CVE-2023-25577

Description

A flaw was found in python-werkzeug. Werkzeug is multipart form data parser, that will parse an unlimited number of parts, including file parts. These parts can be a small amount of bytes, but each requires CPU time to parse, and may use more memory as Python data. If a request can be made to an endpoint that accesses request.data, request.form, request.files, or request.get_data(parse_form_data=False), it can cause unexpectedly high resource usage, allowing an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests, and if many concurrent requests are sent continuously, this can exhaust or kill all available workers.

Common Vulnerability Scoring System (CVSS) Score Details

Info alert:Important note

CVSS scores for open source components depend on vendor-specific factors (e.g. version or build chain). Therefore, Red Hat's score and impact rating can be different from NVD and other vendors. Red Hat remains the authoritative CVE Naming Authority (CNA) source for its products and services (see Red Hat classifications).

CVSS v3 Score Breakdown

Red HatNVDcve.org
Base Score7.57.57.5
Attack VectorNetworkNetworkNetwork
Attack ComplexityLowLowLow
Privileges RequiredNoneNoneNone
User InteractionNoneNoneNone
ScopeUnchangedUnchangedUnchanged
ConfidentialityNoneNoneNone
Integrity ImpactNoneNoneNone
Availability ImpactHighHighHigh

Vector

Red Hat: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

NVD: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

cve.org: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Understanding the Weakness (CWE)

Availability

Technical Impact: DoS: Resource Consumption (CPU); DoS: Resource Consumption (Memory); DoS: Resource Consumption (Other)

When allocating resources without limits, an attacker could prevent other systems, applications, or processes from accessing the same type of resource. It can be easy for an attacker to consume many resources by rapidly making many requests or causing larger resources to be used than is needed.

Frequently Asked Questions

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