FKIE_CVE-2015-8280

Vulnerability from fkie_nvd - Published: 2016-01-15 03:59 - Updated: 2026-06-17 00:34
Severity
7.5 (High) - CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
Summary
Web Viewer 1.0.0.193 on Samsung SRN-1670D devices allows remote attackers to discover credentials by reading detailed error messages.
References
cret@cert.orghttps://www.kb.cert.org/vuls/id/913000Third Party Advisory, US Government Resource
af854a3a-2127-422b-91ae-364da2661108https://www.kb.cert.org/vuls/id/913000Third Party Advisory, US Government Resource
Impacted products
Vendor Product Version
samsung web_viewer *
To clipboard 

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "n/a",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
          ]
        }
      ],
      "source": "cret@cert.org"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:samsung:web_viewer:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "B7EDA3C8-7E89-4BB7-818C-21DEA872BB95",
              "versionEndIncluding": "1.0.0.193",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "Web Viewer 1.0.0.193 on Samsung SRN-1670D devices allows remote attackers to discover credentials by reading detailed error messages."
    },
    {
      "lang": "es",
      "value": "Web Viewer 1.0.0.193 en dispositivos Samsung SRN-1670D permite a atacantes remotos descubrir credenciales leyendo mensajes de error detallados."
    }
  ],
  "id": "CVE-2015-8280",
  "lastModified": "2026-06-17T00:34:15.357",
  "metrics": {
    "cvssMetricV2": [
      {
        "acInsufInfo": false,
        "baseSeverity": "MEDIUM",
        "cvssData": {
          "accessComplexity": "LOW",
          "accessVector": "NETWORK",
          "authentication": "NONE",
          "availabilityImpact": "NONE",
          "baseScore": 5.0,
          "confidentialityImpact": "PARTIAL",
          "integrityImpact": "NONE",
          "vectorString": "AV:N/AC:L/Au:N/C:P/I:N/A:N",
          "version": "2.0"
        },
        "exploitabilityScore": 10.0,
        "impactScore": 2.9,
        "obtainAllPrivilege": false,
        "obtainOtherPrivilege": false,
        "obtainUserPrivilege": false,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ],
    "cvssMetricV30": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 7.5,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
          "version": "3.0"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 3.6,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ]
  },
  "published": "2016-01-15T03:59:11.653",
  "references": [
    {
      "source": "cret@cert.org",
      "tags": [
        "Third Party Advisory",
        "US Government Resource"
      ],
      "url": "https://www.kb.cert.org/vuls/id/913000"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Third Party Advisory",
        "US Government Resource"
      ],
      "url": "https://www.kb.cert.org/vuls/id/913000"
    }
  ],
  "sourceIdentifier": "cret@cert.org",
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-200"
        }
      ],
      "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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Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
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  • 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.



Related by attack behaviour

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.