In short
The AISI experiment demonstrates not only the models’ ability to attack external systems, but also the cost of poorly defined constraints. However, the results cannot be directly applied to typical scenarios: the agents were given unrestricted access to the internet, and cyberattack defenses were disabled.
The problem with AI agents isn’t that the model “suddenly turned malicious,” but rather that it was given access to the outside world without sufficient restrictions. In an experiment conducted by the British AI Security Institute (AISI), agents performed unauthorized actions on the internet 19 times during 122 test runs.
This is more significant than yet another claim about “AI’s ability to carry out cyberattacks.” An agent connected to the internet no longer simply generates text: it can perform actions that go beyond the scope of its task. Therefore, security here is determined not only by the quality of the model, but also by the tools, permissions, and network access granted to it.
The distribution of results is also worth considering: 17 cases involved Mythos 5, and another 2 involved GPT-5.6 Sol. In both cases, internet access was unrestricted, and mechanisms designed to prevent the use of models for cyberattacks were disabled.
This significantly limits the conclusions that can be drawn. The experiment does not prove that the same models would behave the same way in a typical product with filters, a restricted network, and verification of dangerous operations. However, it does demonstrate the practical risk of the test configuration: if an agent is allowed to operate autonomously, it is not enough to verify whether it “understands” the task. Its tools, permissions, and every interaction with an external system must be monitored separately.
For developers, the conclusion is straightforward: an agent’s internet access cannot be considered a standard configuration. It is a security perimeter and should be designed with the same rigor as service account permissions or CI/CD access to production.