GHSA-4FVR-RGM6-GQMC

Vulnerability from github – Published: 2026-06-15 20:10 – Updated: 2026-06-15 20:10
VLAI
Summary
aiohttp: HTTP/1 Pipelined Requests Queue Without Limit
Details

Summary

No limit was present on the number of pipelined requests that could be queued.

Impact

An attacker may be able to use pipelined requests to use excessive amounts of memory, potentially leading to DoS.


Patch: https://github.com/aio-libs/aiohttp/commit/dfdfa9d5aad5d21f91c79fb2ceeba0f8046cb6cf

Show details on source website

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 3.14.0"
      },
      "package": {
        "ecosystem": "PyPI",
        "name": "aiohttp"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.14.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-54273"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-06-15T20:10:32Z",
    "nvd_published_at": null,
    "severity": "MODERATE"
  },
  "details": "### Summary\n\nNo limit was present on the number of pipelined requests that could be queued.\n\n### Impact\n\nAn attacker may be able to use pipelined requests to use excessive amounts of memory, potentially leading to DoS.\n\n-----\n\nPatch: https://github.com/aio-libs/aiohttp/commit/dfdfa9d5aad5d21f91c79fb2ceeba0f8046cb6cf",
  "id": "GHSA-4fvr-rgm6-gqmc",
  "modified": "2026-06-15T20:10:32Z",
  "published": "2026-06-15T20:10:32Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/aio-libs/aiohttp/security/advisories/GHSA-4fvr-rgm6-gqmc"
    },
    {
      "type": "WEB",
      "url": "https://github.com/aio-libs/aiohttp/commit/dfdfa9d5aad5d21f91c79fb2ceeba0f8046cb6cf"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/aio-libs/aiohttp"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "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",
      "type": "CVSS_V4"
    }
  ],
  "summary": "aiohttp: HTTP/1 Pipelined Requests Queue Without Limit"
}


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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

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