Trust, Risk, and the New Threat Landscape | Security Boulevard Ep. 9

Welcome to Security Boulevard, the cybersecurity podcast from The Future Room Group. Each episode explores a variety of topics within cybersecurity and the technologies that drive it. com, our Security Boulevard, YouTube channel, Textron tv, and all of your favorite podcast platforms.

Before we jump into this episode, I'd like to meet our panel for today, starting with my good friend, Fernando. Fernando, it's good to see you again. You've been a busy guy for the last few weeks.

Absolutely. Uh, wonderful to see you, uh, Eric and Manuel. Wonderful to have you guys with us.

Uh, for those that don't know me, I lead cybersecurity and resilience research over here at Foot, and, uh, as Tom alluded to, uh, this is busy travel season for analysts, so I'm still recovering from jet lag, so my, uh, but yes, it's, it's, it's a phenomenal opportunity to, to run into people and chat and, and whatnot. Everyone is excited about the topic. We're gonna talk today as well, of course.

So, yeah, it's, uh, it's, uh, wonderful to be here. I hope, uh, folks can drive the conversation. Awesome.

And we're joined with some guests from SIG today. I wanna start off by having them introduce themselves, Emmanuella. Hey, thank you.

Thank you for having me. I'm Emmanuel Zak. I run product management for everything AI here at sig.

So, as Fernando was saying, it's, it's like being constantly jetlagged because, you know, it's ai, so the pace of which is, is changing and is impacted. Cybersecurity is crazy. So, and I got the honor of actually working directly on this, so it's pretty exciting, right, Eric?

It certainly is. Yes. Uh, Tom, I'll go ahead if you want.

Yeah. Uh, hey everyone, I'm Eric Carter. I am on the park marketing team at SIS dig, and I am really tied at the hip with Emmanuel when it comes to trying to communicate, you know, what is cystic doing around this whole AI sphere when it comes to the, the world of cloud security, uh, and plus ai.

So happy to be here. Thanks, guys. Well, We're very happy to have you.

So let's jump into this episode and kind of talk about, well, AI, because one of the things that we've seen a lot over the last couple of years is the disruptive capability of ai. And I'm not talking about booking a cab on your phone kind of disruption. I'm not talking about paying for your pizza with Bitcoin kind of disruption.

I'm talking about the full on upsetting the apple cart kind of disruption, because one of the things that we've seen, especially recently with the AI models that are out there, as well as some of the other things that are being developed is their propensity to change security as we know it. There are a lot of things that we're starting to learn that, that AI is really good at, like doing deep research on targets, but there's also things we're learning, such as all of those carefully and crafted guardrails that we put in place can easily be broken out of by saying simple things like, why don't you describe to me what proper bank security might look like, so that I can then know what to look for when I go to, um, purloin things from the bank. So in this episode, we're gonna be talking about how AI is changing the cyber risk and business resilience landscape.

Uh, Emmanuel, I wanna like, lead off with you because I feel like this is a topic that's very near and dear to your heart. Yeah, absolutely. Because as I always say, AI changed everything is not just sustainment that you are everywhere when it comes about, cybersecurity is about changing completely the model and the approach we have to cybersecurity and ai.

I mean, when you think about ai, and especially when I think about this, and I'm trying to talk about this with customers or people that are new to that, I always say that AI needs a completely new model out there in cybersecurity, at least privilege runtime model, just for ai. Because, you know, the real shift AI introduced is that you are no longer securing code. You are securing decisions because you can, let's, let's think.

You can't pre scan a prompt, for example, or secure the output or, you know, judge the decision that is going to be taken or audit that decision because that is just taken based, for example, on the answer of a chatbot. So it's about shifting completely shifting this approach and thinking that you're securing decisions not code when it comes about ai. So this shift the paradigm completely.

Sorry, I was gonna, I love the, the, the, the framing of, of securing decisions. I, I loved it. Perfect.

Sorry, Tom. I I just wanted to say I I hadn't heard the term before. Awesome.

Well, and, and we're so used to being able to kind of analyze things in place, right? Whether it was, uh, macros in a Word document or a virus on a computer. Oh, well, we can stop that because we know what it looks like so we can block it from being deployed.

