FKIE_CVE-2022-1112

Vulnerability from fkie_nvd - Published: 2022-04-18 18:15 - Updated: 2024-11-21 06:40
Summary
The Autolinks WordPress plugin through 1.0.1 does not have CSRF check in place when updating its settings, and does not sanitise as well as escape them, which could allow attackers to perform Stored Cross-Site scripting against a logged in admin via a CSRF attack
Impacted products
Vendor Product Version
autolinks_project autolinks *

{
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:autolinks_project:autolinks:*:*:*:*:*:wordpress:*:*",
              "matchCriteriaId": "8C3733BA-B468-41B1-9C38-1AAE9A0FB4AC",
              "versionEndIncluding": "1.0.1",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "The Autolinks WordPress plugin through 1.0.1 does not have CSRF check in place when updating its settings, and does not sanitise as well as escape them, which could allow attackers to perform Stored Cross-Site scripting against a logged in admin via a CSRF attack"
    },
    {
      "lang": "es",
      "value": "El plugin Autolinks de WordPress versiones hasta 1.0.1, no presenta una comprobaci\u00f3n de tipo CSRF cuando actualiza sus ajustes, y no los sanea as\u00ed como los escapa, lo que podr\u00eda permitir a atacantes llevar a cabo ataques de tipo Cross-Site Scripting Almacenado contra un administrador conectado por medio de un ataque de tipo CSRF"
    }
  ],
  "id": "CVE-2022-1112",
  "lastModified": "2024-11-21T06:40:04.320",
  "metrics": {
    "cvssMetricV2": [
      {
        "acInsufInfo": false,
        "baseSeverity": "LOW",
        "cvssData": {
          "accessComplexity": "MEDIUM",
          "accessVector": "NETWORK",
          "authentication": "SINGLE",
          "availabilityImpact": "NONE",
          "baseScore": 3.5,
          "confidentialityImpact": "NONE",
          "integrityImpact": "PARTIAL",
          "vectorString": "AV:N/AC:M/Au:S/C:N/I:P/A:N",
          "version": "2.0"
        },
        "exploitabilityScore": 6.8,
        "impactScore": 2.9,
        "obtainAllPrivilege": false,
        "obtainOtherPrivilege": false,
        "obtainUserPrivilege": false,
        "source": "nvd@nist.gov",
        "type": "Primary",
        "userInteractionRequired": true
      }
    ],
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 5.4,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "LOW",
          "integrityImpact": "LOW",
          "privilegesRequired": "LOW",
          "scope": "CHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 2.3,
        "impactScore": 2.7,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ]
  },
  "published": "2022-04-18T18:15:09.117",
  "references": [
    {
      "source": "contact@wpscan.com",
      "tags": [
        "Exploit",
        "Third Party Advisory"
      ],
      "url": "https://wpscan.com/vulnerability/746c7cf2-0902-461a-a364-285505d73505"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Exploit",
        "Third Party Advisory"
      ],
      "url": "https://wpscan.com/vulnerability/746c7cf2-0902-461a-a364-285505d73505"
    }
  ],
  "sourceIdentifier": "contact@wpscan.com",
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-79"
        },
        {
          "lang": "en",
          "value": "CWE-352"
        }
      ],
      "source": "contact@wpscan.com",
      "type": "Secondary"
    }
  ]
}


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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

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
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