Name: Mastercard and Recorded Future: The New Rules of Machine-Speed Defense
Uploaded: 2026-09-17T15:19:24.896Z
Duration: 1 h 4 s
Description: Mastercard and Recorded Future: The New Rules of Machine-Speed Defense

Transcript for "Mastercard and Recorded Future: The New Rules of Machine-Speed Defense": Hi, everyone. Thanks for joining us. I'm John Miller, and I'll be moderating today's conversation. We're talking about something I think every security leader is wrestling with right now. What it actually means to defend a machine speed and why speed alone might not be enough anymore. I'm joined by two people who are deep in this from very different vantage points. Jason Steer, CISO at Core Future, who's living this every day with customers and making real daily risk decisions, and Christian Nohanyan, VP of government affairs and policy at Mastercard, who's been in the room helping shape the frameworks and standards that are gonna be defined what the future looks like in many industries. Now a CISO on a cybersecurity webinar makes sense, along with a VP of government affairs and policy might seem like an unusual pairing at first. Let me explain why this plan unlocks a unique discussion opportunity. The standard frameworks Christian works on reflect the same new threat landscape that Jason and other CISOs are grappling with every day. Christian sees where the landscape is pushing the guidance and that where that guy needs to adapt. Jason has to translate that guidance into decisions and how to actually protect the organization. Both of them, from different seats, are thinking about the same question. What does it mean to move at machine speed And what actually is required to defend the right things? Jason, Christian, thanks for being here. Thank you for having us. So let's go ahead and get into it. In today's landscape, your unknown exposure just became your whole attack surface. AI accelerates attack defenses alike, and machine speed defense is only as good as the intelligence, vulnerability, insight, and prioritization behind it. The industry is talking about defending machine speed, and I wanna take it a bit further and shift the conversation to the intelligence that powers machine speed. Let's start with the emergence emerging standards and frameworks that are being created to reflect this reality. So, Christian, tell us a little bit about how you're involved with standards frameworks and what these standards and frameworks are looking like to address AI. Absolutely. So there's been a lot of work over the last several years, and it's it's happening globally to develop AI security standards frameworks that are designed to provide additional guidance and helpful information to organizations that are trying to adapt and modify and update their security programs to address the changing threat landscape. And what these frameworks are typically trying to do is balance innovation, encouraging organizations to adopt artificial intelligence in particular to enhance their security and resilience programs while also providing those organizations with helpful details about some of the security threats they're going to face. And that could be everything from AI enabled vulnerability discovery and exploitation to AI powered fraud and scams tactics that are evolving. And the way these frameworks typically do that is by providing a common set of security expectations and best practices that organizations can use to measure and evaluate the adequacy of their security programs against the new and unique AI security threats and challenges they're facing, while also empowering organizations with a common language that can enable them to communicate clearly with their broader ecosystems, so their customers, suppliers, and other business partners about what they expect of each other with respect to how their various organizations are securing themselves. A couple of examples of some of these efforts, there's a there's a lot of great work that's been happening recently at the National Institute of Standards and Technology in The United States where NIST has developed a cyber AI profile and that is currently under, development that is designed to be an AI focused supplement to their very influential and well known cybersecurity framework. There's also some really important work that's been done in Singapore over the last several years with the cybersecurity agency. They're developing a set of guidelines on securing AI systems, which was designed, again, to balance that effort of ensuring that organizations are thinking about using artificial intelligence, especially with respect to enhancing their security, but still giving them guidance on how to best secure their use of those systems because of the unique challenges that artificial intelligence presents. Yeah. I think it's a pretty unique opportunity to hear from you and someone that's at the table helping shape these standards and frameworks. What are some of the discussions that you and the group grapple with? Maybe debating behind closed doors. So one of the issues that's being discussed and debated, and and the NIST Cyber AI profile is a good example of it because this has actually been something that they're navigating currently, is something that mirrors an ongoing discussion and debate that's happening in the broader cybersecurity industry and and in cyber policy circles, which is with such an evolving and changing security threat landscape and with how AI is changing the dynamics of what organizations need to be prepared for and how they need to be looking at updating and modifying their security programs to match the changing speed and severity of the threats they're facing. How do organizations prioritize what to focus on, in what order, and so forth? And that can be because they have different types of technology they're using or even just different resources that they have available to dedicate towards the problem. And so in the case of the cyber AI profile, that's an ongoing debate and discussion is, currently, it