Proofpoint Protect 2026 | Selena Larson, Proofpoint

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Selena Larson

Principal Threat Researcher, Cybercrime Team Lead

Proofpoint

play_circle_outline AI-Driven Social Engineering and the Bifurcation Between Elite and Low-Skill Attackers

play_circle_outline AI-generated templated code and comments in malware/tooling

play_circle_outline Multilingual campaign scale enabled by AI natural language abilities

play_circle_outline Adaptive Detection Strategies for Sandbox Evasion and Custom CAPTCHA Bypass

play_circle_outline Phishing-as-a-service, ClickFix and device code phishing commercialization

play_circle_outline BlueMoon exploit chain: patch-gap zero day possibly exploited with AI

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Selena Larson, Proofpoint

Selena Larson

Principal Threat Researcher, Cybercrime Team Lead Proofpoint

In this interview from Proofpoint Protect 2026, Selena Larson, principal threat researcher at Proofpoint Inc., joins theCUBE's John Furrier to discuss how AI is reshaping both sides of the cybersecurity battle, sharpening the tools of skilled attackers while exposing the sloppiness of low-level threat actors. Larson explains that while defenders are building more dynamic, behavioral detections, the threat landscape is bifurcating: elite actors are refining malware and phishing kits, while less sophisticated ones grow careless, leaving exposed infrastructure a... Read more

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How have cyber attackers' tactics changed since 2023 with the adoption of AI—are attacks more sophisticated now, or have techniques regressed despite more believable social engineering? add

How are cyber threat actors (both less skilled "sloppy" actors and more skilled malware developers) adopting AI and templates in their code and attack workflows, and does this change the effectiveness of their attacks? add

How is AI changing threat actors' ability to scale and localize phishing/lure campaigns across multiple languages and geographies? add

How are attackers evolving their techniques to bypass honeypots, sandboxes, and traditional detections (e.g., novel CAPTCHAs), and what should defenders do to adapt their detection strategies? add

How are threat actors using AI to build and sell attack services, and can you give examples? add

What is the BlueMoon exploit chain, who used it, and how did attackers leverage AI to develop exploits during the Chromium-to-Chrome patch gap (creating a "patch gap zero day")? add

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Selena Larson, Proofpoint

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John Furrier

>> Palo Alto Studio Connection, Silicon Valley and Wall Street. I'm John Furrier, the co-CEO here with Dave Vellante, my co-host.

Selena Larson

>> I'm John Furrier, of theCUBE.

John Furrier

>> We are here in San Diego for Proofpoint Protect 2026, part of our NYSE Wired program and our open community. We're unpacking all the data around security in the enterprise as agents and data become more prevalent. So Cybersecurity posture changes. We have a theCUBE alum back on threat research, Selena Larson, back formerly on at another conference, M-WISE, which is no longer around, which is really one of the premier threat conferences, really talking about the bad guys and all the nation states. Great to see

Selena Larson

>> you.Yeah, thanks so

John Furrier

>> much.Podcaster. Yes. Researcher. So first of all, congratulations on the continued podcast and getting the content out

Selena Larson

>> there.Thank

John Furrier

>> you.Thank you. But I really wanna dig into what's changed in the past few years. Last time you were on was 2023. AI continues to thunder away, but the game has gotten much higher level action on the threats, more organized, more complicated, and more effective. But AI's come on the good side too. So what's different? Give us that lowdown between, 2023, the old way, seems like yesterday, and today.

Selena Larson

>> It does feel like yesterday, actually. I think about it, I was like, wow, that was 3 years ago. and that really was, I feel like, in 2023 when AI was just emerging, people were using it in their own environments, and threat actors had started to adopt things. So I would push back a little bit on this idea that things have gotten better and attackers have gotten smarter. I think that in some ways they have, but in some ways they're regressing. And I think it's been really fun to see because for many of the threat actors, they're using AI in the same way that defenders are, to streamline their operations, to make their social engineering a lot better, right? And some people are using it for marketing or styling, things like that. And they're also using it in their attack chains. But what's really interesting is the good threat actors are using it very effectively and are cutting down the time it takes to develop something such as malware or spam delivery, things like that. But for bad threat actors, the sort of bottom of the barrel folks, the low-hanging fruit, so to speak, they're adopting it. And yes, it does make some of their attacks a little bit more believable. Their social engineering is a lot better. we were talking before this started, the emails look really believable. The language is there, the design is pretty good. But what we've seen is actually regression in techniques. So they're not necessarily as effective. So they'll leave things exposed on the internet.

