FKIE_CVE-2019-20634

Vulnerability from fkie_nvd - Published: 2020-03-30 21:15 - Updated: 2024-11-21 04:38
Summary
An issue was discovered in Proofpoint Email Protection through 2019-09-08. By collecting scores from Proofpoint email headers, it is possible to build a copy-cat Machine Learning Classification model and extract insights from this model. The insights gathered allow an attacker to craft emails that receive preferable scores, with a goal of delivering malicious emails.
Impacted products
Vendor Product Version
proofpoint email_protection *

{
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:proofpoint:email_protection:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "38135AED-BADF-4BCB-9314-320175D5C61A",
              "versionEndIncluding": "2019-09-08",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "An issue was discovered in Proofpoint Email Protection through 2019-09-08. By collecting scores from Proofpoint email headers, it is possible to build a copy-cat Machine Learning Classification model and extract insights from this model. The insights gathered allow an attacker to craft emails that receive preferable scores, with a goal of delivering malicious emails."
    },
    {
      "lang": "es",
      "value": "Se detect\u00f3 un problema en Proofpoint Email Protection hasta el 08-09-2019. Mediante la recopilaci\u00f3n de puntajes de los encabezados de correo electr\u00f3nico de Proofpoint, es posible construir un modelo Machine Learning Classification copy-cat y extraer informaci\u00f3n de este modelo. Los conocimientos capturados permiten a un atacante dise\u00f1ar correos electr\u00f3nicos que reciban puntajes preferenciales, con el prop\u00f3sito de entregar correos electr\u00f3nicos maliciosos."
    }
  ],
  "id": "CVE-2019-20634",
  "lastModified": "2024-11-21T04:38:55.730",
  "metrics": {
    "cvssMetricV2": [
      {
        "acInsufInfo": false,
        "baseSeverity": "MEDIUM",
        "cvssData": {
          "accessComplexity": "MEDIUM",
          "accessVector": "NETWORK",
          "authentication": "NONE",
          "availabilityImpact": "NONE",
          "baseScore": 4.3,
          "confidentialityImpact": "PARTIAL",
          "integrityImpact": "NONE",
          "vectorString": "AV:N/AC:M/Au:N/C:P/I:N/A:N",
          "version": "2.0"
        },
        "exploitabilityScore": 8.6,
        "impactScore": 2.9,
        "obtainAllPrivilege": false,
        "obtainOtherPrivilege": false,
        "obtainUserPrivilege": false,
        "source": "nvd@nist.gov",
        "type": "Primary",
        "userInteractionRequired": false
      }
    ],
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "HIGH",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 3.7,
          "baseSeverity": "LOW",
          "confidentialityImpact": "LOW",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 2.2,
        "impactScore": 1.4,
        "source": "cve@mitre.org",
        "type": "Secondary"
      },
      {
        "cvssData": {
          "attackComplexity": "HIGH",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 3.7,
          "baseSeverity": "LOW",
          "confidentialityImpact": "LOW",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:N/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 2.2,
        "impactScore": 1.4,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ]
  },
  "published": "2020-03-30T21:15:12.373",
  "references": [
    {
      "source": "cve@mitre.org",
      "tags": [
        "Third Party Advisory"
      ],
      "url": "https://github.com/moohax/Proof-Pudding"
    },
    {
      "source": "cve@mitre.org",
      "tags": [
        "Third Party Advisory"
      ],
      "url": "https://github.com/moohax/Talks/blob/master/slides/DerbyCon19.pdf"
    },
    {
      "source": "cve@mitre.org",
      "tags": [
        "Vendor Advisory"
      ],
      "url": "https://www.proofpoint.com/us/security/CVE-2019-20634"
    },
    {
      "source": "cve@mitre.org",
      "tags": [
        "Vendor Advisory"
      ],
      "url": "https://www.proofpoint.com/us/security/security-advisories/pfpt-sn-2020-0001"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "url": "https://atlas.mitre.org/studies/AML.CS0008"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Third Party Advisory"
      ],
      "url": "https://github.com/moohax/Proof-Pudding"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Third Party Advisory"
      ],
      "url": "https://github.com/moohax/Talks/blob/master/slides/DerbyCon19.pdf"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Vendor Advisory"
      ],
      "url": "https://www.proofpoint.com/us/security/CVE-2019-20634"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Vendor Advisory"
      ],
      "url": "https://www.proofpoint.com/us/security/security-advisories/pfpt-sn-2020-0001"
    }
  ],
  "sourceIdentifier": "cve@mitre.org",
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-697"
        }
      ],
      "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

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.


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