actually includes a set of recommended priorities in the various sections where it's recommending best practices for security that organizations should be thinking about. The challenge is on the side of supporting the argument for including those priorities, for including a recommendation as to how organizations should think about updating their programs first, second, and third. That that any additional guidance you can provide to organizations, especially those that don't have a lot of resources to dedicate towards these challenges, will be helpful. The argument that we've seen in the debate against including a specific set of recommended priorities for how organizations should adapt their programs is that these types of frameworks and standards frameworks and profiles are designed to be as broadly applicable and broadly useful as possible, applying to as many organizations as possible. They could be in different sectors. Some may be in a critical infrastructure sector. Some may not. Some may be dealing with particular types of sensitive data. Others may be positioned differently. And so the approach of potentially setting up a set of priorities that operates a little bit like a one size fits all approach to how an organization should think about changing their program may not necessarily make these frameworks as useful as they could be if if you left it open for having a little more discretion for how organizations could tackle updating their programs in the context of a changing AI security landscape. So that's one of the debates and discussions that we've been seeing. Yeah. I think that makes a lot of sense. Now, Jason, when you're hearing some of this as a CSO, how how does how does this sound to you? It's, it's a great great question and thought, John, which is, you you know, the standards create that great taxonomy of language and standards that, you know, we should all be aspiring to measure against. But then, you know, I think from a practitioner's perspective is now answering, you know, the the difficult question, which is, you know, what are the risks to my business? And I think this is why intelligence becomes so important because if we read the cyber news or the hacking news any given day, there are thousand different cyber attacks that businesses face potentially, you know, being compromised and taken out by. But every industry, every geography has its own subtleties of attack. So leaning into, you know, what are the real risks to my business becomes the hardest part that you have to lean into, which is, like, what are the likely threats to my industry? What are already the attacks that I'm dealing with? And what what do I need to prepare for that's now coming around the corner that's next. And that's where the agility of being able to spend multiple plates simultaneously, unfortunately, is, you know, preparing for today whilst also preparing for tomorrow. And today, the the horrible no expression, which is still true is, you know, today's battles are not yesterday's, and tomorrow's battles are not today's. So the challenge is always evolving, always improving, and they're balancing your ability to detect, mitigate, and prevent attacks when you have you know, the reality of security tools that you have to invest for two or three years, and you're really hoping and praying that your security tool tools that you've invested in continue to evolve to, you know, meet the security, you know, threats that you're evolving and working with down around as well. So that's the challenge is now how do you remain well informed? How do you remain, you know, nimble and agile to the new emerging threats, say, with your employees, with your tools and your policies and processes? And then the final part is now how do you communicate to that your executive team and your board that actually you know what you're doing and you have a plan, and you know how to get from a to b, whilst doing it diligently within budget, on time, and without causing any major issues or outages or downtimes or data loss incidents simultaneously. So it's, it's not an easy task to thread those needles, but, you know, lots of organizations, despite that, are still doing it very, very well. And, you know, with AI coming around the corner to help defenders, and they have to remain even more optimistic, I think. Right. And we're gonna get into more about some of your recommendations and what you're hearing from others that are doing well. So we'll come back to that a bit. Now, Christian, when we're when you and you talk to your colleagues about, the standards of frameworks for cyber defense, what are some new approaches that are required to address these new AI threat realities? Earlier, we're talking about the same core guidelines and and new NIST work. So can you speak a little bit more about that? So so a good example, and it's actually relevant to the particularly relevant to this conversation in some of in some of the notes Jason was talking about. One of the areas we've seen that is consistently discussed and is emerging as a as a as a common area that organizations are focused on as a best practice and security measure that organizations need to be thinking about implementing to enable them to to meet the speed and the and the and the severity of some of the AI security challenges they're facing is when looking at an intelligence led approach to responding to some of these security challenges. And a number of these frameworks acknowledge that threat intelligence is going to be a key component of building a security program that is capable of matching the challenges that they're facing. It may not be just a question of whether you're using threat intelligence and whether you have it available to you, but whether you're using artificial intelligence and other types of automated techniques and technology to actually improve and enhance the way you're operationalizing your threat intelligence. And so a number of these frameworks, are starting to reflect, and this is also reflected