John Furrier

>> They get sloppy.

Selena Larson

>> They get sloppy. It's very, very sloppy.

John Furrier

>> So you're pushing back on the idea that the bad guys are getting better. You think they are getting better?

Selena Larson

>> I think the good guys are getting better.

John Furrier

>> And the bad guys are bifurcating into the elite.

Selena Larson

>> Yes.

John Furrier

>> And the idiots.

Selena Larson

>> Absolutely. Yes.

John Furrier

>> Well, I say this because a quote on theCUBE recently— I won't say who the person was because it may be taken the wrong way. She said, "AI makes smart people smarter and dumb people dumber." And I'm like, okay, that kind of lands, but let's just get at the implications. It's kind of true. If you really don't know what you're doing, you get a false sense of security. And you were referencing that, 'cause I think that speaks to some of the sloppiness. We used to call it script kiddies back in the day. Remember those kind of pejorative terms? But what has that done to the artifacts? So what's been the impact of this? Has there been a backlash in amongst the bad guys? Like, hey, say, let the big players take the big game, or is it just too much for everybody?

Selena Larson

>> that's really interesting that you bring that up. So WIRED a couple of months ago published a great look at how threat actors and hackers are responding in some of the forums to the adoption of AI in tooling and marketing and things like that. And they don't love it. And so a lot of the threat actors—

John Furrier

>> Don't love it in which way?

Selena Larson

>> They— well, they were like, get this AI slop out of—

John Furrier

>> out of their own slop problem.

Selena Larson

>> Well, yeah, because they're like, I don't want to read this. can you— I just want to buy this tool. Why are you adding these things that I don't need? It doesn't work anyway. Anymore. So they are getting frustrated with the threat actor adoption with Copilot. And at the same time, you have threat actors that are using AI tools to build things like phishing kits, for example, using device code phishing, right? So they'll make a really sleek landing page and says, oh, this, impersonating Microsoft or DocuSign, and then they'll have a code to input it to legitimately associate an application, a malicious application with your Microsoft account. But if you look at the rest of the attack chain, the panel itself will be exposed. The domain won't be very believable. The lure itself, if it's using something like social engineering, sometimes it might be pretty good. And sometimes the email is just blank because they don't know how to actually do vibe

John Furrier

>> malware.They're bad

Selena Larson

>> at Yeah, they're just not very good.

John Furrier

>> They're not marketing their own security.

John Furrier

>> Yeah.

Selena Larson

>> Yeah.So we have these sort of these slop actors that are doing a lot of that. But then you also have some pretty creative threat actors and threat actors who have done malware development in the past, who have created really unique and interesting loaders or botnets and things like that. They're also adopting AI and you can see it in their code, right? Because Nobody comments their code like an AI comments code. And so you'll see that throughout and they'll say, this is what this JavaScript does, or this is where you can insert a specific Python, or this is a specific command or PowerShell. Or even if you're looking at something like a loader, it'll be like insert the file here, like the file name here, things like that. So

John Furrier

>> you'll—it's a template.

Selena Larson

>> It's a template. Yeah, it's very much templated. And for the threat actors who are really good at it, it can be fairly effective and it's just sort of making them better. But I think that's fewer than what we're seeing with the adoption of SLOP. And I don't want to say that just because it's sloppy doesn't necessarily mean it's ineffective because we've throughout history seen social engineering that might not be super sophisticated be very effective.

John Furrier

>> if someone's taking one shot at something, they don't really care what it looks like after. It's kind of like the slop factory.

Selena Larson

>> Yes, exactly.

