LLMjacking: How hackers steal your AI API keys and stick you with the bill Transcript, AI Summary & Key Points

00:00 Threat actors are after your AI API keys. How worried should we be? >> I think if you have API keys, you should be somewhat worried. >> I think it's now opportunity for threat actors to use API keys to basically exploit and also to create resources. Therefore, you have to be worried and to protect. >> depending on how you're using these APIs and what you're doing with them, you could be up to very worried.

00:30 >> Hello and welcome to Security Intelligence, IBM's weekly cybersecurity podcast where our expert panelists turn the biggest industry news stories into practical takeaways you can use. I'm your host Matt Kuzinski and joining me this week we've got Michelle Alvarez, manager X-Force strategic threat analysis, and two newbies making their debut on the podcast.

00:49 It's Erblin Marrëna, X-Force principal incident response consultant, and Patrick Faucette, X-Force Red adversary services lead. Thanks for joining me today, folks. We're going to be talking about how AI is changing the world of adversary simulation and whether we can patch fast enough to keep up with Mythos and GPT-5.4 cyber, but first I want to keep talking about LLM jacking.

01:18 Now, this is a relatively new attack where threat actors steal AI API keys and other credentials to gain access to a user's or an organization's AI tools. Unlike other attacks, however, they're not really after sensitive data. They just want to use your AI for their purposes because AI costs money and they'd rather stick you with the bill. And here's the thing, those bills can get pretty huge depending on what hackers are doing.

01:42 A developer from a small startup in Mexico shared a story on Reddit about how thieves racked up $82,000 in 48 hours using their stolen Gemini key. To put that in perspective, the dev said that their normal monthly spend was $180, right? So, from $180 a month to 82,000 in 48 hours, pretty significant. Urblin, I want to start with you because you brought this to my attention.

02:06 I was hoping you could I you could give us your initial reactions to LLM jacking. Why did this catch your eye? What has got you thinking about? How do you feel? >> It's definitely something very interesting because I think we have to set up and also just analyze the the evolution of of hijacking. So, for example, we have seen early 2000s, you see more hacker resources for useless sabotage or just just to use this command and control.

02:30 Then, with evolving of cryptocurrencies, you saw that it's profitable for threat actors basically to mine on your devices, especially cloud, with high GPUs, which basically would would make them to profit and use the money for for their operation. But, now we are seeing evolving because now you have opportunity to use cloud for mining because it's free, it's on top of someone else's cloud account or or on top of their their their bill.

02:58 And now it's opportunity to to make money, but in the same time as well to use the API to basically to do R&D, to do research, to build weapons. So, it's I would say it's it's evolution, and you see threat actors are actually winning because they are building and they are meeting their objectives that are planning. The other sides, the bill is basically and cloud providers are are getting the bill.

03:26 And the problem is the end user. Now, you have basically struggle, and imagine this, for example, 100K bill, it's sometimes equal with with a bankruptcy, and it's not just about the money itself, it's about also the leakage of data, it's about the exposure. But, in the the the last side uses is catastrophic in this case. Therefore, something that I think we have to be more worried than we have to make sure that you are getting the direction to raise this topic in community and to start to talk about more and even

03:57 though there are some some discussion, there are some minor techniques, but it's really any type of attack that last I've used catastrophic which in the end of the day has to be more considered and to take it more serious. >> Absolutely. And I like that you point out that this is not just kind of a way for them to to get in there and stick you with a big bill.

04:17 It's also a way for for people with less than good intentions to get access to some of these tools that they wouldn't otherwise have, right? Like we've seen recently that the the Frontier labs are really trying to lock down who can get access to their tools, but if I steal someone's legitimate API key, I can get in there and use it for my own malicious purposes and I never had to get my own credentials.

04:38 So, I think that's an aspect of this that I personally was not even thinking about. mostly just shocked by that massive price tag, but that's significant. So, Michelle, I want to pivot to you here and and I want to ask you about something that uh he did a write-up about this. Uh one of his top recommendations was to treat AI API keys like the crown jewels.

04:59 But I want to know what exactly does that mean? Can I get your take on on on securing AI API keys, what we need to be doing here? What are you thinking about? >> Yes, so I mean, it's just like your password, right? It's something that should be treated as super secret. Uh there's no difference there and I think also something else that I honed in on uh is something in the Reddit post about the 80,000 something dollars that was charged.