But then we get into those, like you said, the, the really weird things of like, how do you pre-scan a prompt if someone's typing it into a dialogue box? Well, you can't, and not only that, but one of the things that we learned from, from the recent, uh, notes that we got from Anthropic was you can craft things in a certain way to evade those controls, right? Like, I can remember getting demos way, way back in the day where someone would go into the, uh, the comments in the header of a, uh, virus executable that had been decomp compiled and change a couple of the numbers or letters in the comments, and then recompile it.

And the hash value was completely different, and therefore it evaded the system. And that's when we started hearing about heuristics. Uh, if you're old enough to remember antivirus heuristic scanning, uh, now is probably the time that you're gonna be getting your a A RP card in the mail, because that's a long time ago.

But, but that has evolved to now where we're at, where we have thinking software that is capable of kind of doing things on the fly, but it's not really thinking because it will just do what you tell it to do unless there's a rule that says that you're not supposed to, and it doesn't know that you're, if you ask it how to delete a backup if I'm, you know, maybe somebody who's doing a little house cleaning in my tape robot library, or if I'm a nefarious actor who's trying to erase all evidence of my presence in an organization. No, I was just going to jump one thing, and, and, and it's funny because we jumped into this in this conversation as well. When I have, when I talk with, with security executives and others who are trying to make sense of this all, one of the things that I, I find interesting is how are we going to tackle the topic to begin with?

Let's go back to, to what we're describing and, and runtime. But the way that we, we like to frame security conversations to help people understand what kind of problems they're trying to solve. Is it, it's the, the, the, the triad that people refer to as security for ai.

How are we securing how organizations are applying AI capabilities in whatever. That's, that's topic one, right? And, uh, the other is AI for security, right?

How are you using AI capabilities within the security processes that you are running your organization? Topic number three is security from ai, right? Or security against ai, which is okay, even if you do nothing else, you go home and, and you just wanna be quiet, right?

And not touch ai. It doesn't mean that your adversaries are not going to do that. And that's what we're seeing all the time.

I'm sorry to give, to go back to basics a little bit, but that I, I find it interesting to, because I've walked into many conversations when we were expecting one type of AI conversa AI security, and we yet another, right? So that's, I just wanted to frame here. The other thing I, the other thing I like to say is I like to frame the discussion between how we talking about workforce AI versus workload ai and workforce AI is okay, within the scope of a company, how is the company using AI to support us as employees?

Right? So, or, or what are you using as a person? Hey, all of us have, uh, an LLM of choice that we use to, Hey, help me craft this email a little bit better.

Whatever. Right? Fine.

That's one type of of use case. The workload AI is, look, our company is deploying AI within our company. Is deploying something that something is using ai, what do we do about it?

Right? So, sorry to backtrack us a little bit, but I, but I think that, uh, uh, making the distinction about which one we're talking about is a really good first step too. Yeah.

We, we face that, Fernando, because, uh, we are, we are out obviously talking to the market about it, but also people inside of SIG and we always have to clarify, you've come to me and you've said AI security. Now let's add something to that. Is it AI four?

Is it security four? I like the third one. Uh, where I think inherently insisting there are things to protect what you were talking about, which is AI trying to break through the walls, et cetera.

Uh, so that's a, that's a good third one there. When we first started talking about this, I had created a slide just to try and put a visual, and if you remember, rock em sock robots, Tom wa and there's like, I have a red team and a blue team, and these guys are fighting it out. So ev we know that the bad guys have this at their disposal.

We, uh, before we, we came on the air, we were talking about the, the claw and the, the, the issue that was revealed this week, right? And so there's a perfect example, right? So they've got it.

We need to have it as well, um, in order to stay ahead of these things. And somewhere in the midst of all this is a, is also this trust conversation so that we, when we are using it, we can trust it, but there's, so there's a lot of things to, to cover, but um, we're, we're focusing on, on both, especially using AI to try and defend, right? First of all.

But also since we are quite, um, good at and known for Kubernetes security, a lot of these AI environments are being rolled out as cloud native workloads. And, and there's, there's a, there, there where okay, it's, uh, it's something you've got to make sure you are ready to deal with, right? If you haven't, um, been securing your cloud and cloud native environments the right way, you better get on it.

So, Oh, absolutely. And, and, and as a side note, I've been covering cloud and cloud native security for a long time. I'm well aware of, of, of, of Falco and, and, and, and everything that that, that f have done in your, in your spot on, like you, the visibility that we, that, that we need into how runtime is running on those clusters, right?

