Frontier AI Models & Cybersecurity: Protecting Your Organization in the LLM Era

Today, I want to talk about frontier models and the cybersecurity implications around them and sort of, you know, what it means to businesses and organizations today. But, you know, in general, how do you deal with the use of these models in a cybersecurity perspective, from a cybersecurity perspective? Because that is something that is key as we also look towards more powerful and usable open source models. Because the problem is from a from a anthropic perspective, from a open AI perspective, where they have chat GBT is they can put the guardrails in place, they can try and ensure as much as humanly possible, at least, that when people use their models, they can't do anything particularly nefarious with them. Now, when it comes to leveraging these models, of course, you know, there's less of a risk to an organization.

But at the same time, you have to think about the open source models and people also being able to jailbreak them because they are not perfect. And so as an organization, we have to start to think about things like attack vectors that are amplified from where they used to be. So like, as a organization, traditionally, the attack vectors may be someone just going through a shared drive or through, you know, an internal route to be able to give people access to information that they shouldn't have access to. These days, of course, with self hosted models and the ability to be able to bring these models in from, you know, anywhere on the internet, the rate that someone can start to leverage those internal attack vectors increases dramatically just because of the nature of the way that these attacks work. You know, if you can set up a bit of a farm, you know, when it comes to self hosted models that have no safeguards in place or very few safeguards in place, then the expectation for a jailbreak or the expectation for someone to be able to find something that they shouldn't be able to on an internal network is greatly, you know, is greatly increased.

The other thing, of course, is external attacks. And so this allows for an awful lot of attacks that weren't viable before to be to be done in a much faster and more widespread operation. And so from a from an enterprise organization perspective, you now have to think about the investment in your infosec department, your cybersecurity department to ensure that they have the best tools available to them to be able to, you know, both detect and mitigate any threats that are ongoing in, you know, the area that you guys are working in. And so using LLMs, both for good and for bad in this case, is something that's going to be important. Being able to utilize the latest technologies to be able to, you know, leverage the defensive capabilities as well as the offensive capabilities of LLMs is going to be something that's going to change a lot over the course of the next few months and years.

You know, but then also from an architecture perspective, if you've got self hosted software that you have written and developed internally or externally with, you know, an external company or whatever, like what does the update frequency look like? How do you detect whether LLMs, LLMs, sorry, how do you detect whether dependencies have been compromised? How do you know that the supply chain that you're building against really offers that protection that you need whilst you're building these pieces of software out? And so then you start to look at companies like Snyk, companies like Chainguard, who, you know, make it their job to be able to make sure that the software that you're utilizing and you're leveraging is as secure as it can be. Because things like supply chain attacks are becoming more and more frequent.

We've seen it where compromised GitHub actions, you know, start to make nefarious commits on updates to software. You've seen pull requests that have gone in because of the volume of pull requests that are going in these days. Developers are swamped and don't validate them properly. And so they go in and all it takes is one compromised upstream dependency, not even the piece of software that you have written or the software that you're leveraging as direct dependencies, but a transient dependency. It comes in from somewhere else.

All it takes is something like that to be to infect your internal workplace. And suddenly either data is exposed, compromised, or you end up locked out, you know, with a Bitcoin ransom. Old school, old school hacking setup. And so, like, you know, the core message from this from this podcast is to make sure that you have the mitigation in place and the thoughts and the processes that you have gone through as an organization to ensure that, you know, everything is up to date. Operating system patches critical to the, you know, the safety and security of the data inside of your organization.

You know, library and dependency updates do not let those things stagnate, especially if they're, you know, accessible either to internal or external users directly. Make sure that you have all these policies in place, because if you only stick them in place after your stuff has been compromised, it's too late. As the frontier models increase in their effectiveness and the stuff that they can do, expect the attack vectors to become more novel, to change and become more critical to business operation. If you need some help and support, feel free to get in contact. Conceptcloud.

com. Otherwise, I will speak to you all next week. Have a great weekend. Bye for now. Why hire when you can partner?

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