CNVD-2017-36170

Vulnerability from cnvd - Published: 2017-12-05
VLAI
Title
McAfee Network Data Loss Prevention跨站脚本漏洞(CNVD-2017-36170)
Description
McAfee Network Data Loss Prevention(NDLP)是美国McAfee公司的一套网络数据丢失防护软件。该软件能够防止无意或恶意泄露客户数据、员工信息和知识产权信息,以及未授权传输信息。 McAfee NDLP 9.3.x版本中存在跨站脚本漏洞。远程攻击者可通过实施跨站请求伪造攻击利用该漏洞查看保密信息。
Severity
中
Patch Name
McAfee Network Data Loss Prevention跨站脚本漏洞(CNVD-2017-36170)的补丁
Patch Description
McAfee Network Data Loss Prevention(NDLP)是美国McAfee公司的一套网络数据丢失防护软件。该软件能够防止无意或恶意泄露客户数据、员工信息和知识产权信息,以及未授权传输信息。 McAfee NDLP 9.3.x版本中存在跨站脚本漏洞。远程攻击者可通过实施跨站请求伪造攻击利用该漏洞查看保密信息。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

目前厂商已经发布了升级补丁以修复这个安全问题,请到厂商的主页下载: https://kc.mcafee.com/corporate/index?page=content&id=SB10198

Reference
http://www.securityfocus.com/bid/101628
Impacted products
Name
McAfee Network Data Loss Prevention 9.3.x
Show details on source website

{
  "bids": {
    "bid": {
      "bidNumber": "101628"
    }
  },
  "cves": {
    "cve": {
      "cveNumber": "CVE-2017-3933"
    }
  },
  "description": "McAfee Network Data Loss Prevention\uff08NDLP\uff09\u662f\u7f8e\u56fdMcAfee\u516c\u53f8\u7684\u4e00\u5957\u7f51\u7edc\u6570\u636e\u4e22\u5931\u9632\u62a4\u8f6f\u4ef6\u3002\u8be5\u8f6f\u4ef6\u80fd\u591f\u9632\u6b62\u65e0\u610f\u6216\u6076\u610f\u6cc4\u9732\u5ba2\u6237\u6570\u636e\u3001\u5458\u5de5\u4fe1\u606f\u548c\u77e5\u8bc6\u4ea7\u6743\u4fe1\u606f\uff0c\u4ee5\u53ca\u672a\u6388\u6743\u4f20\u8f93\u4fe1\u606f\u3002\r\n\r\nMcAfee NDLP 9.3.x\u7248\u672c\u4e2d\u5b58\u5728\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u5b9e\u65bd\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\u653b\u51fb\u5229\u7528\u8be5\u6f0f\u6d1e\u67e5\u770b\u4fdd\u5bc6\u4fe1\u606f\u3002",
  "discovererName": "State Bank Of India",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u7ecf\u53d1\u5e03\u4e86\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u8fd9\u4e2a\u5b89\u5168\u95ee\u9898\uff0c\u8bf7\u5230\u5382\u5546\u7684\u4e3b\u9875\u4e0b\u8f7d\uff1a\r\nhttps://kc.mcafee.com/corporate/index?page=content\u0026id=SB10198",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2017-36170",
  "openTime": "2017-12-05",
  "patchDescription": "McAfee Network Data Loss Prevention\uff08NDLP\uff09\u662f\u7f8e\u56fdMcAfee\u516c\u53f8\u7684\u4e00\u5957\u7f51\u7edc\u6570\u636e\u4e22\u5931\u9632\u62a4\u8f6f\u4ef6\u3002\u8be5\u8f6f\u4ef6\u80fd\u591f\u9632\u6b62\u65e0\u610f\u6216\u6076\u610f\u6cc4\u9732\u5ba2\u6237\u6570\u636e\u3001\u5458\u5de5\u4fe1\u606f\u548c\u77e5\u8bc6\u4ea7\u6743\u4fe1\u606f\uff0c\u4ee5\u53ca\u672a\u6388\u6743\u4f20\u8f93\u4fe1\u606f\u3002\r\n\r\nMcAfee NDLP 9.3.x\u7248\u672c\u4e2d\u5b58\u5728\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u5b9e\u65bd\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\u653b\u51fb\u5229\u7528\u8be5\u6f0f\u6d1e\u67e5\u770b\u4fdd\u5bc6\u4fe1\u606f\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": "McAfee Network Data Loss Prevention\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff08CNVD-2017-36170\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "McAfee Network Data Loss Prevention 9.3.x"
  },
  "referenceLink": "http://www.securityfocus.com/bid/101628",
  "serverity": "\u4e2d",
  "submitTime": "2017-11-01",
  "title": "McAfee Network Data Loss Prevention\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff08CNVD-2017-36170\uff09"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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

Author Source Type Date Other

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.

Loading…

Loading…

Loading…

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.


Loading…