FKIE_CVE-2019-20857

Vulnerability from fkie_nvd - Published: 2020-06-19 15:15 - Updated: 2026-06-17 02:31
Summary
An issue was discovered in Mattermost Server before 5.16.0. It allows attackers to cause a denial of service (markdown renderer hang) via many backtick characters.
Impacted products
Vendor Product Version
mattermost mattermost_server *

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "n/a",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
          ]
        }
      ],
      "source": "cve@mitre.org"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:mattermost:mattermost_server:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "1AB597A8-86FA-4573-A4BB-CDD4FBE3E048",
              "versionEndExcluding": "5.16.0",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "An issue was discovered in Mattermost Server before 5.16.0. It allows attackers to cause a denial of service (markdown renderer hang) via many backtick characters."
    },
    {
      "lang": "es",
      "value": "Se detect\u00f3 un problema en Mattermost Server versiones anteriores a 5.16.0. Permite a atacantes causar una denegaci\u00f3n de servicio (suspensi\u00f3n del renderizador markdown) por medio de muchos caracteres backtick"
    }
  ],
  "id": "CVE-2019-20857",
  "lastModified": "2026-06-17T02:31:19.713",
  "metrics": {
    "cvssMetricV2": [
      {
        "acInsufInfo": false,
        "baseSeverity": "MEDIUM",
        "cvssData": {
          "accessComplexity": "LOW",
          "accessVector": "NETWORK",
          "authentication": "NONE",
          "availabilityImpact": "PARTIAL",
          "baseScore": 5.0,
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
          "version": "2.0"
        },
        "exploitabilityScore": 10.0,
        "impactScore": 2.9,
        "obtainAllPrivilege": false,
        "obtainOtherPrivilege": false,
        "obtainUserPrivilege": false,
        "source": "nvd@nist.gov",
        "type": "Primary",
        "userInteractionRequired": false
      }
    ],
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 7.5,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 3.6,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ]
  },
  "published": "2020-06-19T15:15:10.570",
  "references": [
    {
      "source": "cve@mitre.org",
      "tags": [
        "Vendor Advisory"
      ],
      "url": "https://mattermost.com/security-updates/"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Vendor Advisory"
      ],
      "url": "https://mattermost.com/security-updates/"
    }
  ],
  "sourceIdentifier": "cve@mitre.org",
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "NVD-CWE-noinfo"
        }
      ],
      "source": "nvd@nist.gov",
      "type": "Primary"
    }
  ]
}



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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.

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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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