FKIE_CVE-2018-11309

Vulnerability from fkie_nvd - Published: 2018-05-28 16:29 - Updated: 2026-06-17 01:35
Summary
Blind SQL injection in coupon_code in the MemberMouse plugin 2.2.8 and prior for WordPress allows an unauthenticated attacker to dump the WordPress MySQL database via an applyCoupon action in an admin-ajax.php request.
Impacted products
Vendor Product Version
membermouse membermouse *

{
  "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:membermouse:membermouse:*:*:*:*:*:wordpress:*:*",
              "matchCriteriaId": "F610DF00-B60A-4886-8BE3-E8DB45E8DDD9",
              "versionEndExcluding": "2.2.8",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "Blind SQL injection in coupon_code in the MemberMouse plugin 2.2.8 and prior for WordPress allows an unauthenticated attacker to dump the WordPress MySQL database via an applyCoupon action in an admin-ajax.php request."
    },
    {
      "lang": "es",
      "value": "Se ha descubierto un problema en Moodle 3.x. Si un profesor crea una pregunta \"Calculated\", puede provocar intencionadamente la ejecuci\u00f3n remota de c\u00f3digo en el servidor. Esto tambi\u00e9n se conoce como \"eval injection\"."
    }
  ],
  "id": "CVE-2018-11309",
  "lastModified": "2026-06-17T01:35:41.947",
  "metrics": {
    "cvssMetricV2": [
      {
        "acInsufInfo": false,
        "baseSeverity": "HIGH",
        "cvssData": {
          "accessComplexity": "LOW",
          "accessVector": "NETWORK",
          "authentication": "NONE",
          "availabilityImpact": "PARTIAL",
          "baseScore": 7.5,
          "confidentialityImpact": "PARTIAL",
          "integrityImpact": "PARTIAL",
          "vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
          "version": "2.0"
        },
        "exploitabilityScore": 10.0,
        "impactScore": 6.4,
        "obtainAllPrivilege": false,
        "obtainOtherPrivilege": false,
        "obtainUserPrivilege": false,
        "source": "nvd@nist.gov",
        "type": "Primary",
        "userInteractionRequired": false
      }
    ],
    "cvssMetricV30": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 9.8,
          "baseSeverity": "CRITICAL",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
          "version": "3.0"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 5.9,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ]
  },
  "published": "2018-05-28T16:29:00.217",
  "references": [
    {
      "source": "cve@mitre.org",
      "tags": [
        "Exploit",
        "Third Party Advisory"
      ],
      "url": "https://blog.riccardoancarani.it/cve-2018-11309-blind-sql-injection-in-membermouse-plugin/"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Exploit",
        "Third Party Advisory"
      ],
      "url": "https://blog.riccardoancarani.it/cve-2018-11309-blind-sql-injection-in-membermouse-plugin/"
    }
  ],
  "sourceIdentifier": "cve@mitre.org",
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-89"
        }
      ],
      "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.

Sightings

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