GSD-2016-5011

Vulnerability from gsd - Updated: 2023-12-13 01:21
Details
The parse_dos_extended function in partitions/dos.c in the libblkid library in util-linux allows physically proximate attackers to cause a denial of service (memory consumption) via a crafted MSDOS partition table with an extended partition boot record at zero offset.
Aliases
Aliases

{
  "GSD": {
    "alias": "CVE-2016-5011",
    "description": "The parse_dos_extended function in partitions/dos.c in the libblkid library in util-linux allows physically proximate attackers to cause a denial of service (memory consumption) via a crafted MSDOS partition table with an extended partition boot record at zero offset.",
    "id": "GSD-2016-5011",
    "references": [
      "https://www.suse.com/security/cve/CVE-2016-5011.html",
      "https://access.redhat.com/errata/RHSA-2016:2605",
      "https://advisories.mageia.org/CVE-2016-5011.html",
      "https://linux.oracle.com/cve/CVE-2016-5011.html",
      "https://ubuntu.com/security/CVE-2016-5011"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
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        "CVE-2016-5011"
      ],
      "details": "The parse_dos_extended function in partitions/dos.c in the libblkid library in util-linux allows physically proximate attackers to cause a denial of service (memory consumption) via a crafted MSDOS partition table with an extended partition boot record at zero offset.",
      "id": "GSD-2016-5011",
      "modified": "2023-12-13T01:21:25.639200Z",
      "schema_version": "1.4.0"
    }
  },
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          "cvssV2": {
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            "accessVector": "LOCAL",
            "authentication": "NONE",
            "availabilityImpact": "COMPLETE",
            "baseScore": 4.9,
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:C",
            "version": "2.0"
          },
          "exploitabilityScore": 3.9,
          "impactScore": 6.9,
          "obtainAllPrivilege": false,
          "obtainOtherPrivilege": false,
          "obtainUserPrivilege": false,
          "severity": "MEDIUM",
          "userInteractionRequired": false
        },
        "baseMetricV3": {
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            "attackVector": "PHYSICAL",
            "availabilityImpact": "HIGH",
            "baseScore": 4.6,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:P/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
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          "exploitabilityScore": 0.9,
          "impactScore": 3.6
        }
      },
      "lastModifiedDate": "2020-09-11T15:22Z",
      "publishedDate": "2017-04-11T15:59Z"
    }
  }
}



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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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