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CNVD-2018-10302

Vulnerability from cnvd - Published: 2018-05-25
VLAI
Title
iBall Baton ADSL2+身份验证绕过漏洞
Description
iBall Baton ADSL2+ Home Router是印度iBall公司的一款路由器。 iBall Baton ADSL2+ Home Router FW_iB-LR7011A_1.0.2版本中存在身份验证绕过漏洞。攻击者可借助通过构建带有.cgi扩展的URL利用该漏洞登录管理面板。
Severity
Formal description

厂商尚未提供漏洞修复方案,请关注厂商主页更新: https://www.iball.co.in/home

Reference
https://cxsecurity.com/cveshow/CVE-2017-14244/
Impacted products
Name
iBall Baton ADSL2+ Home Router FW_iB-LR7011A_1.0.2
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2017-14244",
      "cveUrl": "http://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2017-14244"
    }
  },
  "description": "iBall Baton ADSL2+ Home Router\u662f\u5370\u5ea6iBall\u516c\u53f8\u7684\u4e00\u6b3e\u8def\u7531\u5668\u3002\r\n\r\niBall Baton ADSL2+ Home Router FW_iB-LR7011A_1.0.2\u7248\u672c\u4e2d\u5b58\u5728\u8eab\u4efd\u9a8c\u8bc1\u7ed5\u8fc7\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u501f\u52a9\u901a\u8fc7\u6784\u5efa\u5e26\u6709.cgi\u6269\u5c55\u7684URL\u5229\u7528\u8be5\u6f0f\u6d1e\u767b\u5f55\u7ba1\u7406\u9762\u677f\u3002",
  "discovererName": "Unknow",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0:\r\nhttps://www.iball.co.in/home",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2018-10302",
  "openTime": "2018-05-25",
  "products": {
    "product": "iBall Baton ADSL2+ Home Router FW_iB-LR7011A_1.0.2"
  },
  "referenceLink": "https://cxsecurity.com/cveshow/CVE-2017-14244/",
  "serverity": "\u9ad8",
  "submitTime": "2018-05-21",
  "title": "iBall Baton ADSL2+\u8eab\u4efd\u9a8c\u8bc1\u7ed5\u8fc7\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

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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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