browser. And so as that's become a huge focal point, not only is it a focal point for work, but it's a focal point for attackers. And so that's our bread and butter business -- protecting knowledge workers, protecting the human in terms of how they interact with the browser.
[00:02:31] Sean Martin: Yeah, because a lot of apps -- many people probably don't know -- the knowledge workers just using an app, our web apps. They may have an app-looking interface, but they're also a web app that runs in the browser directly.
[00:02:44] Ed Wright: I mean, the entire digital transformation that's happened over the last few years. The SaaS explosion, right -- that's sort of all in the can already. And so when I'm interacting with the key applications that I have in the enterprise, I'm gonna be doing that through the browser. And not only that, but that's the sum total of human knowledge, so to speak, right?
As I interact with that, there are threats that occur within the framework of the browser. Phishing attacks have not decreased over the last three years. Social engineering attacks have not decreased over the last three years. But at the same time, the typical security stacks right now -- customers have spent billions and billions of dollars on their SSE stack, they spent billions of dollars on their endpoint protection stack -- and yet we continue to see these attacks multiply.
And so now we have this added huge sea change that's happening around agentic AI. And the reality is that even though if we looked at this a year ago, we would've said agents and applications are gonna talk via MCP -- that's gonna be very structured, organized, well secured -- but realistically, agents utilize browsers to acquire the data they need and complete their tasks. And they do that either through a browser agent that sits within a headed browser on their desktop, or even more frequently, they're out there spawning up headless browsers and using that to scrape websites.
[00:04:46] Sean Martin: And you do a search through an LLM interface. Sometimes you can see it, sometimes you don't always see that it's doing that. It's doing a search through some browser system that it has, right?
[00:04:56] Ed Wright: Yeah. And if you look at it -- and this is all almost in its infancy now -- you see things like Jensen's keynote the other day, and NVIDIA NIM and that sort of agentic approach becoming maybe the de facto way that enterprises roll out AI. If you look at OpenAI NIM, that's entirely headless browser based in terms of how it consumes information.
The threats are similar, but they're a little bit different. If I'm worried about what Sean is doing, I'm worried that Sean is going to click on that phishing link, I'm worried that Sean is gonna download that file and attached to that file is going to be a malicious zip attachment that Sean's gonna click on, I'm worried that Sean is gonna get social engineered, or that Sean is gonna get a deepfake video from his boss that says he needs to wire $10,000 to Jakarta or whatever.
From an agentic perspective, the threats are different. Agents see things that humans don't. You may look at a website and say there's just a white space on that webpage. An agent's gonna look at that and see white-on-white text, zero font size text. Prompt injection is a huge problem here. Agents are extremely smart, they're also extremely gullible. You tell an agent to do something, the agent's gonna go do it. They have a difficulty separating instructions from data. They treat malicious commands as a command. So you have to worry about all these hidden instructions, hidden in images, all of these things, that you don't have to worry about with humans.
And at the same time, agents are maniacally focused on accomplishing the task you give them. They're gonna access any data that they can possibly get to that they feel is in furtherance of that task. And so when we talk to enterprises, talk to our customers, the biggest threat that they see is data exfiltration from agents. That agent is gonna go grab a file, or scrape an internal page, acquire this data, go talk to another LLM, talk to another agent. And as it does that, it's potentially gonna share that data and then that data's outside the organization.
And really the problem that happens with network security -- well, I've got SSE, isn't that gonna take care of it? That's seeing the wire, but because it can't see inside the browser session, it's blind to these sorts of processes that are happening staying in the browser. And a lot of these agentic interactions happen outside the perimeter of the enterprise.
[00:08:21] Sean Martin: Describe that scenario.
[00:08:22] Ed Wright: So if I'm an agent and I go out and I request a headless browser to be opened, that happens outside the enterprise perimeter -- that happens in the cloud. And when that happens, I don't even see that on the wire at that point. And so I'm blind to the potential threats that occur there.
[00:08:48] Sean Martin: So what are some of the other -- well, talk to me about who you speak to within the enterprise that may or may not realize that some of this risk exists.
[00:08:57] Ed Wright: So I'll give you a great example. And this happened just in the last few months. We had a Fortune 500 customer. The CISO demanded an emergency meeting with us -- existing customer. When that happens, the first thought is, oh my gosh, what happened? So they flew over, took a meeting with our exec team, and they said, look, we had a mandate from the board to give every employee the ability to create and deploy their own agents. And so we did.
Our thought was that there's gonna be some uptake -- we're gonna roll this out over time. They wound up with 20,000 plus agents operating inside their organization. And this was in a very brief period of time. And they realized very quickly that they really hadn't thought about the security guardrails that they need to put in place around them. And this is specifically with the agents consuming information through browsers. And so that suddenly became a huge threat vector, potential threat vector, that they really hadn't thought out.
[00:10:17] Sean Martin: So this is their Slack running through the browser. This is their Salesforce running through the browser. This is --
[00:10:22] Ed Wright: Well, think about it like this. If you tell an agent to go research a particular topic for you, I don't know -- it's a black box in terms of how the agent does that. That agent could spin up five, ten, a hundred, a thousand different browser sessions and do that at machine speed. And those sessions could last milliseconds, seconds, hours, days -- whatever that agent needs to accomplish its task. So that's the hidden iceberg around how agents are being deployed today.
[00:11:05] Sean Martin: So when you're working with customers or even prospects, do they have a grasp of what the risk is and how it fits into their program? How does it fit in with the endpoint? How does it fit in with the network? How does it fit in with things like DLP and email and perimeter security and identity?
[00:11:30] Ed Wright: Yeah. Identity's a big one.
[00:11:31] Sean Martin: So talk to me a little bit about how some of those conversations go where they say we need help understanding where all this stuff comes together.
