GHSA-2c2j-9gv5-cj73
MEDIUMStarlette has possible denial-of-service vector when parsing large files in multipart forms
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
Blast Radius
starletteReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
Summary
When parsing a multi-part form with large files (greater than the default max spool size) 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) has a minor bug. Instead of just checking for self._in_memory we should also check if the additional bytes will cause a rollover.
@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 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.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | starlette | all versions | 0.47.2 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for starlette. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update starlette to 0.47.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-2c2j-9gv5-cj73 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-2c2j-9gv5-cj73 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-2c2j-9gv5-cj73. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-2c2j-9gv5-cj73 in your dependencies?
O3 detects GHSA-2c2j-9gv5-cj73 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.