CNVD-2019-30424

Vulnerability from cnvd - Published: 2019-08-30
VLAI
Title
D-Link DIR-823G访问控制错误漏洞
Description
D-Link DIR-823G是中国台湾友讯(D-Link)公司的一款无线路由器。 D-Link DIR-823G存在访问控制错误漏洞。攻击者可利用该漏洞劫持WLAN中所有客户端的DNS服务配置信息。
Severity
Formal description

厂商尚未提供漏洞修复方案,请关注厂商主页更新: http://www.dlink.com/

Reference
https://nvd.nist.gov/vuln/detail/CVE-2019-7390
Impacted products
Name
D-Link DIR-823G 1.02B03
Show details on source website

{
  "bids": {
    "bid": {
      "bidNumber": "106855"
    }
  },
  "cves": {
    "cve": {
      "cveNumber": "CVE-2019-7390",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2019-7390"
    }
  },
  "description": "D-Link DIR-823G\u662f\u4e2d\u56fd\u53f0\u6e7e\u53cb\u8baf\uff08D-Link\uff09\u516c\u53f8\u7684\u4e00\u6b3e\u65e0\u7ebf\u8def\u7531\u5668\u3002\n\nD-Link DIR-823G\u5b58\u5728\u8bbf\u95ee\u63a7\u5236\u9519\u8bef\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u52ab\u6301WLAN\u4e2d\u6240\u6709\u5ba2\u6237\u7aef\u7684DNS\u670d\u52a1\u914d\u7f6e\u4fe1\u606f\u3002",
  "discovererName": "David Chen",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0\uff1a\r\nhttp://www.dlink.com/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2019-30424",
  "openTime": "2019-08-30",
  "products": {
    "product": "D-Link DIR-823G 1.02B03"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2019-7390",
  "serverity": "\u4e2d",
  "submitTime": "2019-07-25",
  "title": "D-Link DIR-823G\u8bbf\u95ee\u63a7\u5236\u9519\u8bef\u6f0f\u6d1e"
}



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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.
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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.


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