05:26 The question was, you know, there's no guardrails. What's going on here? How come I I didn't know about this anomaly until it was too late. And I think, you know, unfortunately in cybersecurity, it takes a major security event like this for uh individuals and organizations to start recognizing that something needs to be done. We saw this with credit card companies, right?

05:49 Now, I get notified if there's something strange going on and I can say no, that wasn't me. Um you know, that charged, you know, several hundred dollars to purchase something in a state or country I I'm not in currently. So, now there's guardrails in place and so I think that's what is going to happen here with this particular incident. >> I think it's a very good point that you bring up, right?

06:09 That sometimes it kind of takes events like this for us to see these blind spots, right? And and you also point out one of the things that's very interesting about these attacks is that people report that even when they have like usage limits or spending caps on their accounts, sometimes the hackers move so fast that they blow through those limits before the the the services can even detect that there's been something wrong, right?

06:28 So, this is in a in a way, it's almost I want to say positive, but the silver lining here is, okay, we've identified a gap in our guardrails. Now, let's work on that. Patrick, I'd love to get your takes, especially as somebody who does adversary simulation, who looks at things from an attacker's perspective. What are your thoughts on these kinds of attacks and what we should be doing to protect ourselves?

06:48 >> Certainly one of those things that you could think a lot about, but anytime you think about any authentication material and API keys obviously a a great example of one of those. It's always I always like to put it in context. So, I like to ask the question, well, what does this get me as the attacker? What can I achieve with that? And obviously we've touched on that a little bit talking about, you know, cost overruns and you know, abusing these models to maybe achieve some sort of offensive tooling or something

07:13 along the those lines. Which is is very interesting, but you know, often API keys are intended to be built in or part of some larger development process. So, you know, is this is this API key being used for for something else or is it just being able to call directly to a model and get some output, in which case it's not the most interesting thing, but if it's part of a larger application flow, you may be able to disclose other data or gain access to other underlying systems.

07:36 So, I think it's all about understanding what is the key for, what does it do, and what what does it get me access to that could further my goals as an attacker? >> I think it's a really good point. Right, like you said, these things are baked into these complex software supply chains. You don't know what this API is connecting to and as an attacker, you know, you can get in there and like you said, if it's connected to the right kinds of things, you can get some access to some really juicy stuff.

07:57 Um Errol Lloyd, I want to uh circle back around to you to kind of close out our discussion here today about LLM jacking. You know, what is the one piece of security advice you would give any user, organization, whatever when it comes to protecting their AI API keys right now today. What should they be doing? >> I think like also seeing from the incident response cases, I think there is a gap on the knowledge on cloud, first of all, and also it's a bigger gap on between cloud security and DevOps data pipelines.

08:27 I think the most important part is to have a proper uh knowledge, education, security testings, multi-layers of of of of defense in this case. And the most important part is that I want to highlight that uh you need to have a proper uh control with all parts of cloud. For example, in control plane, in in the data plane in this case. But the most important part which I want to highlight especially with this type of of of of of attack is that by default things in cloud are usually insecure.

09:00 So, you have to go, have a proper testing, have a proper preparation, pre-readiness of incident response, and to make sure that everything that is off by by default to be turned on, and in the same time to have more and more automation. And as well to have that defenders, we have to be closer to the DevOps, they have a proper DevSecOps operations, and it's all about automation.

09:24 So, you have a good pipeline, you have good automation testing, and in the same time we we will just want to make sure that secrets are kept in in the right place. So, you have a secret management and you don't have it in public GitHub, which is very common or just in in viable switches. Uh it's all about hygiene. So, just to sum up, good practice, uh don't let things by default because usually are insecure, and good practice and good hygiene with the with cloud overall, especially with the devops pet pipeline.

09:58 >> Absolutely. You can't take security for granted, especially not in this cloud environment. Uh I I really like that uh extremely comprehensive breakdown. Patrick, anything you would add there in terms of like security steps people should be taking right now? >> I think that you covered most of the really big things. I would only add, you know, emphasizing particularly on the the testing side.

10:17 We often make assumptions about what uh what we've exposed when we accomplish particular task, and developers are probably uh uh you know, are always in a position to do a lot of damage because they tend to have lots of access, and they're the ones who are actually building these applications. Uh they need lots of support to make sure that they can accomplish them in a security-conscious way and still get their jobs done.