If, uh, if, if is essential. So Yes, absolutely. And this Fernando goes, sorry, now goes back into what you were saying at the beginning actually, because the point is that right now we are no longer, you know, we are no longer securing something static.

Think like a castle, for example, with firewalls that we were mentioning before, is something that is changing constantly. It's dynamic if think to this like an ecosystem. And that's the thing, because people only think about ai, but the real thing there is that attackers, like we talk from the point of view of defenders and people that works in cybersecurity, but we have the same tools.

We can leverage AI to actually defend against those threats, but they can leverage AI to automate and actually make things faster. Some, I remember it was some couple of months ago, I guess, with a web UI kind of, uh, kind of box that was out there, and you remember that they kind of exposed without name, privilege, uh, this interface. And basically the attackers just created an AI generated Python script as simple as that, to be able to leverage that and start a crypto mining activity.

As simple as that, when you analyze dev code, it was 90% AI generated. And that's the thing we're, you know, we're starting a war with the very same weapon out there, and it's powerful on both sides. Yeah.

So it's, And, and It's there, The thing that I, I help, uh, that I wanna have conversations, the thing that I think helps people understand is what is AI changing, right? And AI, at least talking about security from ai, like what are the attackers doing, right? And we are not yet, like, we're starting to see these more and more.

And, and, and I'm, uh, um, I think that attackers are very, um, uh, very rational when it comes to the economics of attacks. And they will use what's affordable. They'll use what's, they'll use the minimum they need to get the job done, right?

And, and so, uh, I've, I, I've had conversations where people are saying, look, I don't, I, I know AI here, but I don't want to deal with it because I have to deal with so many other things. First, I like to point out that, look, we're not, we, we want you to think about security, security from AI now, not because of the attacks that are happening now, but what is changing coming along, right? You mentioned, you mentioned the Python script, Tom mentioned the, the, the, the, the, the, the report that just came out.

What is common between them? I think that two things we're seeing that it's important for defenders to keep in mind. We're talking about AI enabling more attackers.

So we're giving attackers or AI is giving attackers access to better knowledge, right? So in other words, if I, if I am, I, uh, I'm old enough when we used to call them script kit, right? Uh, uh, uh, now that capability, the capability that somebody can have now is much greater.

That's point number one, right? Point number two is that not only that comes with greater capabilities, but that also comes with much faster speed, right? And I think that if, if as practitioners, we can help teams be ready for what if you are, what if the, what if your attackers are more skilled, and what if your attackers are faster, right?

Those are the two things that, that, that can help frame the conversation. Sorry. Yeah.

Fernando this's, it's a great point, and it's one of the areas where we focus, when we talk about how we are doing AI for security, is you, you do have people who are not as skilled and they need help, right? And it, ai can, can be that helper. Uh, this week I was reading news about, you know, new models and so on, and they talked about these are now PhD level and above kind of intelligence that you're bringing to this.

And I was like, wow. You know, I didn't go to that much school myself, but, um, yeah, I mean, this is it. We need, we need to enable, because you're saying like, you know, they, they're very little effort and knowledge.

They're getting out and doing bad things, and we need to help people with the knowledge to, to combat against that, right? Right. Where they're working and not have to jump out, ask a friend, not have to jump out, try and find an answer somewhere on the internet, right?

Give them the answers they need or give 'em the insights they need, right? Where they're working to stop these threats. And that's need back to the point, uh, Exactly.

Just To clarify, the, the more knowledge and more speed applies to both. I mean, I was talking about attackers data applies as well. Yeah.

Yeah. We want, yeah. Defenders need to be faster and, you know, full stop, right?

And, and how one way to do that is to employ ai, you know, in a, in a helpful way, um, and to, so that everyone can do what they need to do, even if the, uh, super smart guys are not around the shop that day when something happens, right? And the other, the other piece to this, Eric, I guess is also the, the fact, and, and you know this because that keeps coming from customers and users, is not just about, you know, getting the insights you need. It's getting the insights you trust, which is the other big topic with ai, because it's not just about, Fernando used this image at the beginning saying, do we need to distinguish between AI workloads and AI workforce?

Everybody's so worried that AI is going to steal their jobs while AI is actually augmenting what they can achieve. Because it give, it's giving me more knowledge. It's giving me visibility into something that usually will take even days to just understand what is this threat I'm trying to investigate on?

