GHSA-4J72-4C44-2FXP

Vulnerability from github – Published: 2022-05-01 17:56 – Updated: 2022-05-01 17:56
VLAI
Details

Heap-based buffer overflow in the LDAP server in IBM Lotus Domino before 6.5.6 and 7.x before 7.0.2 FP1 allows remote attackers to cause a denial of service (crash) via a long, malformed DN request, which causes only the lower 16 bits of the string length to be used in memory allocation.

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{
  "affected": [],
  "aliases": [
    "CVE-2007-1739"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2007-03-28T22:19:00Z",
    "severity": "HIGH"
  },
  "details": "Heap-based buffer overflow in the LDAP server in IBM Lotus Domino before 6.5.6 and 7.x before 7.0.2 FP1 allows remote attackers to cause a denial of service (crash) via a long, malformed DN request, which causes only the lower 16 bits of the string length to be used in memory allocation.",
  "id": "GHSA-4j72-4c44-2fxp",
  "modified": "2022-05-01T17:56:38Z",
  "published": "2022-05-01T17:56:38Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2007-1739"
    },
    {
      "type": "WEB",
      "url": "https://exchange.xforce.ibmcloud.com/vulnerabilities/33278"
    },
    {
      "type": "WEB",
      "url": "http://labs.idefense.com/intelligence/vulnerabilities/display.php?id=494"
    },
    {
      "type": "WEB",
      "url": "http://secunia.com/advisories/24633"
    },
    {
      "type": "WEB",
      "url": "http://www-1.ibm.com/support/docview.wss?uid=swg21257248"
    },
    {
      "type": "WEB",
      "url": "http://www.kb.cert.org/vuls/id/927988"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/23173"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/23174"
    },
    {
      "type": "WEB",
      "url": "http://www.securitytracker.com/id?1017825"
    },
    {
      "type": "WEB",
      "url": "http://www.vupen.com/english/advisories/2007/1133"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}



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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

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