John Furrier

>> Carnage, whatever, bad code laying around. What has it done for— let me ask you this on your research. There's been themes of, hey, the basic blocking and tackling kind of techniques are just getting better and faster. That's kind of a proof point, gotta deal with those with machine speed. But there are new things emerging. What is new? What's emerging that you haven't seen before that AI has enabled? Has it been better coordination? Has it been just new ways, scale, understanding better social engineering combined with other things?

Selena Larson

>> Yeah, so I think scale is a really great one. So historically what we've seen are threat actors will tend to target specific languages, specific geographies, with one campaign, and then maybe a few days later, if they're a threat actor that targets multiple, then they'll switch to a different language. What we've seen in some cases is up to 15 or 16 languages and lure themes that target a broad variety of geographies. It's really carbon copies of each other, but the language changes. And so you can tell that they're using some type of automation, some type of scripting to be able to clone essentially the original lure. But because AI is really good with natural language, they can make it seem a little bit better, whereas historically, if you were trying to clone something into 16 different languages, it probably wouldn't look natural. It wouldn't look legitimate. So things like, for example, Japanese or Korean, the AI has improved those templates quite a bit. And yeah, so we'll see a higher volume in campaigns. The other thing I think that we've seen more of is just experimentation on filtering. So what I mean by that is when a threat actor is trying to send high volumes of URLs, for example, and they're trying to make sure that only you get it. There is a trick that they'll incorporate, either something like geo-filtering, IP filtering, or something like a CAPTCHA where you have to solve a puzzle in order to get the payload. They wanna make sure that it's a real human being that's actually getting this phishing payload and not me in my sandbox getting that. So we've seen a lot of experimentation in that aspect of it.

John Furrier

>> So they figured out the honeypots, they figured out all the little tricks. The

Selena Larson

>> sandboxing.Yeah. So they kind of know how to do some sandbox bypassing. So it'll be like, all right, I'm going to come up with this CAPTCHA that no one's ever seen before. Some sort of weird puzzle or bicycles. No bicycles. Yeah. No more bicycles. No more stoplights.

John Furrier

>> No

Selena Larson

>> more.Yeah. Cars. How many cars is this? But I think I've seen ones that are like little fish emoji and then it's like figure out the strawberry is weird. So it's just weird things like that. So they've changed that up a little bit. And with every new iteration of that, it's on us as defenders to be able to come up with more sort of dynamic detections. And so one thing I think is really cool from our perspective as the defenders is that historically, static detection on IOCs and landing pages and stuff could be pretty effective because they would be used for a prolonged period of time. But now the time of the— or the length of time that static detections are valuable or useful has really decreased because of the rapid iteration and development of the payloads and the attack chains. So it's on us to be really creative. It's like, okay, how can we come up with some really interesting dynamic detections that we can anticipate, okay, we think that they're going to try another type of filtering, so we should create detections for this to preemptively block it, essentially.

John Furrier

>> The intelligence— that's where I think your point about the AI is getting better on the good side is because, there's real-time stuff on the defense. Okay, we know what that is, kill it right away. But then there's the more complex things that look normal, like the mechanisms are all working. There's no malware. Email comes in. Oh, you run accounts payable?

Selena Larson

>> Yeah.

John Furrier

>> Oh, there's all the suppliers on your email. Just email them too. One owes money. So there's all this, kind of like living off the land by accident on purpose. You're like, okay, I'm not living off the land, like hanging around. I actually just discovered all these new people. All I gotta do is get one of them.

Selena Larson

>> Yeah.

John Furrier

>> So there's all these techniques, but that doesn't look like it's breaking anything. So But the psychology of the data was why I'm intrigued by this knowledge graph element, because you might say, oh, John is running accounts payable, he's on vacation, and in Slack he already told the people there's some data. So it's all the context.

Selena Larson

>> Mm-hmm. Mm-hmm.

John Furrier

>> How is that defense helping? Any new ways to pull in the psyops side of it? Yeah. To the defense side.

