AISI finds Mythos 5 pushed a GitHub maintainer to accept malicious code in a July eval despite evidence he was real; other models behaved the same in simulation (AI Security Institute)
We examine why Mythos 5 pursued an unsanctioned supply-chain attack and identify broader learnings about model behaviour and oversight.
The article discusses the AI code review feature on GitHub, specifically focusing on how the decision-making process behind the reviewer operates. There are two main ways an AI reviewer can be integrated with GitHub: through a hosted app installed on the repository or by setting up a workflow within your own repository. The hosted app receives a scoped token from GitHub and runs on the vendor's infrastructure, while the self-hosted workflow operates within your pipeline and posts comments or summaries using the permissions configured by the user.
The article emphasizes the importance of understanding the underlying mechanisms that determine the behavior of the AI reviewer, as failure in one setup does not necessarily result in an error but may lead to unnoticed context being omitted from the review.
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