#328 Kevin Tian: Exploring Doppel's AI-Native Social Engineering Defense Platform

23:17And so that's something that, you know, is a key program that we invest a lot in. But it is scary, right? Like if someone, you know, let's say they weren't even going to use Doppel. Like the reality is like people can use AI agents in general, right? Try to go, especially if I'm a bad guy, hey, I just need an AI agent to focus on my specific use case. They could easily do a lot, a lot of malicious stuff with these AI agents, right? Spend up a thousand AI agents to phone call a, you know, a customer support center and, you know, DDoS it essentially, right? And it's very scary stuff. And again, it's, that's why the mission is so important.

23:54And it's the realization that, yeah, AI could really destroy a lot of things right now if you are a really motivated bad guy.

24:01Kevin Tian:Yeah. So we're entering a world where digital identity can no longer be assumed authentic. Right. From the, you know, Doppler then protects someone, protects their real identity from deepfakes. But is there something that individuals can do to ensure the authenticity of what they're looking at? Right. I mean, there's there's a lot of like tactical things that I think individuals can do that don't require, you know, technology, things like that. Like, for example, Craig, how would you verify that I'm a deep fake writer not right now on this podcast? Or how would I help verify that you're real or not?

24:41Right. And so a couple of the like tactics that I've learned from, you know, just chatting with security customers, like you could ask, like I could ask you, Craig, to put up your phone and then with your phone, you know, show the selfie view. Right. So like if you're deep faking through this software, you're not necessarily going to deep fake on, you know, the camera view. You know, I could ask you, you know, about some random topics. Right. And see if you've got pre-Can AI answers. Like, you know, we could chat about the Cowboys in Texas and, you know, see if you pick up on the Dallas Cowboys or if you just start talking generically about Cowboys in Texas.

25:15Right. And or even ask you about fictional places that AI models may have been trained upon. You know, see if your kids are enjoying a Hogwarts or not after college. And and so that's, you know, those are just some of the, you know, individual tactics that I've heard from security practitioners. I think the other reality is like, it's important because the attacks are multi-channel, right? They may be hitting you the fake email. They may be hitting you the fake phone call. The key is then the defense has to be multi-channel as well. And obviously that's reflected in our product architecture. But even again, technology aside, what that means is, hey, let me call Craig's known number to verify that this is Craig, right?

25:51And let me, you know, maybe also message Craig on LinkedIn, right? And so it's one thing for me to go impersonate across LinkedIn or a phone channel or a video channel, but it's really, it's harder to do it across all the different channels. And of course, if you pull that off, that's what makes the attack so scary. And that's what we combat, but it is important to have out of band verification channels so that, you know, if, if credit got compromised in one area, uh, you, you could, uh, you know, suss it out from another channel.

26:20Kevin Tian:Yeah. I mean, ultimately what's eroding here, it's not the individual attack, It's trust in general. Right. And trust in digital digital media. Right. How? Yeah. Talk about that. I mean, you know, most organizations are relying on security awareness training. But from the consumer's point of view, where do you think how damaged do you think societal trust will become? Right. Well, we can we can already start quantifying it right in the sense that we're seeing consumers lose tens of billions, if not hundreds of billions of dollars today to things around fraud and phishing and social engineering.

27:06So that's one way to look at the problem and put a number to it. Second is, yeah, I mean, I think like, again, just even numbers aside, just anecdotally, right, hearing the stories like yours, Craig, around, you know, your YouTube experience, right, or mine about just some of the disinformation campaigns that are happening about layoffs, for example, in the tech industry. It's a very real threat. And the reality is that it's also just getting started as well. Like over the past three or six months, we've seen it ourselves, how much better the AI models have gotten at deepfake phone calls, right?

27:41Like I think everyone's probably seen deepfakes for a couple years now. But in the past six months, it's not just scripted deepfakes. It's interactive deepfakes now that are very good. So I don't have to, you know, hop on a call and get a deepfake mask put on. But I'm still the one who's the brains behind it speaking and thinking. I can now, like we actually have team simulation capabilities where, you know, a team's call can get generated and it's not a person behind it at all, but it's an AI agent who's thinking, responding, has natural pauses and ums and, you know, acts like a human. And that's what is really scary is that AI keeps getting better at that.

28:18Kevin Tian:Yeah. What is human risk management? So human risk management is a category recognized by security analysts. Um, but we think about it as a very broad, uh, platform capability from the double side. So it's, you know, traditionally there's been security awareness training and that's a huge part of human risk management, right? Like, Hey, if I'm going to reduce human risk, I really need to train my workforce against, but we go beyond that in the sense, like there's other capabilities such as like real time interventions to prevent folks from, you know, maybe sharing that, uh, sharing that, uh, Google doc or that office 365 document, right.