Selena Larson

>> Yeah. So I think that's one way where AI can be really interesting in terms of behavioral detections. So like you mentioned, I know so-and-so is out of town. Also things like misdirected email. If there is a CC, a BCC, or reply-to that's unusual or outside of the scope of what someone might typically reply to, then you can say, oh wait, this seems out of the ordinary. This seems like, you know, something that we should flag. Are you sure you want to send this email to this individual? Or if you receive it on the recipient side, something like this is a suspect URL or a domain that doesn't have longevity. This is suspicious. So I think things like that can be really effective. And then same thing with looking at data loss and the data loss landscape and the insider risk too, right? Because when you're a threat actor who has done an account takeover and gained access to something, I think detection opportunities are something like malicious apps that might be added to the account itself. So this is something that's suspicious, this is out of the ordinary, this name doesn't align with our existing enterprise applications, this is something that we should investigate. And then also downloading various files trying to exfiltrate that type of data. So, paying attention to where it's going and what authorization and what sort of identities are enabled within accounts.

John Furrier

>> My interest in agents is interesting because agents remind me of when Facebook came out with misinformation. It wasn't the network effect and the graph, it was the content was the payload. And Facebook just wasn't paying attention.

Selena Larson

>> Yeah.

John Furrier

>> So the theme we're hearing now in AI is that we wanna pay attention to the trust.

Selena Larson

>> Yes.

John Furrier

>> The agents will do what they're told.

Selena Larson

>> Yes.

John Furrier

>> So how is agents, 'cause they can be weaponized.

Selena Larson

>> Mm-hmm.

John Furrier

>> Just like Facebook was weaponized for misinformation. That conversation's starting to lurk around in the mainstream now. We're saying, okay, agents are going rogue, but are they really going rogue? And also if they can get weaponized, taken over. Mm-hmm. That's an interesting dynamic. What data are you seeing on the agent front? Because this then brings in the question of, okay, I got the good agents and the bad agents, there's espionage going on. So it's like they're crafting their own civilizations.

Selena Larson

>> Well, that's an interesting way of putting it. I think—

John Furrier

>> Can they form, can agents form as a digital twin of the threat actors?

Selena Larson

>> I think if they are programmed to do so. So I don't necessarily think that we are gonna have some sort of rogue robots like HAL, open the pod bay door, HAL, no. I don't think that that's necessarily coming up in the near future.

John Furrier

>> Are there any threat vectors around agents that kind of give you pause?

Selena Larson

>> Yeah. So one of the more interesting things I think about this is supply chain, for example. So, and I actually just a brief aside, when you mentioned you think about it with Facebook a lot as sort of the original agent, when I first got Facebook, I remember it was posting everything that I listened to on Spotify to Facebook and I was like, wait a second, why is everything that I'm listening to on Spotify automatically being posted to my Facebook page? And people are commenting on it. This is so weird. And that was like, wait a second, I don't have the proper restrictions in place. I just sort of added something to my

John Furrier

>> account.Installed some app,

Selena Larson

>> probably.Yeah. And I didn't necessarily understand how it worked or what it was talking to or what data was going to be shared with, what account was going to be shared with.

John Furrier

>> At least you didn't put a MySpace widget on

Selena Larson

>> there.Oh

John Furrier

>> yeah.Wow. This is the first generation of spam takeover of

Selena Larson

>> Facebook.Yeah. I mean, that's how I learned to code, was MySpace. I'm old school. I got that. So, but that's a really great analogy that you bring up in thinking about Facebook because that's how I think about agents. If we're just installing any sort of agent on our devices without the governance aspect of it and without understanding, what accounts are talking to it, what information is being uploaded, what is this AI doing with this information? Who has access to this information? And I think it's a little bit parallel, draws some parallels with the cloud as well, right? Because it used to be like we're just going to upload everything to the cloud and then guess what that was, the bucket was open. The S3

John Furrier

>> bucket.No one told me about

Selena Larson

>> it.Yeah. Yeah. How many data breaches did we have because of exposed S3

John Furrier

>> buckets?And that's the same thing. No one told me this. So there's kind of rules of the road. So I guess my question is, as you look at the threats, that's just humans got to keep up. So it's kind of like basic blocking and tackling, but also what's net new. Oh, we didn't know