[00:11:37] Ed Wright: Yeah. So I'll list out the major concerns that they have around this. The first one, which we already talked about, is agents exfiltrating data. That is almost universally the largest concern. Saw the same thing at the CISO bootcamp here that I attended on Sunday. The biggest concern when they did the Slido poll and said what are you guys concerned about around agentic? It was data exfiltration. So that's a big one -- making sure that agents can't take my sensitive data and share it someplace where I don't want it to be shared.
That's one. The second one is that the agent will in some way have its goal hijacked. So I've told the agent to go do this. The agent consumes some sort of prompt injection and the agent says, I'm not supposed to do this anymore, I'm supposed to go do that. And the instruction that they get is -- get into the financial system if you can, secure this information and email it to evilhost@yahoo.com or whatever. So that's the second thing -- how do we protect our agents from essentially being co-opted?
The third one is that we want agents to get the data that they are entitled to, but we also wanna make sure they get access to all the data that they are entitled to. And in that scenario, a lot of enterprise data is trapped inside internal systems that don't have the type of API that is required to effectively communicate with an agentic system -- either because the API is simply not robust enough, or because the API was not designed to scale the way agentic AI requires. If you have an API that's designed for three to five API calls a minute and that API is getting 5,000 calls a minute, things can break down very quickly.
So the other piece is -- how do I make sure that the agent, and this goes back to agent identity -- how do I make sure that the agent is getting to the right data stores and the right data sources, but at the same time, how do I enable that without having to go and refactor these front ends and take on all of this technical debt? Like I need ROI now. I don't need ROI in 12 to 24 months.
[00:14:21] Sean Martin: Right. Without stifling, hopefully, the innovation that's coming from this. If you just move something over and make an agent and don't let it do what it's capable of because you have too many guardrails, you're kind of defeating the purpose.
[00:14:56] Ed Wright: Well, the other piece of that is if you think about something like DLP. For a human, you go grab a file, that file has sensitive data in it, I block it. So you go and complain to the IT team. They say go back and remove this data, or there's an exception or something. And it may take you four, five, six hours or the next day or whatever to get done what you want to do. And that's irritating, but that's sort of the way DLP works.
For an agent, what happens in that same scenario where an agent is blocked from accessing a file is just the workflow fails. That's it. And so that just stops and until you go realize that it stopped, nothing has happened there.
So I think the trick is -- and this is one of the big pillars -- one of the things that we've released with this browser security platform for humans and agents, which is the Menlo offering we're talking about, is what we call AI Adaptive DLP. And the idea there is think of it as a combination of DLP and DSPM at the same time. We'll go out into the organization, we'll find where the sensitive data lies -- whether that's in files or data stores, public cloud sources, wherever that is -- and we'll find it by PII, PHI, financial information, whatever that is. But we'll also allow the organization to create customized definitions. So we're also capturing corporate IP -- code, samples, whatever it is.
And so then we mask that in real time. Whether it's Sean going to find this document to just share it on Teams, or whether it's an agent going to access that document because it's gonna use it as a source file in a workflow that it's engaged in -- those workflows are uninterrupted. There's no block, but within that source itself, that sensitive data is masked out automatically. And that makes a lot of sense, both for human workflows, but especially for agentic workflows. And that's where, going back to the list of concerns, that first big concern which is data exfiltration -- we handle that very gracefully.
[00:18:01] Sean Martin: So talk to me, because we're getting close to wrapping up here. Talk to me about the importance of understanding the human and the agent spaces really well so you can tackle this problem. And what are some of the outcomes you see when you're working with customers?
[00:18:16] Ed Wright: I mean, the reality of it is the controls, the type of controls that you have to deploy for humans and for agents are similar. The policies and the flavor of those is different. And so the pillars that at Menlo we've always been known for are: threat prevention, including the prevention of zero-day threats; secure application access -- that becomes important because not only do you want to make sure your human employees get where they need to go, but you want to make sure that you put controls around the agentic workforce and make sure that they can get there; third is data security -- we already talked about AI Adaptive DLP; and then the fourth is file security -- that goes back to the scenario I talked about earlier where the file gets downloaded, it's got the malicious file in it, it gets executed.
What we've really done is taken those core capabilities and applied those to the agentic world. And we've done that in a way that's extremely easy to deploy. When you look at a lot of these agentic security offerings, either they're point solutions -- this solution is meant to solve prompt injection, this solution is meant to solve file security for agents -- so really unifying all that within a single platform, and then making it extremely simple to deploy a single layer of visibility and observability across the human workforce and the agentic workforce. Single set of policies, single set of capabilities. So that an organization doesn't have to go and deploy separate human browser security and agent browser security, or multiple point solutions that you then have to string together and try to figure out how to get some sort of reasonable forensic analysis or data out of at the end, and some policy that works on top of it.
[00:20:22] Sean Martin: And I'm gonna say probably great to have a team behind that that stands behind it as well -- like you just described that scenario, we need help, and here's Menlo. You're gonna have them in, or you're gonna go to them or get on a call or whatever. It's actually tackle that problem with them, side by side.
[00:20:37] Sean Martin: Well Ed, it's fantastic chatting with you.
[00:20:43] Ed Wright: Yeah, great to chat with you.
[00:20:43] Sean Martin: We'll have to have more conversations. Sounds like you're doing some really good things there. And I hope everybody has a chance to connect with Ed and the Menlo Security team online at LinkedIn. They can use your browser to do that
[00:20:55] Ed Wright: safely with Menlo Security. Yep. Follow us on LinkedIn. Go check out menlosecurity.com.
[00:21:01] Sean Martin: Yep. And think about how you're deploying agents, how you're using your browser, how you're enabling your workforce to take advantage of all these new technologies -- but safely -- with the Menlo Security team. Thanks everybody.