in the discussion, the importance of organizations looking really closely at how they can increase the speed of the way they're using threat intelligence, how they can increase the accuracy of the prior of the prioritization of the alerts and the warnings that they're getting. And so this is consistently showing up as a key component of being able to respond to some of the challenges, and especially with what we've seen out there in terms of some of the the just the volume of, for example, vulnerability information that's out there and and the need to be able to not just know what all the vulnerabilities are, but actually prioritize your response plan to that. That's being reflected and mirrored in a lot of these frameworks and discussions as well as the ability to use a a a nuanced and really enhancing the way we're thinking about operationalizing threat intelligence. Jason, if you're now hearing that these frame standards are incorporating for intelligence and intelligence driven approach, How do you see that as as a CISO and in addressing AI security threats? I I think it's very welcome. I think, you know, for many organizations that are still very early on their intelligence journey, which, you know, I think from my experience, certainly doing this over eight years is they there are many organizations across the world who are still very early. So embedding intelligence is only gonna improve decision making because just every organization is struggling with volume of alerts to to filter and prioritize and respond to which of the relevant ones. But I think, you know, if I'm looking at it more positively, John, is and I think threat intelligence centric security programs have been a thing for a number of years now that we've been talking to our clients about. And bringing intelligence into the center of thinking, planning, preparation, testing, probing has proven to be very effective for organizations that want to invest intelligence into the center of the program. And and, you know, I think if we look at AI and Frontier AI vulnerability testing as just one example is it's just an extension of what we've seen over the last eight, ten years, whether it was an extortion extortion in ransomware five years ago, whether it was the evolution of identity stealers, info stealing malware three years ago, whether it's just credentials being harvested. You know? These are things that have evolved with with intelligence collection capabilities. So anyone who's watching this call is, you know, cyber threats should be evolving along with capabilities of your cyber intelligence feed and capabilities. And, you know, as those criminals adapt and evolve, you know, any intelligence provider should be adapting and evolving with that to to be, you know, side by side matching them for capabilities. Thanks. Yeah. That makes a lot of sense. Now I wanna touch a little bit more on intelligence led approach and and putting one level down on there. So there are these frameworks and policies that are highlighted the need for threat intelligence and an intelligence led program or approach to to move that today's machine speed. Now do these, like, description, do these also address the quality of the threat intelligence use? So I guess which, I suppose, leads to what are the characteristics of of quality for intelligence that that really can move some of these frameworks and and policies and standards forward and make them, very effective? So I think they they do typically address it, and there's two ways that that these security standards frameworks typically address and respond to that question. The first is to specifically address that question. And a good example of that is The United Kingdom's, their National Cybersecurity Center has a cyber assessment framework that actually includes a section that that unpacks threat intelligence and some of the best practices there. And in that section, it actually talks about how important it is not just to have threat intelligence or to have a threat intelligence supplier or threat intelligence feeds that you have available to you, but that it's important for you to actually measure whether that threat intelligence meets your business needs from a threat based and a risk based evaluation, whether it's actually suited and well suited fit for purpose for your business, and that you're evaluating the effectiveness of the threat intelligence you have available to you or that you're using and to ensure that it really is fit for purpose and that it is that right quality that that is useful for your organization. So some standards frameworks address it directly. Some also zoom out a little bit and address it, and many do many approach it from the standpoint of ensuring that you have good governance, that you have third party risk management, and that you have supply chain security expectations for all of your security technology that you're using. So the NIST cybersecurity framework, the NIST cyber AI profile, a number of other, security frameworks as well, HABIC can have sections where the best practices that are recommended include an expectation that organizations will be taking due diligence with respect to the way they're evaluating the security technology that they're using, including the threat intelligence, and that would be included in there. Right? It's threat intelligence that they're using to ensure that it's fit for purpose, and then it's actually helping to secure their organization in the way that they need. So it it it, these frameworks absolutely do address those questions. Jason, do you have a thought on on what some characteristics are of quality for intelligence? I suppose you do at the CCO for the future. Well, yeah, I'm kind of biased, I think, John. So, you know, I'm preaching to the choir here a little bit, but, you know, from you know, talking to organizations around the world is there there are some really important things to to decision making for threat intelligence that enable good outcomes, and I think that that's