MultipartParser denial of service with too many fields or files
Affecting starlette package on PyPI
Context / Overview
Impact
The MultipartParser using the package python-multipart accepts an unlimited number of multipart parts (form fields or files).
Processing too many parts results in high CPU usage and high memory usage, eventually leading to an <abbr title="out of memory">OOM</abbr> process kill.
This can be triggered by sending too many small form fields with no content, or too many empty files.
For this to take effect application code has to:
- Have
python-multipartinstalled and - call
request.form()- or via another framework like FastAPI, using form field parameters or
UploadFileparameters, which in turn callsrequest.form().
- or via another framework like FastAPI, using form field parameters or
Patches
The vulnerability is solved in Starlette 0.25.0 by making the maximum fields and files customizable and with a sensible default (1000).
Applications will be secure by just upgrading their Starlette version to 0.25.0 (or FastAPI to 0.92.0).
If application code needs to customize the new max field and file number, there are new request.form() parameters (with the default values):
max_files=1000max_fields=1000
Workarounds
Applications that don't install python-multipart or that don't use form fields are safe.
In older versions, it's also possible to instead of calling request.form() call request.stream() and parse the form data in internal code.
In most cases, the best solution is to upgrade the Starlette version.
References
This was reported in private by @das7pad via internal email. He also coordinated the fix across multiple frameworks and parsers.
The details about how multipart/form-data is structured and parsed are in the RFC 7578.
Jit Recommended Tools
OSV-Scanner
Objective: Dependency check (SCA)
Description: OSV-Scanner provides an officially supported frontend to the OSV database that connects a project’s list of dependencies with the vulnerabilities that affect them. Since the OSV.dev database is open source and distributed, it has several benefits in comparison with closed source advisory databases and scanners:
Vulnerability Layer - SCA
SCA Dependency Check is one of the important tools used to identify vulnerabilities in open-source components used in software applications. However, it primarily focuses on identifying vulnerabilities in the dependency layer of the software application. In contrast, code vulnerability layer analysis is focused on identifying vulnerabilities in the source code of the application itself, rather than the dependencies it uses. It typically involves analyzing the source code to identify security issues such as buffer overflows, injection vulnerabilities, and authentication issues, among others. While SCA Dependency Check is an important tool in identifying vulnerabilities in open-source dependencies, it may not be sufficient to ensure the overall security of the software application. To ensure comprehensive security, it is important to also perform code vulnerability layer analysis to identify vulnerabilities in the source code of the application. Incorporating both SCA Dependency Check and code vulnerability layer analysis into the software development lifecycle can help ensure that vulnerabilities are identified and remediated at both the dependency and code layers of the application. This can help prevent security issues from being introduced into the final product and improve the overall security posture of the software application.