Selena Larson

>> that.Yeah. Well, so I think, going back to this idea of supply chain and that I think is something that's pretty interesting because if you look at essentially maybe agents pushing malicious commits into GitHub, for example, and then having the autonomous development pipeline just automatically accept things without review, that could potentially lead a malicious agent to upload itself essentially into your own network. So if you are just relying on agents to, do this security and do the auditing, and you're just pushing accept on things, because you just trust that it's gonna be secure, I think that that's where we're gonna get into some issues. And we've seen poisoning, like supply chain poisoning in Python packages, for example, or on GitHub, or in various coding repositories. And right now what we're seeing within the enterprise is an automated continuous integration and continuous deployment pipeline. So organizations are just relying on things that are already in open source, are already in these various

John Furrier

>> Git—So the CI/CD pipeline was never really programmed to do software supply chain validation except for

Selena Larson

>> containers.Yes, right. It was something that we're just like, okay, we're

John Furrier

>> just—it's

Selena Larson

>> working.It's

John Furrier

>> working.Not until it doesn't

Selena Larson

>> work.Yeah, yeah, right,

John Furrier

>> right.The threats

Selena Larson

>> here.Yes, exactly. We're doing sprint, we have this, and Oh, wait a second. Now we have potentially rogue AI agents.

John Furrier

>> Yeah, the guy's like, I gotta get my margarita in 10 minutes. Go.

Selena Larson

>> Exactly.

John Furrier

>> And that's human error. That's back to the human piece. That's why I like the Proofpoint's perspective. It seems to be a much deeper thought process around the endpoint relationship to the user.

Selena Larson

>> Mm-hmm.

John Furrier

>> And then the agents on the inside. Well, so there's a whole nother level of two-sided.

Selena Larson

>> Yeah.

John Furrier

>> Human agent relationship.

Selena Larson

>> Yeah, well, and I think one of the great things that I love about Proofpoint and how we've really adopted this and I have embraced it since I've been here— is this human-centered security. And I think that as we're moving to an agent-centered security, there's always going to be the need for the human in the loop. And I think that AI and agents and agentic development and agentic SOCs, for example, security operations that are AI-enabled, what we're doing is effectively just giving the human more power, more tools, more resources.

John Furrier

>> Don't you think, like a manager would have direct reports, that humans should be responsible for agents because it makes sense. Like, wait, what happened? I don't know, an agent got loose. I don't know whose fleet it's from. Selena, that's Selena's agent, not my

Selena Larson

>> agent.Don't point fingers

John Furrier

>> here.That wasn't my agent. So this comes back down to, okay, whose organization? Because if it's work, it's an extension of

Selena Larson

>> work.Yeah,

John Furrier

>> yeah.I almost look at it as you're an operator of agents, a manager of

Selena Larson

>> agents.

John Furrier

>> Yeah.And has to take responsibility.

Selena Larson

>> There does have to be some responsibility because fundamentally our AI is only going to do what people tell it to do. And we don't have AGI right now. We don't have robots that are building themselves. And we're essentially, they're all reliant on the person that's telling them what to do. And we do run into some issues where if you have someone who isn't necessarily trained or knowledgeable about what they're doing, for example, a threat actor creating malware but not knowing how to put their botnet panel behind, secure resources so you can very easily take it down. You have the same thing from a defender perspective. So if you're

John Furrier

>> not—it can get loose without— it's just by accident. I was trying to do this, but everything else happened.

Selena Larson

>> Yeah. So that's why I do think that there are some, really great opportunities for automated governance, automated detection of some of these rogue threats, and making sure that you have these tools and protocols in place that your AI can tell the person, are you sure you want to do that? Or you're going to— this data is going to be sent here. Is this compliant with your Talk about the organizations that have become

John Furrier

>> companies.malware's been out there and ransomware, you can buy ransomware as a service. We've covered that years ago. Are there yet agentic-as-a-service attacks? I'm gonna imagine that's just another extension of as a service on the higher end. What's going on with the big actor, the threat actors? Is there any movement on crushing them and getting—

Selena Larson

>> Crushing them. Yes, we're always crushing them.

