GHSA-F37Q-Q7P2-CCFC

Vulnerability from github – Published: 2022-04-14 00:00 – Updated: 2022-04-26 13:05
VLAI
Summary
Resource exhaustion in Mattermost
Details

The image proxy component in Mattermost version 6.4.1 and earlier allocates memory for multiple copies of a proxied image, which allows an authenticated attacker to crash the server via links to very large image files.

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "Go",
        "name": "github.com/mattermost/mattermost-server/v6"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "6.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2022-1337"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-400",
      "CWE-770"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-04-26T13:05:37Z",
    "nvd_published_at": "2022-04-13T18:15:00Z",
    "severity": "MODERATE"
  },
  "details": "The image proxy component in Mattermost version 6.4.1 and earlier allocates memory for multiple copies of a proxied image, which allows an authenticated attacker to crash the server via links to very large image files.",
  "id": "GHSA-f37q-q7p2-ccfc",
  "modified": "2022-04-26T13:05:37Z",
  "published": "2022-04-14T00:00:17Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-1337"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/mattermost/mattermost-server"
    },
    {
      "type": "WEB",
      "url": "https://mattermost.com/security-updates"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Resource exhaustion in Mattermost"
}



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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

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Nomenclature

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Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.


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