I will get there in second, but can I trust the answer that I'm getting and the trust topic? If I have to think, think back to the last three years. So my life working in, in ai, the trust topic is probably the biggest one always coming up.

Because the thing is, I'm getting, I'm trusting, completely trusting this solution that is telling me we want to be faster. This is the thing you should look at. This is how you should solve this.

These are all the things that are related to this threat that I'm identifying right now. All of different time events, all of the context that is happening out there. It's not, the room is the build on fire.

And this is what you should do, is frustrated. Should I, shall I do that? Actually?

Can I trust doing that? And trust is the real currency of ai. That's the thing.

The clo the, the whole topic of the clothing was they asked kindly. So that's the thing. You, you trust them because it looks like it was a human interaction.

That's the, that's the thing. Who am I trusting? And, and, and it's a phenomenal, sorry, I get excited about this.

It's a phenomenal conversation because in part, we're asking security teams to, to think about this differently. I would argue that this, this discussion of trust get outside of technology, right? Uh, it gets into things like semiotics, right?

Where you're, where you're talking about the, the, the, the meaning of symbols and the meaning of trust, right? What does it mean within, uh, a workflow that we can trust what AI is generating? Now, I I I, I, I, I'm aware of the Rings fan, and every time I talk about ai, I quote the, the scene from the movie where, where, um, uh, Elron is telling, uh, gal, I was there, I was there 3000 years ago.

You're Good. Yeah. Yeah.

Uh, and, and because I was there when we were playing with a, with symbolic AI in the early nineties, right? And, and of course it goes even before that McCarthy in 1960s, right? But, um, but we have been trying to, back then we were trying to do just AI based on, on, on meaning and trust, uh, and, and expert systems.

We are now into this age of, of generative AI with neural networks and, and, and they're amazing, their own right? But perhaps we're, we're, we're gonna see something, uh, we need something different, right? We need a better, a better interpretation of how do we evaluate trust in these systems.

I think you're, you're, you're spot on. And I think agentic and the evolution we are seeing with Agentic AI goes also in that direction. I mean, it's, it's cool from a technology standpoint because of course, you, you are seeing AI being at your service more and more doing things for you rather than just reacting to what you're asking, which is absolutely amazing.

AI is becoming proactive more and more, but are we actually ready, especially in the cybersecurity area for the right use cases to actually make the most out? Uh, I, okay, let's, let's pick on that. Um, where I think that, uh, I, I agree.

What I've seen is that the, we are, as an industry, we are arriving at the point where we are sort of agreeing on what is okay. And some of those things is, uh, uh, some of those is that we need domain knowledge experts yourself, right? To take what you understand of the domain, cmap, cloud native security, what have you, and then find out, okay, what are the rules within this domain that we are going to enforce?

And where are we going to use an agentic capability that's going to use a, um, that's going to use a, a layer of the interaction with the user may very well be at your LLM of choice, right? Whatever model, right? But within it, we rely on your expertise for coding the rules of how that agent is gonna behave, right?

And then the output of that can be exactly, uh, I love your, your, your part. I don't have time to study all this. Give me this, give me that summary.

But even that summary is informed by your domain knowledge of the subject, right? You're not going to say, uh, for a Kubernetes cluster, oh, just reboot the cluster, right? Or, or, or, or, or, okay, just, just kill, uh, q proxy or whatever.

No, it doesn't work, right? Because you know how the system works and that, so it's a phenomenal area where we need, I think we need both. We need people who understand the AI side of things, but we also need to understand the domain that we, that, that, that we're talking about.

I mean, agentic makes the most out of it when it, when it gets in context knowledge, it's even more relevant than in all the other AI stuff. And the thing is that, that in context, knowledge is not just about where I put AI in the product. For example, when people ask me, that's a classical question I always get, why shall I use your assistant inside your product in instead of going to my LLM of choice, whatever it is, and just copy and paste the same question and answer is always the same.

Does that LM knows the context you're acting into. If you ask about these alert or on time events or vulnerability, does it know all of your infrastructure context and what that relates to? No, it doesn't.

So that's exactly a thing. And there's no one other than us as, as people that are, you know, embedding this solution or you as users that know exactly what you're chasing for that can give that context. Without that context, AI is blind.