the important part. Part. What does threat intelligence enable? It it means that my security practitioners and teams, whether it's across vulnerabilities, third party risk, whether it's across, you know, red teaming, whether it's across, you know, desktop teams, firewalls. So, you know, there are some common things to think about, you know, and threat intelligence starts with coverage. You know, how how many places am I collecting intelligence from at any given one time? Because, you know, the more coverage you have, the more likely is you're you're gonna cover and collect information on, let's say, a new Russian cyber cyber story that's being covered in the Russian media today, half an hour ago, or an event happening in Iran, or like a a geographical or geology event yesterday in Nepal. There's no all those different news sources that enable decisions for businesses in what we would call real time. So coverage and collection at fast speed enable information to be brought together for people to assess the impact of that to their business. You know, whether that's credentials, whether that's phishing sites, whether that's new vulnerabilities that haven't yet been disclosed to to NVD, that are being used by criminals. So that that coverage and speed becomes very important. But then it's only good if that information gets to the right people in the right tools. So, you know, for a lot of security organizations, then that means integrating good intelligence into your SIM, into your EDR, into your DNS tools, into your CNET tools, where practitioners can use that information for enrichment of data in the tool. And they can use that enrichment and correlation, you know, to connect the dots, and then, ultimately, they can make a better decision. And, you know, I think analogy I often use is that the lowest common denominator is, you know, you are a SOC analyst with six months experience straight out of doing your a levels in The UK. You know nothing about cybersecurity still, but you're in the SOC. It's 1AM, Monday morning, and you have to make a decision about an alert. Now how do you know that that person is gonna make consistently the right decision with that alert? To escalate it, to close it out, or to say it's benign. No problem. Move on. And then that's the challenge of where where does threat intelligence help is that consistency of decision making and up leveling people who are in the unenviable position of having to make some very difficult decisions every minute of every shift that they work on. And they're never gonna get all of them right. So how do we ensure they make better decisions? So the integration becomes important. And then the final part is the context. How many places have reported on this? Now how many other people have observed this intelligence? How many other people have observed or seen threat actors talking about this vulnerability? So those are some of the aspects. And I and the other the other final part of that is there's there's unique sourcing that maybe lots of CTI vendors have unique sources that are unique to them. Is you know, how do you turn that into good outcomes in your program? Compromised identities, compromised devices. Have I got machines in my infrastructure connecting to known botnet and CTU systems, for example? Those are all good unique data sourcing capabilities that reduce your risk, improve your visibility, and ultimately, they make your business safer. So those are some of the characteristics. I could go on, but for the for for for the sake of brevity, let's not go any deeper down it today. But there are a number of attributes, and I think it would depend on maturity with your organization and know where to start that journey. Yeah. That all makes a lot of sense. And I think that example you made, the one I'm that that really paints a picture that we can all relate to. So let's go ahead and shift some gears now and and move to operationalizing for intelligence, talking about that. Jason, how should security leaders be thinking about these new frameworks or standards that are being adapted to machine speed world and the need for quality intelligence and actually being put into practice today? Can you walk us through, you know, what you've been doing, what you're seeing others doing, what's going on in the world? Well, the the first thing I think of, John, is, you know, what are we actually defending? And I think that that that is the important part is where is the line that we're defending? And, you know, that that depends on the type of business you are. And are you on premises? Are you in the cloud? Are you a full SaaS company? So what is it you're protecting becomes very important to then being able to identify, you know, what are the most critical parts of your business. They what's mission critical, what's business critical to your organization. That that really is where to start because now you know what you're looking for to protect and what are the likely threats that you have to worry about to protect that system. So I think making sure you're practicing and preparing for the right things, but, you know, to get to your point about machine speed, now it's about API integrations. Then we have to have computers able to communicate to other computers so that we don't have humans in the loop. And now I think the Recorded Future, you know, many other vendors are doing a great job of making data and intelligence available available via API. And, you know, I, you know, really think that in the world of frontier AI testing, you know, just in the world of vulnerabilities, for example, is now how do I pipe enriched contextual data to my vulnerability tools? How can I chain my vulnerability tools to my data lake with an MCP server that's got side got threat intelligence alongside all of my computer network data, my firewall data to start creating a view, you know, using AI of saying where are the actual risks where I've got vulnerabilities with sensitive systems, and we've got threat actors exploiting some of