28:54With the, with the whole world. Um, and then also we think a lot about the red teaming side as well, where it's like, if you're going to manage human risk and really reduce it, your job isn't just to train your job isn't just to do these real time interventions, but your job is to really, uh, pen test your whole human program. Right. And understand where the gaps are. Like maybe, maybe we've got some significant gaps with our workforce and, um, offshore locations, right. Uh, maybe we've got some significant insider risk where, you know, there are folks that, that can be bribed, right? like if I want to get access to your YouTube account, Craig, my best bet is probably to go bribe someone on the YouTube customer support side.

29:30And so that's what we mean by human risk management is how do you holistically evaluate all the different risks that are opposed to the humans on your side of the organization, train against that risk, test against that risk with red teaming, and then put in proactive interventions.

29:45Kevin Tian:Yeah. And in your company, that must be a never ending process. Yeah. And it's a never ending process. And you'll actually see us launch some more products this year as well to add more real time intervention capabilities. And that's really the power of the social engineering defense platform, right? It's like we're the first platform that enables you to, you know, there are products out there that enable you to do the individual pieces, but there's no product out there that enables you to do, hey, we can find these attacks. We can take them down. We could do real-time interventions now. You're going to see more and more of those products this year.

30:22And then we can really train and test against these attacks as well.

30:26Kevin Tian:Yeah. And how do you initiate an attack? I mean, what does an AI native defense actually look like in practice? Yeah, the AI native defense in practice is, I mean, we chatted about our two agenta capabilities, right? The agent that enables you to analyze all these attacks and shut them down in real time. time um that's critical because if you're just throwing the bodies at the problem right you're not going to keep up with the AI threat uh second is the AI agent that enables you to simulate and test against these attacks as well um so you know essentially the defensive agent and the offensive agent right and that offensive agent um it has the ability you know if you've seen like the whole craze around open claw and uh how AI agents now can interact with the rest of the world through any digital means like that's what the offensive agent can do it can do texts it could do phone calls.

31:16It can go, you know, do phishing emails, create fake websites. And that's a real, real scary capability of AI.

31:24Kevin Tian:Yeah. But for you guys, when you are simulating an attack, how do you make it as close to a real world attack as possible? That's a great question. And that's a big reason why this platform has developed. It's like our first product started off on the threat intelligence side, right? And the executive VIP protection side and the brand protection side of the digital risk protection side. So we're seeing these attacks happen in real time for all of our customers. We're shutting them down in real time for all our customers. But because we know how the bad guys are pretending to be you, Craig, that means we can then make our simulation very, very, you know, real world scenario as a result, because we actually are the ones also protecting against these attacks.

32:09Kevin Tian:Yeah. And where is this going? I mean, as I say, it's, it's, people have been seeing it coming for a long time. It's now hitting, it hasn't yet hit in a way that is causing mass confusion, but we've got elections coming up. Yeah. And there's a lot of concern about that. Where do you think this is going in the next three to five years? Yeah. So So we actually got to work with the elections on both sides of the aisle, of course, in 2024. So we work with this nonprofit, nonpartisan organization called Defending Digital Campaigns. And, you know, just from that one time experience, we already kind of got a sneak preview of a lot of different things that were going on.

32:50Everything from, you know, what we suspect was AI generated campaigns and ways to like pull people into certain content and certain social media groups. and then it suddenly pivots right in the messaging. We've seen fake organizations get spun up and those get linked to certain individuals. So you're talking about the next three to five years and at least within the US, a major, major election cycle in 2028. Yeah, I mean, it's definitely something that we're apprehensive about and thinking a lot about in terms of how to help protect. I think the biggest thing is from, at least from what we could control on the doppel side And this is what informs our product roadmap is, hey, we got to have integrations with as many channels as possible, give you as much visibility as possible, real-time defense as possible, inline solutions, and then also proactive threat hunting solutions.

33:43So it's really about, hey, how do we enable you to get the full view of the problem and then also the full capability to stop it?

33:51Kevin Tian:And do you think enterprises are waking up to this threat? Or what would you advise enterprise leaders, CEOs and CTOs to think about in the next five years? I would say yes. And it's certainly a big part of our growth here at Doppel and why we are one of the fast growing cybersecurity companies in the world now is that at the board level, at the C level, we're talking about AI transformation. We're talking about deep fakes. We're talking about these bad guys like Shiny Hunters and Scattered Spider and social engineering. We're chatting a lot about executive and VIP protection, especially after a lot of public incidents over the past 12 to 18 months.

34:35Kevin Tian:So that's certainly happening. And my message to large enterprise C-levels and really any business out there is that this is the problem to solve for on the AI side and the security side. Again, when we started this company, we didn't even necessarily start this as a security company. We started this as an AI company. And it's with the vision that, hey, this is really the problem solved with AI. And when it gets to the point now where you can deep fake anything, anyone, and do it at scale and in real time, things get really scary. And our commitment, of course, to these folks is that we're going to continue to build more and more to give them more and more capabilities to stop that.