So that's exactly where we can make, have an impact and make that that change. I always, you know, I always say that AI is, is not a technological challenge, is evolving easier to stay, that's a matter of fact. It's going to evolve.

We will have more that are getting better and better. And even the a GI promise that is still still out there, we'll get there. But the point is, I know the point is that even like that all of this is, is out there, is evolving, and that is true, but the real challenge is a business challenge.

Are you going to adopt that and actually understand if it's valuable for you and having an impact on your business? Or you're just looking at that like a technological thing and want to check a box and say, yes, we are adopting ai? Because that completely changed what you're trying to achieve with that.

To Go back to you, you touch on so many good points. Uh, uh, I think that one of the things that I, um, I keep coming back to is that we, what we observe is over in technology overall, and, and like I, the gray hair comes from being there 3000 years ago, right? The, uh, what I've seen throughout career is that we keep, uh, we security is, is, uh, it's like a K thing, right?

On one hand, we need deep technical knowledge about specific areas and, and, and whatnot. How does eBPF work? How do what, uh, how do, what are timing attacks, uh, uh, or side channel attacks against quantum protocols, whatever, right?

But there's also this, this tying into the business, right? And they keep saying that as security, uh, practitioners, one of the things that we should be doing in this time of AI is this should be the golden age of business process engineering for cybersecurity. We should be helping our, we should, uh, be helping our stakeholders understand what their business processes actually are within those business processes.

Where does AI fit? And there are places where AI fits perfectly. There are places, there are places where AI fits, and there are places where, get this away from us, right?

That AI doesn't fit here. So to your point, it's about understanding not only the technology, but the business side of things. And, and, uh, that's a, uh, that's a conversation that requires growth, that requires you to understand people, process and technology.

I know it's the, the usual, the usual things, but yeah, that's where we're going as an industry. We are getting better. I'm, I, I'm optimistic about all this.

We can debate agi, agi I is a different story, but, uh, let's talk about that one later. Pandora books, uh, yes. Uh, yes, yes.

Yeah. Let's stick with, yes, that's it. So I guess maybe the, to kind of bring it home, I, the question is we have all of these aspects of AI that we need to be keeping track of.

Like we need to understand how we can leverage it, how it can be leveraged against us, what we need to do to keep it secured for our people to use, whether it's for workforce or workloads or things like that. But I guess maybe the question would be, you know, what are some of the things you guys are doing at SIG to kind of advance the technology here? Uh, because one of the things that I love about AI being kind of a great equalizer is that sometimes the best innovations come from places that you wouldn't have expected.

Yeah, indeed. Uh, which is Go ahead, Ika. Yeah, yeah, yeah, yeah.

So, um, one of the things that we've done at Cystic, first of all in the, in the realm of protecting AI is to, and because there's so much concern about something's just popping up, there's data being used to train, what's the security is helping to auto identify where there are AI libraries and packages running in your environment, right? So we've been able to do that so that then we can start to apply the security principles and the things that we do. Fernando, you mentioned CNAP, we are A-C-N-A-P, you know, whether it's posture side or whether it's the threat detection side, right?

So, so there's that. Just trying to give you a spotlight that this AI is in your environment. Did you know it?

Did you not? Well, now, you know, right? So that's, that's the one thing.

Uh, on the other hand, and again, our assistant is something we call TIC started with of the, you know, ask me a question about this thing you're seeing. We talked a minute ago about context, right? So one of the cool things is that it knows what I'm looking at, and that's important.

It knows what I'm looking at and knows what's going on in my environment so that I can ask a question. And it's considering that context. And so we've started to implement that around, whether it's threat detection, I need assistance, right?

Or it's vulnerability management, which is a still a huge, despite all the goodness that we put in to trying to help people prioritize, it's still a problem. And this is where we're trying to leverage AI agents or agent AI to, to do some of that tedious work for our customers. Um, and then as well on the posture side, right?

Just being able to get insights about my environment by asking a simple question. So we're trying to give the, the tooling, and I'll have Emmanuel can expand on that, just that, again, wherever I'm working, I get the right insights and I get recommendations on what to do next. And that's sometimes the hard part.

We really wanna get to a point where you've got the recommendation. You can say, make it so, or trust you got a point where I, it's just doing the thing for you. And if you need to peel back the layers, you can peel back and see what was it that AI considered?