these vulnerabilities on the dark web? You know, how do we highlight those clusters of really interesting data that help the teams think about mitigations and risk and patching decisions? Because playing the game whack a mole with patching everything isn't is not the world we live in anymore. And I think that these are some of the examples of how we have to use AI to to work faster, but also to highlight better decision making rather than the continuous game of whack a mole, which we've done for thirty years. And somehow, we've done quite well most of the time, not all the time. But now we have to be much more thoughtful about what to patch and when if and then the reality is for most organizations, you know, for context, the vulnerability patching programs have to go from critical vulnerabilities being patched in seventy two hours to now less than 12. And so difficult trade offs for our businesses all across the world, which is the big trade off, which is what's worse? Having an outage for an hour is up. Now I can't pay with my bank card at the supermarket, or my data gets leaked to a group of teenagers from Scattered Spider who go and publish it after stealing it from a hack. And they eat both are equally unpleasant, but, you know, what's the least worst outcome there? And this is where, you know, you're having to have much more difficult conversations about how do I get the right data to the right tools to make the right decisions in very short time to ensure my executives understand, you know, that short window decision making is getting even shorter now. So I'm gonna stick with you, Jason, on this one. So from what you just explained there, what does effective then look like for that? Say, put that into practice. And now what what should a security leader be looking forward to to show that it's that things are moving the right direction and working? Well, I think there's lots of metrics that we can, you know, look at in a mean time to respond, mean time to detect, how many assets do we have critical vulnerabilities assigned to and linked to still. And those are all good metrics to think about to to try and measure and improve upon. But, I think the hard part is we're we're always only one bit of vulnerability away from an absolute disaster on any given day of the week, any time of the year. And, you know, that's the hard part of then what is the Achilles heel of the Internet this month, this year? That, you know, means that all of those metrics and plans go out the window, sadly. So that doesn't mean we can't not do our job and prepare for that, but equally is there's always gonna be an x factor that takes, you know, everything we've done and puts a huge stake a huge stick in the spoke of our wheels that will disrupt anything and everything anyway. But we depend it depends, John, on where the risk is now, and I think vulnerability is probably biggest talking point run right now because Frontier AI has dominated. Now I was just reading a news article yesterday, You know, Varnopolis is it's got people rightfully nervous and worried, and vulnerability prioritize prioritization is absolutely prime for use of AI right now to streamline and accelerate contextual decision making at executive levels. Actually, I I wanna go now full circle back to to Christian. You've been hearing what Jason's saying here about, you know, what Beckett looks like and different ways of putting the practice. How is this aligning to what's being discussed in the rooms of this frame versus standards? Is this what the is this aligning to the intentions of what you are all building out and planning for in the future? Absolutely. I think and as we discussed a little bit earlier, I think that's absolutely what's what's trying to be reflective as these standards frameworks are developing, especially in the context of intelligence. The emphasis on finding out ways to enhance the delivery and operationalization of threat intelligence to ensure that that prioritization is happening and ensure that organizations are getting access to prioritized information and that it's not just a question of receiving a significant volume threat intelligence that they can't use effectively because there's that recognition that in a universe in which every organization is trying to set itself up to be as well prepared as possible for the AI related security threat they're facing, It is simply not realistic for their security program that they're trying to build to try and consume every alert possible and to consume every piece of threat intelligence. And so these standards frameworks are trying to reflect that both in the way that they reflect the importance of threat intelligence as a response measure to these security threats, but also, as I mentioned a little bit earlier, how organizations think about leveraging increasingly advanced technology, automated techniques, agentic capabilities, and AI in general to just enhance and refine the way that they're using threat intelligence and just security intelligence in general. There's there's so many different challenges that are out there. Vulnerability discovery and exploitation is one, but as as Jason knows, payment fraud intelligence is another place where, you know, common common fraud tactics that that have been around, you know, with us for a long time are now only being accelerated at a rate that is really quite astonishing. And that type of intelligence is also absolutely critical in terms of being able to enable organizations to prioritize what they're focusing on and to enable the delivery and the the use of that information to be effective for them. And these standards frameworks are trying to reflect that. They're trying to reflect that the types of technology you're using to secure yourself, including intelligence, not limited threat to threat intelligence, but every type of technology you're using to secure yourself, whether it's in the identity space, whether it relates to AI agents and your use and monitoring of AI agents, whatever the