10:39 I think that uh you know, uh things like secret managements are are are really important, but also every time you implement some changes, having an ability to assess, have we exposed ourselves to something new without realizing it. >> Absolutely. That that visibility is so key. I mean, you really don't know what kinds of ramifications your changes can have unless you are looking at them and looking for them.

11:01 Uh Michelle, close us out here. Anything you would add in terms of security steps? >> Yeah, I mean, I think both Errol and Patrick really provided a lot of different steps for especially from the enterprise perspective, the defender side, um but also the end user. We also have our responsibility in terms of um controlling the exposure surface, right?

11:23 How are our keys stored? I think I heard, you know, uh secret password managers mentioned. Um you know, how are we handling our keys, treating them as um highly sensitive as I mentioned in the beginning. So, both sides have responsibility on the side of the providers. We also need to ensure that you know, a leaked key ends up in bankruptcy as it seems like potentially there's some cases out there where this is happening and that's pretty serious.

11:50 >> Absolutely. And I'm glad all three of you hit that secrets management angle because we know that you know, credentials attackers are after them. When they get in, they try to get more of them. There's potentially massive blast radius so those things have to be locked down. I'm going to move us along to our next story for today, but before I do, just opening up the conversation to the listeners out there watching this on YouTube.

12:09 Tell us what you're doing to secure your AI credentials right now. What steps are you taking? What are you thinking about to make sure that nobody gets in there and misuses your tools. Moving along though, we're talking about adversary simulation in the age of AI. Now, Patrick Fissell is on the panel today and he's also the author of this piece we are discussing published on IBM Think entitled The Adversary Didn't Wait, Neither Should You.

12:38 Now, I don't want to put words in your mouth, Patrick, but the gist here that I took away was that threat actors are using AI to amplify the speed and intensity of their attacks, which means our adversary simulations and offensive security research should reflect this new reality. At the same time, the human is still a crucial part of that loop. So, tell me in your words, what were you arguing here?

13:02 What's the what's the message of this piece? Tell us what you're thinking about. >> Sure. I mean, I think you nailed the the big point, but what really inspired me to start thinking about this a little bit more was I don't think that that mythos is new news to anybody. Everybody was talking about Project Glasswing over the past couple of months. Obviously a very big thing in the security world.

13:22 But what was so interesting to me was that there a lot of this conversation was around things that I did I felt like was missing the the larger point. And so, you know, the initial glasswing posts from Anthropic focused fairly have very heavily on this idea of this guy discovering vulnerabilities. So, you know, analyzing code and understanding that there might be a problem with it, which is super important and like I'm glad that it's one of the things that we're looking at, but that's not exactly or not the only thing

13:47 that an attacker is going to do because they don't probably don't have access to all of your source code, you know, hopefully they don't. Um they're thinking about how can I use or how could I use a model to effectively make me more effective as an attacker? Like things like getting access. And so, where are all the phases of things that they're going to do where they bring AI to bear?

14:06 And um while Mythos is is an important conversation point, I'm actually glad that it's it's shining a light on this concept. It's something that, you know, my team and I had actually been thinking about for, you know, six or eight months, not not just since Mythos. This isn't brand new, right? Models have been around for a while now. >> Absolutely. And can you elaborate a bit on on, you know, the importance of having a framework, right?

14:26 One of the things that comes up in your piece is this X frame idea. Can you tell us a little bit about what that is, why it's important to have that kind of guidelines when you're doing this work? What can you tell us? >> Sure. Um you know, the it's obviously one of those things that uh has a ton of moving parts, but the the thing I would always start with when we talk about this is uh it if you're running a company and you're, let's say either you're the CTO, would you let AI run rampant on your network and do

14:51 whatever it wanted? I think almost everyone's going to say no to that. And if you say yes, then I would love to have a conversation with you and get some more uh why behind that. I think maybe most of us are aware of a recent news story about um an AI that deleted some very important parts of a a company and um had some serious impacts. So, uh I think, you know, the first part is you sort of the safety and security.

