For most of security’s history, defenders were saved by time. A vulnerability was disclosed, a patch shipped and attackers spent months or years building a reliable exploit. That lag was the buffer the entire scan-and-patch model was built on.
That buffer is gone. According to the Zero Day Clock, the average time from vulnerability to weaponized exploit has fallen from roughly two and a half years in 2018 to a matter of hours in 2026. Frontier models like Mythos are the reason. The same system that finds a flaw in your code can write a working exploit against it, and it can do both at machine speed.
Time to Exploit
Permission granted by Rein Security
This creates two problems at once, and they pull in opposite directions.
The first is the unknown attack. A frontier model can discover a zero-day in your application, your AI agents, the tools they call, or their dependencies, with no CVE and no patch to reference. When the target is an agent holding API keys, database access and the ability to run code, the distance from discovery to breach closes in seconds. There is nothing to scan for, because the flaw has never been catalogued.
The second is the known vulnerability flood. The same capability that finds novel flaws also generates vulnerability reports by the thousands. Backlogs that were already unmanageable now overflow. Teams patch by instinct rather than by risk, and every hour spent on a vulnerability that can never be reached in production is an hour not spent on the one that can.
Notice that neither problem can be solved by looking at code at rest. A scanner cannot flag a zero-day that does not yet exist. A scanner also cannot tell you whether a known CVE is actually reachable in your running system, so it flags everything and calls it diligence. The blind spot is the same in both cases: tools that inspect artifacts instead of behavior have no idea what your software actually does when it runs.
That is why the only approach that holds up in a post-Mythos world is execution-based. Instead of asking what might be wrong with the code, you watch what the code and the agents actually do in runtime, in real time. Every prompt, every tool call, every API request, every library invocation, every resource touched.
Watching execution solves the unknown problem without needing a CVE. Watching execution also drains the known flood. First, you can block unwanted behavior the same way you block Zero Days, which buys you time until remediation. Then, once you can see which functions actually run and reachable, you can separate the vulnerabilities that are genuinely exploitable in your environment from the thousands that only exist on paper. The unreachable CVE cost you a lot to manage, but with this approach, it literally costs you nothing. The reachable one gets your attention. Prioritization stops being a guess.
Moving Security to Production Solves Two Problems at Once
Permission granted by Rein Security
Prevention used to mean keeping bad things out before they ran. In a world where attacks are generated on demand, faster than any human response, prevention has to mean recognizing and stopping bad behavior as it happens. The control point moves from the perimeter and the pipeline to runtime.
The timeline is not going back. The only defense that can move at the speed of a frontier model is one that lives where the model’s exploits ultimately have to run.
