And then from that, how are enterprises supposed to scale at this size of attack and when it becomes easier and cheaper to do that?

Yeah, it's really interesting because it used to be a bit more static than it is today, right? One of the bigger problems right now especially is the geopolitical threat landscape is so chaotic.

We don't know what nation's going to attack another nation on a daily basis.

so that causes the threat model to change significantly on a regular basis and so one of the things that i've seen pretty consistently is that especially on large security teams they're updating their threat model they're looking at a geopolitical risk standpoint even if they don't have a geopolitical risk team that's dedicated to that they're still looking at it on a regular basis we see at least quarterly sometimes monthly sometimes even more frequently Because if you don't, then you could get into a situation like we saw with Iran and the Handal hackers, where you become a target even if you weren't in the weeks and months prior, you become one because of the changing geopolitical landscape.

And by the time that you understand that, you've already been hit.

And so it's really critical to start as early and often as possible with evaluating the existing geopolitical landscape outside of cybersecurity, and then apply the potential motivation of the attackers based around that and to make decisions based around that.

Now, AI introduces an entirely different layer that's really interesting here because the attacks that they're able to perpetrate are not just much faster, but they're much more dynamic.

How has that kind of changed the attack economy and maybe what the new threats will kind of start looking like, or emergent threats and emergent patterns that we're going to start seeing?