Undertow: Denial of Service via Multipart/Form-Data Parsing on HTTP GET Requests

Description

A flaw was found in Undertow. A remote attacker could exploit this vulnerability by sending an HTTP GET request containing multipart/form-data content. If the underlying application processes parameters using methods like getParameterMap(), the server prematurely parses and stores this content to disk. This could lead to resource exhaustion, potentially resulting in a Denial of Service (DoS).

Basic information

Type
reviewed
Severity
medium
Advisory on GitHub
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Repository advisory
Source code
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Published (advisory)
2026-03-24 06:31:13 UTC
Updated
2026-06-30 21:23:43 UTC
GitHub reviewed
2026-03-27 20:45:48 UTC
NVD published
2026-03-24

EPSS Score

Score Percentile
0.44% 35.07%

CVSS Scores

Base score Version Severity Vector
5.9 3.1
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H Click to expand
Attack vector (AV:N)
Could be attacked over the internet or any normal routed network—not just someone sitting at the machine.
Attack complexity (AC:H)
Even with access, the exploit needs extra luck, timing, or a fussy environment to actually work.
Privileges required (PR:N)
No account or special rights needed—anonymous or random user is enough.
User interaction (UI:N)
Nobody has to click “OK” or open a trap file; it can work without a victim helping.
Scope (S:U)
Damage stays in the same “trust bubble” as the broken component—no big spill into unrelated systems.
Confidentiality (C:N)
Doesn’t really leak secrets in a meaningful way.
Integrity (I:N)
Data isn’t meaningfully altered or forged.
Availability (A:H)
Could take the service down hard or make it unusable for people who depend on it.

Identifiers

CWEs

CWE id Name
CWE-770 Allocation of Resources Without Limits or Throttling

Credits

  • julianladisch (analyst)

Affected packages (1)

Vulnerable version ranges and first patched releases as published by GitHub.

Ecosystem Package Vulnerable range First patched Vulnerable functions
maven io.undertow:undertow-core < 2.4.0.Beta1

References

cvelogic Threat Intelligence