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🐍
🐍 PyPI
Not in CISA KEV
HIGH severity

GHSA-p24m-863f-fm6q

HIGHFix: starlite-api/starlite@9674fe8

GHSA-p24m-863f-fm6q is a high-severity (CVSS 7.5) CWE-770 vulnerability in starlite. 1 public exploit reference exists, so weaponization risk is real. O3 Security confirms whether GHSA-p24m-863f-fm6q is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

Denial of service vulnerability when parsing multipart request body

Also known asCVE-2023-25578PYSEC-2023-49
Published
Feb 15, 2023
Updated
Feb 4, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
1 known
Exploitation data as of Feb 4, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Real-World Exposure

1 pkg affected
🐍starlite

Real-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

The request body parsing in starlite allows a potentially unauthenticated attacker to consume a large amount of CPU time and RAM.

Details

The multipart body parser processes an unlimited number of file parts. The multipart body parser processes an unlimited number of field parts.

Impact

This is a remote, potentially unauthenticated Denial of Service vulnerability.

This vulnerability affects applications with a request handler that accepts a Body(media_type=RequestEncodingType.MULTI_PART).

The large amount of CPU time required for processing requests can block all available worker processes and significantly delay or slow down the processing of legitimate user requests. The large amount of RAM accumulated while processing requests can lead to Out-Of-Memory kills. Complete DoS is achievable by sending many concurrent multipart requests in a loop.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIstarliteall versions1.51.2
Exploits & PoCs
1

Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for starlite. 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.

  2. Fix

    Update starlite to 1.51.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-p24m-863f-fm6q is resolved across your whole dependency graph.

  3. 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.

  4. How O3 protects you

    O3 pinpoints whether GHSA-p24m-863f-fm6q 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-p24m-863f-fm6q. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Summary The request body parsing in `starlite` allows a potentially unauthenticated attacker to consume a large amount of CPU time and RAM. ### Details The multipart body parser processes an unlimited number of file parts. The multipart body parser processes an unlimited number of field parts. ### Impact This is a remote, potentially unauthenticated Denial of Service vulnerability. This vulnerability affects applications with a request handler that accepts a `Body(media_type=RequestEncodingType.MULTI_PART)`. The large amount of CPU time required for processing requests can block a
O3 Security · Impact-Aware SCA

Is GHSA-p24m-863f-fm6q in your dependencies?

O3 detects GHSA-p24m-863f-fm6q across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.