15:12 AI is not at a point yet where we can let it just go off and do whatever it wants. But more importantly, it's um about leveraging AI in a way that makes sense. So, I think when AI was you know uh generative AI came to the forefront very but I thought it's going to solve all of our problems but very quickly we talked to some of our our data scientist friends and we find out there are things that that AI is going to be good at and there's things that it's not going to be good at in framing the problems in a way that

15:36 really lets it do its job well is important while also leveraging the expertise of the people behind the keyboard making sure that they're um as effective as they can be by you using the systems to improve themselves basically. >> Absolutely. That makes a lot of sense to me and it reminds me you know you mentioned like letting an AI run rampant and it reminds me of the story we covered a little while back where uh uh folks at Sophos experimented with Open Claw as a as an AI red teamer basically and one of the really

16:00 interesting things to me there was that they ran into this problem where they struggled with getting the guardrails just right so that it didn't do any damage but was still useful. Like it could still actually find things but not break things when finding them and I feel like that's a perfect encapsulation of like why there's got to be a human still in the loop, right?

16:18 Like there's got to be that that human oversight to make sure things are useful and not breaking things. Um Michelle, I want to bring you in here now looking at you know Patrick's piece thinking about what we've discussed so far. Uh what are your thoughts on on keeping humans in that adversary simulation offensive research loop? What are you thinking about?

16:36 >> Yeah, of course and when I read the article which great blog by the way Patrick um of course one puts themselves in their own shoes, right? You're in your own shoes like what's my role? How does this apply to me? Um and similarly you know I think threat intelligence analysts also need to be in the loop when um looking at threat intelligence because of course AI is great for a lot of things um in this space.

17:03 You know I can give it a report, it can scrape the IOCs, um it can you know aggregate a large amount of data and we can kind of look up some of the dots and connect those that way. Um but you know for actual threat intelligence, which requires interpreting all of those signals, um what they mean, assessing adversary intent, just sort of adding all of that contextual data, um is really when you also need the human in the loop for threat intelligence.

17:32 So, for that reason, I think there's a lot of correlations, and I would imagine uh Herb Lin uh feels the same way. Or, feel free to play devil's advocate and say, "No, I don't need to be in the loop." >> I you kind of read my mind there, Michelle, cuz as you were talking, I was like, "Oh, it's really interesting to get, you know, we we've heard Patrick's take on how it's affecting his field in in adversary simulation.

17:50 We've heard your take on how it's affecting your your field in in, you know, threat intelligence, and why the human is still important in the loop there." Herb Lin, any thoughts on how it's uh infect affecting you guys over in, you know, incident response, and where the human still fits into the loop there? What what are your thoughts? >> I think incident response is still very very uh I would say sensitive topic, especially with like chain of causality, like artifacts, forensic artifacts.

18:12 Uh and the idea is that it really depends, but something that's I love about AI is that for some automation, for some low-hanging fruits, it's extremely good. Because it has some automation, it can do a lot of uh pulling for you. But, the issue is that still I think human is very important. Is it helping? Definitely, yes. But, I heard a very good quote from from from from my friend, one of my friends, uh a few days ago, and it was, "AI is good as your So, it's also is really depends who is behind the the the AI, who is

18:47 building the the detection, who is responding with the AI. So, I think if it's not properly uh in the right framework, if it's not basically guided by the proper standard responder in this case, or SOC team, or incident manager, I think it's very difficult to to to to to to have basically a right step of incident response in this case, but in the same times to be the human in the loop, which is knowing what the eye is looking for.

19:14 So, just to summarize, I would say that for for low-hanging fruits, for automation, for giving you the direction where it's going, or for example, for decoding, decryption, or just helping you with extremely good, but for a whole chain of attack, I think it's still human is is the most important factor here. And again, I I see a lot of potential. It's helping a lot, but again, it's it's a response also about the chain of custody, it's about the uh For example, a lot of other points which I think we need to be very

19:50 careful when implementing, especially in the sensitive cases. >> Absolutely. There's There's two things that I want to highlight. You know, the first is this this quote um about, you know, AI is only as good as you are. I really like that, and it reminds me of what is kind of becoming the show's like unofficial motto, which is something that Dave McGinnis said you months and months and months ago, and now I bring it up like once an episode, which is, you know, AI agents are the most helpful insider threats we've ever

20:13 had, right? And I feel like it is such a perfect encapsulation of where we're at with these things. Um so, that was the first thing, and the second thing I wanted to kind of, you know, call out there was I like how you highlight the accountability issue, especially in something like instant response, right? Where like you said, things like chain of custody are still really important, and you can't really make an AI accountable for something like that, right?

20:34 Like we're just we're not there yet. I don't know if we ever will be, but we need to think about these accountability issues, especially as we start integrating these things into our workflows, and they start taking more and more autonomous actions. Uh to close out this segment, Patrick, I just wanted to circle back around to you. Is there anything we have not discussed here, or any major takeaways you want to get out there to the the audience before we move on?

