GHSA-2c2j-9gv5-cj73

Starlette has possible denial-of-service vector when parsing large files in multipart forms

### Summary When parsing a multi-part form with large files (greater than the [default max spool size](https://github.com/encode/starlette/blob/fa5355442753f794965ae1af0f87f9fec1b9a3de/starlette/formparsers.py#L126)) `starlette` will block the main thread to roll the file over to disk. This blocks the event thread which means we can't accept new connections. ### Details Please see this discussion for details: https://github.com/encode/starlette/discussions/2927#discussioncomment-13721403. In summary the following UploadFile code (copied from [here](https://github.com/encode/starlette/blob/fa5355442753f794965ae1af0f87f9fec1b9a3de/starlette/datastructures.py#L436C5-L447C14)) has a minor bug. Instead of just checking for `self._in_memory` we should also check if the additional bytes will cause a rollover. ```python @property def _in_memory(self) -> bool: # check for SpooledTemporaryFile._rolled rolled_to_disk = getattr(self.file, "_rolled", True) return not rolled_to_disk async def write(self, data: bytes) -> None: if self.size is not None: self.size += len(data) if self._in_memory: self.file.write(data) else: await run_in_threadpool(self.file.write, data) ``` I have already created a PR which fixes the problem: https://github.com/encode/starlette/pull/2962 ### PoC See the discussion [here](https://github.com/encode/starlette/discussions/2927#discussioncomment-13721403) for steps on how to reproduce. ### Impact To be honest, very low and not many users will be impacted. Parsing large forms is already CPU intensive so the additional IO block doesn't slow down `starlette` that much on systems with modern HDDs/SSDs. If someone is running on tape they might see a greater impact.