John Furrier

>> Well, and we talked about not just give a slap on the wrist, knocking them out completely and arresting them. And that was something that came up.

Selena Larson

>> Yes.

John Furrier

>> Taking them off the streets, literally.

Selena Larson

>> Yes. So there is a lot of efforts and continued efforts on that. For example, one of the efforts that we participated in recently was the disruption of the Tycoon 2FA phishing kit. So it was a multifactor authentication phishing as a service. And we were able to work together with some private-public partners to be able to do that disruption as a civil lawsuit filed by Microsoft and with support of international law enforcement was both an online disruption and it did have some real-world impact with countries actually taking people down. Yeah, it was very exciting.

John Furrier

>> A challenge

Selena Larson

>> coin.Uh, I didn't get a challenge coin. The challenge coin is the friends we made along the

John Furrier

>> way.Yeah, but it's also nice because that's like, you can actually— that's tangible

Selena Larson

>> impact.Yes,

John Furrier

>> absolutely.Just reconstituting another gang or

Selena Larson

>> whatever.Yeah, well, and we're seeing that now with various malware. So you're asking if there's AI as a

John Furrier

>> service.What we are seeing are different threat actors using AI to build services.

Selena Larson

>> So for example, phishing as a service, like I mentioned before, device code phishing as a service is something that is quite popular, and all of the device code threat actors are using AI to build these tools. We also see, for example, ClickFix as a service. I'm not sure if you're familiar with ClickFix, but essentially ClickFix is a technique that threat actors will use to compromise— they'll compromise a website, and then you'll see a little pop-up that says, "Your Windows is out of date. Copy and paste this," like, Windows-R which opens PowerShell and then copy and paste this command and then it'll be up to date. Of course, that's copy pasting and running PowerShell that installs malware and et cetera, et cetera. It's bad. But that was quite popular with a handful of pretty bespoke and sophisticated threat actors. But now what we're seeing is a threat actor cluster that's actually doing that as a service. So threat actors can pay them to be able to use their AI-generated ClickFixes essentially. So they'll be compromising these websites using this actor-created ClickFix. So they are using this automation and tooling that a threat actor is selling. So I'm not sure if we've seen sort of AI agentic solutions in the same way that we're seeing AI-enabled threats be sold and repackaged as a service.

John Furrier

>> It's just so fascinating. There's so much going on and I love the success of the takedown of the organization with the law enforcement and taking them offline with disruption. What I'm noticing is that there's been a real generational shift. We're seeing it at the political level.

Selena Larson

>> Yes.

John Furrier

>> I just don't trust anyone anymore. I don't care which party you're from. Seeing that now play out on the national scale, there's kind of a tech version going on. And I'm a Gen Xer. So we're the last feral generation as described. But I'm old compared to the young guns coming in now. But like, there's a whole mindset of like, there's a whole new way. Are people changing their expectations on how they interface because most people that didn't grow up with the internet, I know what a domain name looks like, so I can tell by the URL, but techniques are so good now that the younger generation are seeing new popups. Is there a trend to go headless and go, I won't say analog, but like minimalistic?

Selena Larson

>> Yeah.

John Furrier

>> No interface. Are you seeing any generational patterns around the consumption side that's safer? Yeah, maybe less functional. And generational shift on the

Selena Larson

>> attackers.That's a great question. You know, I have seen some TikToks from the Zoomers and Gen Alpha that are basically like, I want to go back to the '90s. And they, like, they're, they're like, they're missing the flip phone that they never experienced. I have seen that all over just in my own neighborhood. And I live in Washington, DC. There's a big movement to do like a no-phone detox where you lock up your phone and it's kind of like Dry January. Yeah, exactly. And like live analog But I think that there is some of that because I feel like Gen X and I'm a millennial. So we kind of grew up as internet natives and we never trusted really anything. And if you look at historically looking at the behaviors and who gets defrauded the most, it's usually the older generation. But now you're seeing a lot more young people that didn't have that digital native experience, that transition from—

John Furrier

>> they'll sign up for anything, right?

Selena Larson

>> Yeah. Yeah.

John Furrier

>> Or click on any link.