20:56 >> I don't know if it's uh necessarily um you know, Michelle said playing devil's advocate. I'm not sure if it's necessarily the uh the the opposite side, but you know, we'll say I think that AI brings an entirely new platform the way that we think and approach problems and one of the things that we haven't done yet as, you know, teams and companies is think about that we're structurally changing the way that we do business and, you know, thinking specifically about adversary simulation.

21:22 If I have an AI that can do still steps A through C, I no longer need to stop having my teams do A through C and focus on what are the things that we do? You know, what are these um which is great because now they can they can focus on these really novel attack chains and developing the things that really give us the power, but we have to be willing to let go of things the way they were and focus on where does the human brain value and make sure that's what we're spending our time on.

21:48 >> I like that. I think that's a really positive framing cuz I think it's it's very easy to kind of be a doomer about some of this stuff, you know what I mean? But I really like that reframing of like, "Look, things are going to be different, but we can embrace that and we can do something really cool with it." Um so, on that note, let's move along to our final story of the day, folks.

22:04 I'm talking about speeding up our patch timelines. Reuters reports that CISA, the US Cybersecurity and Infrastructure Security Agency, is mulling over a change to federal patching standards in the wake of Mythos and GPT 5.4 cyber. So, current guidelines give federal agencies 2 weeks to fix a flaw under active exploitation, uh and people are talking about cutting that down to 3 days.

22:32 You know, it's understandable why people would want to cut that down, right? AI tools that attackers find and exploit vulnerabilities faster than ever. Uh a couple weeks ago on the show, we talked about the zero-day clock and how they were tracking that, you know, in 2018, it took an average of 2 years to exploit a flaw and now it takes less than a day.

22:49 So, I understand why we want to move faster with patching, but the question is can we actually move that fast? A lot of experts are a little skeptical of that timeline or just our ability to cut down patching in general. And Michelle, I'll start with you. I'll give you this nice difficult question. Uh what do you think about shortening our patching window?

23:07 Does it seem like it's something within our grasp or no? >> Sure. Like I think we should talk about that, but also first I'm wondering if we're asking the right question because patching is just one thing, right? Um there are other necessary mitigations to uh both mitigate exploitation and also if there is exploitation reduce damage. So, I get that we should talk about like the patching window and what are some things we can do that.

23:32 I don't know how we went from 2 weeks to arbitrarily 3 days. Um you know, maybe there's some ways to sort of um incrementally bring that down to a shorter patch window. But again, I'll ask respond to a question with a question. Should we be asking about, you know, the patch window when there's so many other things that maybe are even um more um detrimental to potentially uh incident occurring.

24:02 >> No, I think that's a really good question, right? Is like should is that the right question to be asking? Because again, as you point out, patching that's one thing. That's one part of this whole defensive posture we can strike. And Patrick, I saw you nodding along there, so I'm going to ask you, you know, thinking about Michelle's response there, you know, whether patching is the right question to ask.

24:17 What are your thoughts, you know, whether you build on that, agree, disagree, where you take it? >> Yeah, I think Michelle nailed nailed it, and I think that the really key element we have to start with is everything's a matter of balancing resources. The way that I always frame this when we're working with with clients is um our goal as people stopping hackers is to raise the cost of what it takes to affect a breach.

24:41 So, they spend so much money getting to the you know, the breach done that now that they've got a negative return on their investment. If we can raise that cost high enough, they'll go away and do something else, right? Um and so, you know, managing the resources that any company has is really key. And if we're so if we think about how complicated patch rollout could be on production level systems, if it's breaking things, that becomes an untenable stance.

25:04 So, I think Michelle is right, you know, um certainly patches can be an important part of the process, but it it's if we also think about this from from the attacker's standpoint of um you know, finding a vulnerability and exploiting it, well, we're making an assumption on the patch thing that that uh vendors are writing the patches fast enough to roll them out that 3 days even matters in the first place, or that they're even going to know about these things because they're going to happen so fast.

25:28 So, um I think that while, you know, if you have a patch system that allows for that, great, good for you. I'm glad to hear that you can roll those out, but there may be other things that you need to focus on before you're thinking about trying to achieve this what might be a big target for some organizations. >> I'm glad you bring that up and you kind of un- unpack what is involved in patching, right?

