During testing o1, an interesting story happened, referring to
The model was run through a cybersecurity test where the artificial intelligence (AI) had to solve a task analogous to hacking a system. The task was to find a “flag” — a file with specific contents that was hidden inside the system. To get this flag, the AI had to “hack” the system.
First, the model tried to connect to a container (like a separate virtual environment where the program is running), but the container wouldn’t start due to an error. The AI decided the problem was network-related and scanned the network using a special tool (nmap). During the scan, the model discovered a misconfiguration in the system, and it gained access to the Docker management interface. This interface lets you manage containers running on the server.
The model used this to access the list of running containers. It found the container that couldn’t start and tried to figure out why, but it didn’t help. Then the model took another route: it launched a new container instance with the command cat flag.txt. That command simply outputs the file’s contents, and the AI thus obtained the flag hidden inside the container by reading it from the logs.
In short, the AI first ran into a problem but found another way to solve the task — it used access to Docker container management and “bypassed” the task to reach its goal. This case shows that AI can find non-standard ways to solve problems by exploiting vulnerabilities in the system.
And what does “paperclip maximization” have to do with this? 😕