What was it that AI did, right? So that there's that whole visibility aspect as well. I mean, when, when we usually always introduce a cystic agent and what we are doing, a cystic explaining to our customers, you know, prospects, people asking about what we do, saying that we are not substituting what they do today, or just giving a fancy way to do the same thing they could do with the product or just using a, an a, an API with a CLI and whatever we're augmenting what they can do today.

Because if the pain is that I have thousands of vulnerabilities to manage with every single day to deal with, and I have no idea where to start from, that's the pain. I don't want a fencer interface. I want a real help out there to cut through the noise, to prioritize and say, bring me to the action point where you are giving me all of the information I need to take a decision and move on and do what I need to do.

And that thing, I, I mean, I may be biased, of course, as manager, so my baby's always the best baby out there. But the point is that that's what you need to do. Use AI to better serve the need that we have out there in cybersecurity.

And we know that speed is our currency because that's what makes the difference between completely fail and have your infrastructure down and have a business damage out there. And instead being effective and saying, okay, I can go out there and, and be armed with a brace and weapons that may attacker said, we, We really wanna, That's exactly where we're, We wanna flip the script, so to speak. Like today, when an alert fires, we get into action and we start investigating, we try and figure out what's the impact or potential impact, and then we figure out what's the solution.

And all of that takes time. You know what, if you get right in the alert happens, yes, I still get notified and everything I need to know how to deal with that issue is right in front of me. And again, when I get to a level of trust, I say, okay, thank you, AI engine, we've done it, we're gonna do it.

Go do it. Right? And then, then I can go see all of the impact, all of the, uh, forensics of what was leading up to this, but I've taken action in, in really, uh, seconds or minutes instead of having to go through that long chain.

And that's some, that's the promise of, of AI and AI agents that will go out and do things for you. Well, it sounds like there's a lot that we're gonna need to consider as we think through this whole process. Uh, there's a lot of aspects that we need to have control over, and one of the things that I know about AI is we're probably going to be rethinking this problem in six months when some new capabilities come out or some new thing that we need to worry about is happening.

But the good news is, is that no matter what happens, we're gonna keep you up to date here on Security Boulevard. Uh, Fernando, uh, you just had a report came out that, uh, I think people want to tune into. Uh, it was, uh, one of the new signals, Yes, we just, we just published a security operations platform, uh, report, um, where, so TU is a, uh, we call ourselves an AI native analyst firm, and we are very much, uh, looking into where do we deploy it in a way that makes sense and, and, and so on.

And, uh, this type of signal reports, they, um, they're looking into this broader notion of security operations platform. And then from there, where, uh, where should people go? It's, it's, it's supposed to, it's, it's, it's aimed at helping people understand this, this fusion of, of, we have analytics, we have controls, we have ai, where are things going?

So that was just published, uh, uh, uh, group com, track signal, it, it's relatively easy defined, right? And, um, and yeah, it's been, um, it's been a, a, a, a very interesting experience. I'm, I'm, uh, I'm, I'm starting to work on the next one now, right?

So the, these are, that's one of the things that for us is interesting because we can, we can, uh, work on them in a much faster pace. So this will, uh, this will be fun, right? Alright, And, uh, our guests from, uh, cystic, if you, uh, you've talked a lot about some of the cystic platforms and products that you, you worked on and that people, uh, should be checking out if they want to do that.

Where can they go to learn a little bit more? Just, man, I was waiting for the marketing guy to speak up. com from the very get go, you'll get the flavor of, of what we do and can lead off from there to, to dive deep.

We have a lot of interesting and good, uh, uh, articles about technology. Even, even if it's not a cystic thing, just like you wanna learn about really what is agent ai, we've got something that will help you and put that in the context of cloud security. Alright?

com. One thing that I think you're gonna be excited about, though, we're gonna be at RSA this year. First time we're doing Tech Field Day Extra at RSA, we've got a couple of companies that are already lined up and ready to talk about it.

And guess what? We still got four more months before we get there. So I bet you we'll have a couple more before all things are said and done.

com for more information about that as well as security Field A and all the other things that we've got coming up. We wanna thank you all for listening to this episode of the Security Boulevard podcast. If you enjoyed our conversation, please make sure that you subscribe on YouTube or in your favorite podcast application choice.

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