Selena Larson

>> Yeah. Or on TikTok, they'll be like, oh, I, you know, would you like to be an ambassador? A brand ambassador and here's some free clothes if you send us, you know, $50 or whatever. So for shipping. And so you have this sort of like this generation where they're getting scammed a lot more than I think historically we were able to. And I do think that things like AI, deepfakes, improved social engineering really do play a role in that. And so I think the natural progression of that is for people to push back and say, wait a second, I don't like this. I want to go back to when it was the '90s and you had to call me on my house phone to hang out. So I do

John Furrier

>> see—Meet at 10 o'clock on the corner, actual real

Selena Larson

>> communication.Yeah. In fact, I'm mentoring a teenager and he's like, I actually prefer phone calls. Can we have a phone call as opposed to text or email? And I said, yes, we absolutely

John Furrier

>> can.Of course, you're a podcaster. You're like, I'll talk all day long, like I love yapping. Yeah, it's funny. Podcasters love— I was talking to someone in support that said anyone who likes podcasts like to call support, the support number. So bloggers would all

Selena Larson

>> email.Look, I don't mind waiting on hold, I have to— I do have to say, though, if we're talking about people being frustrated about technology, I've seen so many people be so frustrated with AI support bots and these call centers. It's just, I miss talking to a human. I just want help.

John Furrier

>> We know you're not real. At least be good, not real. Yeah.

Selena Larson

>> Just pretend to be good at this. Yeah. Yeah.

John Furrier

>> So that's right. So what's the coolest thing you've worked on the past year? Were there a couple of things that were either cool you didn't see coming or cool you knew was coming. What were some of the cool things you worked on?

Selena Larson

>> Well, I actually— am I allowed to say something that I didn't actually work on, but my team did? And it was really cool.

John Furrier

>> If it's something cool that people might see and be motivated by.

Selena Larson

>> Yeah, absolutely. So one thing that we have recently published information on is something called the BlueMoon exploit chain. And this was really interesting because my colleagues discovered an attack chain that was used by a variety of Chinese espionage threat actors, and it chained together multiple vulnerabilities in Chrome and Windows. But what was really interesting was, and we're— if we're talking about AI and the use of AI, the actors actually were able to create something called a patch gap zero day. When someone identified a flaw, a legitimate researcher identified a flaw in Chromium, published that information, here's this bug, Chromium and the dev teams were able to sort of fix it and adapt it. But there's a 2-week, 2 to 4-week gap between when something is patched in Chromium and when it's rolled out broadly for everyone on Chrome and using the Chromium build. So between the time that that was reported and the time that it would've been patched, the threat actors were able to create an exploit to use this vulnerability. And while we don't know 100% for sure, we do suspect with fairly high confidence that the threat actors were able to essentially reverse engineer and create with AI this exploit that was related to this post that was actually the bug report for Chrome. So my colleagues named it the BlueMoon exploit chain, very interesting and it was used by Chinese adversaries, but it has since been adopted by more threat

John Furrier

>> actors.So, are they reversing the code or the timing, the clock's ticking, go get it

Selena Larson

>> exploited?Well, it was the actual report. So, these bug reports and open source bug reporting is very, very detailed. And so, you want to be able to say, here's everything I found, here's how to fix it. And they'll say, yep, thank you. And then go ahead and do that. And while it was patched, it was fixed. It does take a little bit of time to sort of roll that out in the patch gap. So, that was actually pretty interesting. And I have to give a shout out to my team for finding

John Furrier

>> that.All right. Nice plug. Yeah. Anything

Selena Larson

>> else?I would say I don't often see interesting AI-developed malware, but there are a couple of recent malware families that we have found that are created by pretty sophisticated malware threat actors that are making loaders a little bit more interesting. So we'll hopefully have more to share on that in the coming weeks.

John Furrier

>> We'll wait to see. Get busy working. So thanks for coming on. Thanks for the great conversation and the insights and commentary. Appreciate it. Thank you so much for having me. John Furrier with theCUBE. We are here at Proofpoint Protect 2026. It's part of the NYSE Wired programming community. Thanks for watching.