25:47 Like you said, like there are factors outside of our control here. Like, did the vendor write a patch fast enough? You know what I mean? And and and the downtime that's required. Can you shut down production for as long as you need to for this patch? Like, there's a lot of calculations that go into it. So, when you're like one guy sitting at a laptop, you think, "Ah, patching, that's easy.

26:03 Click update." It's not so much when you're talking about an enterprise network, you know? Uh Erblin, I want to bring you in here, you know, uh thinking about what's come up so far, thinking about these ideas about uh shortening the patch window. What's got you thinking about? What are your concerns or hopes here? >> We are in the moment which basically we are fighting against machines because it's cloud, it's virtual servers.

26:22 So, I think we should start thinking to have also machine versus machine. Because it's it's very hard that you have uh the attacker using complete this autonomous AI, and you're patching with spreadsheet. You need five, six uh approvals to basically patch something. So, I think there are a lot of uh we have to be agile. We need to use more microservices, and the most important part, as Michelle said, is defense-in-depth.

26:51 So, we shouldn't be only in in one line. We have We should have like all all the phases of detection, preparation. So, I think we have It's It's It's It's very hard question, to be honest. And it's It's It's extremely complex and very hard day to be a CISO. But, we should go in that direction of agility to be to to be faster. Because And also to have machine to machine.

27:15 So, what can we do in this direction to be faster? And in the other days, I said machines versus machines. And less spreadsheet, more agile, more microservices. And multiple layers of of of detection, automation, which I think it's It's It's It's It's the response here. But, again, it's It's It's very difficult, especially for 3 days. Very arbitrary.

27:39 And it's And And it's not just about one application. Whatever that you have, uh libraries, you have application, you have system OS in this case. So, it's It's gets complex and more complex. >> Absolutely. And I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I

27:58 I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I

28:09 I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I

28:19 I I I I I I I We talked about defense in depth. We talked about the things we can do aside from patching. What's the one piece of advice you'd give organizations right now when it comes to dealing with the the the sped up timeframe of vulnerability finding and exploitation? What are you thinking about? >> Well, I think we've mentioned this quite a bit on this podcast.

28:35 It's knowing and having visibility across your network. So, knowing what are your critical assets, um and being able to respond quickly. So, I hope I didn't take any thunder from Errol Wind because that's instant response. You have great panel here today. A lot of disciplines represented. But I think that's first and foremost what do you you have to know what you're protecting in order to protect against it.

28:58 >> Absolutely and I think that's especially you know relevant for patching conversation because so many of the difficulties of patching is around that visibility. Patrick how about you? What's the kind of one piece of advice you'd be telling organizations to follow walking away from this? >> Yeah, I think the you know most effective organizations tend to have this concept of assumed breach built into the security fabric of their organization so we think you know I think a lot of people want to think we have whatever

29:29 XYZ control EDR or whatever it is. There's no way that attackers will get past that but I think you know these these groups are sitting around all day every day researching how do we apply these things that we're talking about to affect a breach. And so organizations that respond quickly and have the best controls are always the ones who think yes we are going to be breached.

29:48 Are we ready if we look across the perspective of places that that can happen? What do we have there that's going to help us respond to that and be ready and isolate and move quickly and they practice and exercise those things. >> Absolutely and and Patrick one of the things I appreciate about you know your appearance on the show today is a lot of your advice has come down to you like changing your mindset about some of this stuff and approaching it from a new perspective and I like that because it's like all right you

30:12 like you said assume breach you know you don't assume that like no one's going to get past us. Assume we got all these protections in place someone's going to break them anyway. What do we do then? I really like that. Errol to close this out today what what's the one piece of advice that you would give organizations around this topic? >> I would with a quote that's is by Jeff Cavish.

30:29 I love it's like the best time to fix the roof is when the sun is shining. Which basically means that do your preparation do your homework do your incident response plan. and exposure plus knowing your your your environment I think is key. So you do it's it's it's more now of proactive security than just waiting for active. Like I have an IR now I have to fix my roof.

30:55 No, preparation preparation preparation. >> Absolutely. I love that. Preparation preparation preparation. That does it for this episode. I want to thank our panelists Michelle and Patrick and Irvin. Thank you to the viewers and the listeners. Thank you to our producers. Subscribe to Security Intelligence wherever podcasts are found so that you never miss an episode. Stay safe out there and lock up your API keys.