CNVD-2019-36475

Vulnerability from cnvd - Published: 2019-10-22
VLAI
Title
NETGEAR JNR1010跨站请求伪造漏洞
Description
NETGEAR JNR1010是美国网件(NETGEAR)公司的一款无线路由器。 NETGEAR JNR1010 1.0.0.32之前版本中存在跨站请求伪造漏洞,该漏洞源于WEB应用未充分验证请求是否来自可信用户,攻击者可利用该漏洞通过受影响客户端向服务器发送非预期的请求。
Severity
中
Patch Name
NETGEAR JNR1010跨站请求伪造漏洞的补丁
Patch Description
NETGEAR JNR1010是美国网件(NETGEAR)公司的一款无线路由器。 NETGEAR JNR1010 1.0.0.32之前版本中存在跨站请求伪造漏洞,该漏洞源于WEB应用未充分验证请求是否来自可信用户,攻击者可利用该漏洞通过受影响客户端向服务器发送非预期的请求。目前,供应商发布了安全公告及相关补丁信息,修复了此漏洞。
Formal description

厂商已发布了漏洞修复程序,请及时关注更新: https://kb.netgear.com/30177/JNR1010-Firmware-Version-1-0-0-32

Reference
https://github.com/cybersecurityworks/Disclosed/issues/13 https://lists.openwall.net/full-disclosure/2016/01/11/4
Impacted products
Name
Netgear JNR1010 <1.0.0.32
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2016-11015"
    }
  },
  "description": "NETGEAR JNR1010\u662f\u7f8e\u56fd\u7f51\u4ef6\uff08NETGEAR\uff09\u516c\u53f8\u7684\u4e00\u6b3e\u65e0\u7ebf\u8def\u7531\u5668\u3002\n\nNETGEAR JNR1010 1.0.0.32\u4e4b\u524d\u7248\u672c\u4e2d\u5b58\u5728\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eWEB\u5e94\u7528\u672a\u5145\u5206\u9a8c\u8bc1\u8bf7\u6c42\u662f\u5426\u6765\u81ea\u53ef\u4fe1\u7528\u6237\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u901a\u8fc7\u53d7\u5f71\u54cd\u5ba2\u6237\u7aef\u5411\u670d\u52a1\u5668\u53d1\u9001\u975e\u9884\u671f\u7684\u8bf7\u6c42\u3002",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://kb.netgear.com/30177/JNR1010-Firmware-Version-1-0-0-32",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2019-36475",
  "openTime": "2019-10-22",
  "patchDescription": "NETGEAR JNR1010\u662f\u7f8e\u56fd\u7f51\u4ef6\uff08NETGEAR\uff09\u516c\u53f8\u7684\u4e00\u6b3e\u65e0\u7ebf\u8def\u7531\u5668\u3002\r\n\r\nNETGEAR JNR1010 1.0.0.32\u4e4b\u524d\u7248\u672c\u4e2d\u5b58\u5728\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eWEB\u5e94\u7528\u672a\u5145\u5206\u9a8c\u8bc1\u8bf7\u6c42\u662f\u5426\u6765\u81ea\u53ef\u4fe1\u7528\u6237\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u901a\u8fc7\u53d7\u5f71\u54cd\u5ba2\u6237\u7aef\u5411\u670d\u52a1\u5668\u53d1\u9001\u975e\u9884\u671f\u7684\u8bf7\u6c42\u3002\u76ee\u524d\uff0c\u4f9b\u5e94\u5546\u53d1\u5e03\u4e86\u5b89\u5168\u516c\u544a\u53ca\u76f8\u5173\u8865\u4e01\u4fe1\u606f\uff0c\u4fee\u590d\u4e86\u6b64\u6f0f\u6d1e\u3002",
  "patchName": "NETGEAR JNR1010\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Netgear  JNR1010 \u003c1.0.0.32"
  },
  "referenceLink": "https://github.com/cybersecurityworks/Disclosed/issues/13\r\nhttps://lists.openwall.net/full-disclosure/2016/01/11/4",
  "serverity": "\u4e2d",
  "submitTime": "2019-10-18",
  "title": "NETGEAR JNR1010\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\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.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • 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.

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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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