35:16Yeah.

35:17Kevin Tian:And do you have a use case? You don't have to name the person or the company that was being targeted. And, you know, you were able to, are you able in these cases to completely solve the deep fake misinformation problem? Or do you get like 97 % but there's still going to be stuff that you can't stop? Right. I mean, I think in the game of risk, right? Well, I shouldn't actually call it the game, but in the framework of risk, right? And that's really what a lot of us think about on the security side. There are attacks that we totally shut down and totally mitigate, right? At the same time, will we ever say that risk is 100 % prevented all the time, every time, right?

36:05I don't think anybody can claim that any vendor, any company, the reality is it's an adversarial it's an adversarial industry, right? Where as you build more defense capabilities, the bad guy is building more offensive capabilities. And so it's a rat race. So I'll give you a specific case study around, you know, an attack we really shut down. We saw a case where people had spun up a fake LinkedIn account pretending to be part of an organization. And we actually saw a phishing email come through from that person. But we took that email address. We found the LinkedIn account in this tattoo. we found all the adjacent LinkedIn accounts that are connected to that LinkedIn account, their email addresses, their telephone numbers, right?

36:46And so we saw this whole attack happening in real time with that threat graph. And then we shut it all down, right? Like you actually would see the LinkedIn accounts disappear just within hours. The telephone numbers and emails also getting shut down quickly. And so that's an example of a case where, hey, we were able to shut down an attack that was targeting their offshore operations and do it before any real damage was done.

37:09Kevin Tian:Yeah. And are the platforms like LinkedIn, YouTube, X, are they cooperative when you want to take something down? That's a great question. So a lot of our work on the doppel side is to build relationships. These platforms, right, become trusted reporters, get access to APIs, hotlines. And so the quick answer there is yes, in the sense that like, because we've been able to develop that reputation and earn that trust as a trust reporter. That's how we're able to effectively coordinate and partner with a lot of these organizations. I do think that without those relationships, right, it is harder.

37:48It's slower, it's less successful. And again, that's the reality of a lot of the work that we do day to day is to build those relationships and earn the trust reporter status.

37:58Kevin Tian:Yeah. Is scale a problem? I mean, if these attacks are being done at scale, I mean, not just a few discrete deep fakes on YouTube or Twitter, but if they're flooding the zone, do you have the capacity to head that off? Right. It's a huge problem. And we talk about like there's, you know, there's just increased volume when it comes to AI. Right. A lot of folks debate, hey, does AI really bring new attacks or it's just more of the same stuff? And I think at a certain point it becomes semantics. Like there's no question it just increases volume. There's no question it increases the velocity of these attacks and how quickly they could be spun up.

38:40There's no question that, you know, the kind of the bride and the fidelity of these attacks are also really, really high. You know, that's why we give it a three Vs framework. And so in order to have the capacity to combat them, you also need to be using AI, right? AI to fight AI. And that's why the AI agents we've built are so critical. Like you could, for example, test your team by manually calling into every employee and every customer support line and every help desk line, but it's just not scalable. And you can manually have security analysts look at every single impersonation alert and try to take it down.

39:14But again, it's just not scalable. So how do you actually deploy AI effectively to build up your own capacity? That's a business critical mission critical problem to solve.

39:24Kevin Tian:And do you think that you'll grow or your industry segment will grow to the point that it'll keep ahead of the misinformation and deepfake and prevent it from eroding societal trust? Or do you think that we'll never get ahead of it? It'll be kind of like cybersecurity has been all along, whack-a-mole, cat-and-mouse game. well our job is to make it not whack-a-mole but to be how do we be strategic and proactive um you know that is our mission right is to solve this problem i think uh the mission is never ending in a sense like yeah it's not again because it is an adversarial cat and mouse game you know even if we get to level x right then the bad guy just will focus in on getting to level y um but i so i'll say this is absolutely our mission to solve this problem um i i strongly believe that we're already doing things and we are already building things that give our our clients a significant leg up um and then it's our continuous investment in that platform that enables us to stay ahead yeah why don't the various platforms i mean why don't you sell to them directly or why don't they develop uh this kind of technology so that the stuff never appears or if it appears it's only up for a couple of minutes so i do think the platforms do invest a lot in this space already um you know to varying degrees of success of course like the reality is like there's certainly a lot getting through but i do believe that a lot of these platforms are investing in trust safety teams, integrity solutions, things like that.

