CVE-2026-54277

June 22, 2026, 6:28 p.m.

6.6
Medium

Description

AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Prior to 3.14.1, it is possible to bypass the max_line_size check in parts of an HTTP request in the C parser. If using the optimised C parser (the default in pre-built wheels), then an attacker may be able to send oversized lines through the HTTP parser and use an excessive amount of memory, potentially leading to DoS. This vulnerability is fixed in 3.14.1.

Product(s) Impacted

Vendor Product Versions
Aiohttp
  • Aiohttp
  • <3.14.1

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-770
Allocation of Resources Without Limits or Throttling
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any restrictions on the size or number of resources that can be allocated, in violation of the intended security policy for that actor.

*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 <3.14.1 / / / / / / /

CVSS Score

6.6 / 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: HIGH
  • Exploit Maturity: UNREPORTED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/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, 6:28 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.