CVE-2025-13466

Nov. 25, 2025, 10:16 p.m.

5.5
Medium

Description

body-parser 2.2.0 is vulnerable to denial of service due to inefficient handling of URL-encoded bodies with very large numbers of parameters. An attacker can send payloads containing thousands of parameters within the default 100KB request size limit, causing elevated CPU and memory usage. This can lead to service slowdown or partial outages under sustained malicious traffic. This issue is addressed in version 2.2.1.

Product(s) Impacted

Vendor Product Versions
Body-parser
  • Body-parser
  • 2.2.0, 2.2.1

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-400
Uncontrolled Resource Consumption
The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a body-parser body-parser 2.2.0 / / / / / / /
a body-parser body-parser 2.2.1 / / / / / / /

CVSS Score

5.5 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: LOW
  • Exploit Maturity: PROOF_OF_CONCEPT
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:L/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:Y/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: Nov. 24, 2025, 7:15 p.m.
Last Modified: Nov. 25, 2025, 10:16 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

ce714d77-add3-4f53-aff5-83d477b104bb

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.