CVE-2026-50269

June 22, 2026, 7:17 p.m.

2.7
Low

Description

AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Prior to 3.14.0, attacker-controlled input included into multipart/payload headers can be used to modify a request to inject additional headers or similar. In the unlikely situation that an application is passing user-controlled strings into MultipartWriter.append(headers=...) or Payload.headers, then an attacker may be able to modify the request to inject headers or change the contents of the request. This vulnerability is fixed in 3.14.0.

Product(s) Impacted

Vendor Product Versions
Aiohttp
  • Aiohttp
  • <3.14.0

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-93
Improper Neutralization of CRLF Sequences ('CRLF Injection')
The product uses CRLF (carriage return line feeds) as a special element, e.g. to separate lines or records, but it does not neutralize or incorrectly neutralizes CRLF sequences from inputs.

*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 aiohttp aiohttp <3.14.0 / / / / / /

CVSS Score

2.7 / 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: LOW
  • Availability Impact: NONE
  • Exploit Maturity: UNREPORTED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N/E:U/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:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: June 22, 2026, 6:16 p.m.
Last Modified: June 22, 2026, 7:17 p.m.

Status : Undergoing Analysis

CVE is currently being analyzed by NVD staff, this process results in association of reference link tags, CVSS scores, CWE association, and CPE applicability statements.

More info

*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.