icon-to-image#As someone who primarily works in Python, what first caught my attention about Rust is the PyO3 crate: a crate that allows accessing Rust code through Python with all the speed and memory benefits that entails while the Python end-user is none-the-wiser. My first exposure to pyo3 was the fast tokenizers in Hugging Face tokenizers, but many popular Python libraries now also use this pattern for speed, including orjson, pydantic, and my favorite polars. If agentic LLMs could now write both performant Rust code and leverage the pyo3 bridge, that would be extremely useful for myself.
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The Sentry intercepts the untrusted code’s syscalls and handles them in user-space. It reimplements around 200 Linux syscalls in Go, which is enough to run most applications. When the Sentry actually needs to interact with the host to read a file, it makes its own highly restricted set of roughly 70 host syscalls. This is not just a smaller filter on the same surface; it is a completely different surface. The failure mode changes significantly. An attacker must first find a bug in gVisor’s Go implementation of a syscall to compromise the Sentry process, and then find a way to escape from the Sentry to the host using only those limited host syscalls.