41:12We have an advantage where our business model is different. We don't make money off ads. We don't make money off views, things like that. And then also because of our business model, we get to learn what ground truth is from every company in the world. And so that's always a challenge. If you're one of these big social media platforms, you operate with billions of users. How do you know what's real, what's not? Well, our business model is based off working with each individual organization, which means then we know the ground truth for every individual organization. And that scales up the more customers we sign up, the more ground truth data we have, the more revenue we have.

41:50So I think that's it as we have. And then to answer kind of the last question there is like, well, why don't we sell directly to the platforms? It's for those reasons aforementioned, right? One is like, there is actually a real technology and business model advantage when you're selling directly to the individual organizations, it's, it's, it scales up the ground truth better. Um, second, we have tried, uh, exploring selling to the platforms and what ends up happening is that they all have very unique and customized, uh, requirements just because like, yeah, if you're working with YouTube, right.

42:24That looks different than LinkedIn. That looks different than Facebook in terms of the data models. And, you know, the, even, even, you know, even the, even the people organization structures, right? Things like that. And so we found it's not a very repeatable product for ourselves. So we think this is the most efficient way for us to partner with them is to be that trusted reporter, work directly with the organizations getting infected. So we collect that ground truth and basically augment what they're already investing in. Yeah.

42:54Kevin Tian:Do you think that eventually this problem will go away because the detection and intervention strategies will improve to the point that you just can't get a deep fake onto a social media platform? Right. It's a great question. You know, I'd love to get to that point, right, of not having to, you know, need to monitor those specific platforms. but the reality is like even if that were the case right let's say even if they were impossible to manipulate a particular platform what we do see the bad guys do is they then go pivot to a different platform and and so we've we've seen that for example with our own defense capabilities like we've we so successfully shut down an attack that we saw the bad guys complaining about it on telegram like hey you know this this technique is not effective at all double keep shutting it down um but then you know what they did is like all right we're gonna do a totally different platform we're gonna just focus on a totally different platform totally different organization that doesn't have doppel um and so that's you know I think that's just the reality of it it's like again the bad guys are always evolving as well um it is an adversarial uh back and forth and um and our job though is to make it really really hard for them make it really expensive for them and discourage them from ever doing it again.

44:20Kevin Tian:Yeah. And how do you guys work with customers or enterprises? Is it a subscription and, you know, you turn it on and then Apple takes care of sort of monitoring all the various channels and the enterprise doesn't have to worry about it? Yeah, it is a subscription. And really this offers out for any listener, right? We could turn it on in the span of 24, 48 hours for anyone really like, Hey, you know, if StreamYard needed, was curious, right. We could immediately turn on that protection, show them what's out there and show them what's already being taken down. And then, yeah, that's, you know, a lot of the value that we add, right.

45:02It's like that peace of mind that you've got this capability across all these areas, you know, we're a full white glove partner as well. For example, we will work closely with, you know, our customer security teams to tune policies, to tune, you know, automatic capabilities to their specific business environment. And that's a lot of, you know, ultimately what we sell, right? Is that peace of mind, that white glove service and that partnership, right? So that when the bad guys do evolve and we have to go build something new, we're making it happen.

45:34Kevin Tian:Yeah. Is it affordable for individuals or is this really an enterprise grade product we're working on um in an individual products well like it's it's today still through enterprises how we protect individuals so for example um you know if ion were to protect correct right then like ions help and cover that um so we're gonna work on um some individual solutions that will come out um but as of today you know we we work with a lot of different organizations of different sizes of different scale and it's it's really that holistic solution right and we work with athletes, we work with politicians, we work with, you know, folks in the entertainment industry, right?

46:14And it's all part of the same platform.

46:17Kevin Tian:Yeah. You know, big companies like, you know, any big, big, particularly consumer brands, having insurance against reputational damage. Do you work with insurance companies? It seems to me that insurance companies might require yeah yeah so definitely from a go-to-market perspective always happy to partner right so insurance companies or credit card companies or you know a lot of different ways that um you know folks consume our products so uh that's definitely always um a creative option yeah but do you think as this deep fake uh ecosystem expands do you think it'll get to the point where any responsible ceo will ensure that they have somebody like Doppel protecting their brand or their personnel out on social media channels?

47:15I'd say yes. Yeah, yeah.

47:17Kevin Tian:I mean, I'm surprised. As I say, I'm starting to see public figures selling stuff, and it's obviously deep fakes. And what is, like, YouTube's policy? Do they you were saying that a lot of the business from your point of view is building relationships so they trust you. And when you guys contact them to take something down, it gets done. But are they generally eager to take this stuff down? I mean, I certainly can't speak directly to YouTube specific policies, but I would say in general, though, like, you know, the partners we work with are very willing partners. The reason why they built these programs is because they want to consume this intelligence.

48:05They want to shut down these campaigns. And I think a lot of the efforts by these trust and safety and integrity and security teams is to help protect the world from these attacks.