space is that you're trying to ensure that you have a robust security architecture, you're using increasingly advanced techniques to defend yourself as well, and that includes many, many, many of the things that Jason was mentioning. That's why I think it's a really cool opportunity to have you both speaking on this. What we're hearing both sides and how they're all coming together. We're all we're all trying to deal with this new reality same time, And it's I think this partnership and this group between the framework standards and what he's supposed to deal with, it's all coming together for what's gonna what we're all gonna have to to grapple with and and defend against in the future. So now as we come to the end of this conversation, if we were to leave our audience with maybe one or two takeaways, what would you want them to walk away with and put into action today? So, Christian, I'm gonna start with with you here. Absolutely. So I think with the goal of so many of these security standards frameworks that are developing, especially in the context of securing AI systems, but also just securing your enterprise broadly speaking and and and where AI fits in both from the defensive standpoint, but also in terms of being prepared for AI enabled security threats. One thing I think that, you know, that I think of as a takeaway is it'll be important for organizations to be tracking the development of these guidelines and frameworks because as we saw with so many frameworks before, whether it's the ISO standards, whether it's the NIST cybersecurity framework, these security standards frameworks often become very influential, very important in the the broader industry. They can be critical points that you end up needing to understand how you're measuring your own program and how you're communicating with customers, how they're communicating with you about how they're securing their organization. They could end up being defining components of as of a key aspect of understanding the security of your broader ecosystem. So tracking the development of these frameworks will be essential for organizations because no organization wants to be playing too much catch up in terms of understanding the direction these frameworks are going because that will that will put them in probably not the best position to be well prepared for the direction that the modern security expectations are going, especially in light of of a changing AI security landscape. So I think ensuring that you're tracking the development of these frameworks and ensuring that you're measuring and evaluating where your security program is, in in terms of the direction these these standards frameworks go is going to be important. Jason? Ah, no. I love doing this particular bit, John, because, you know, when I go to hockey or cricket as a parent and I end up talking to other parents about what I do, we always get to the point of, you know, what what is threat intelligence about? And and I think I I I this is great to close on because, you know, good threat intelligence is about, you know, we've got Christopher and Stu Solomon, who who I, you know, spent a lot of time working with over many years ago when they started at Recorded Future. They they had a great interview. And that interview they did when Stew was at Optiv was literally, you know, the essence of good threat intelligence is decision advantage. Does this piece of intelligence in the hands of the right person enable them to make a decision that they would not be able to make without this information. And you know what? That is such a simple, powerful statement that good intelligence enables me to patch a vulnerability. It it means I don't have to patch a vulnerability. It means I do have to reset this device, or I have to clean this phone, or I have to fix this firewall, or I have to go and ship a new card because that that card has been compromised. And that's what good intelligence is about. It's not about gray. It's a black and white yes, no decisions that in a world where we have to make decisions consistently well, we don't have time for ambiguity. We need context. We need speed. And, you know, as we move into the world of machine speed, having that black and white, good, bad, yes, no, enables us to be much quicker at making the right decisions and pausing when we don't have enough context. But and I think I'm very hopeful that, you know, with intelligence and AI systems flowing together nicely, we're gonna be able to take the humans out of the loop on many of these tactical decisions that we're making thousands of every day and enable our teams to focus on moving, you know, shifting left to be able to do much more of the proactive work of, you know, launching for the business. Who are the threat actors targeting targeting our business? How well prepared are we for those threats that we're likely to face from them in the next three to six months? Are our security tools, programs, policies effective at detecting, deterring them? Where are our realistic gaps? Because guess what? Every organization has security deficits. Where are ours? How can we uniquely figure out what are ours so that we can be prepared and ready to defend and they'd be more able to prevent them moving forward? You know, that's where threat intelligence is going. And then using AI, all of that is gonna be possible, I I believe. I think, actually, that's a great place to leave it then. The big idea, really, I would think for the audience to take away here is speed without intelligence just means you're wrong faster. Machine speed defenses table stakes, but it's the intelligence behind it that makes it actually effective. Christian, Jason, thank you both for such a candid conversation, and thank you all for joining us. For more information on threat intelligence, visit recorderfuture.com, where you'll find interactive demos on threat intelligence solutions and other helpful resources to help you defend against threats in this new machine speed world. Thank you for joining us.