CNVD-2017-37860

Vulnerability from cnvd - Published: 2017-12-22
VLAI
Title
IBM RPA with Automation Anywhere跨站脚本漏洞
Description
IBM Robotic Process Automation with Automation Anywhere是美国IBM公司和Automation Anywhere共同开发的一套流程自动化解决方案。 IBM Robotic Process Automation with Automation Anywhere 10.0.0.0版本中跨站脚本漏洞,该漏洞源于程序未能正确的过滤用户提交的输入。远程攻击者可利用该漏洞向Web UI中注入任意的JavaScript代码。
Severity
Patch Name
IBM RPA with Automation Anywhere跨站脚本漏洞的补丁
Patch Description
IBM Robotic Process Automation with Automation Anywhere是美国IBM公司和Automation Anywhere共同开发的一套流程自动化解决方案。 IBM Robotic Process Automation with Automation Anywhere 10.0.0.0版本中跨站脚本漏洞,该漏洞源于程序未能正确的过滤用户提交的输入。远程攻击者可利用该漏洞向Web UI中注入任意的JavaScript代码。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

目前厂商已发布升级补丁以修复漏洞,补丁获取链接: http://www-01.ibm.com/support/docview.wss?uid=swg22011185

Reference
https://www.securityfocus.com/bid/102217
Impacted products
Name
IBM Robotic Process Automation with Automation Anywhere 10.0.0.0
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2017-1751"
    }
  },
  "description": "IBM Robotic Process Automation with Automation Anywhere\u662f\u7f8e\u56fdIBM\u516c\u53f8\u548cAutomation Anywhere\u5171\u540c\u5f00\u53d1\u7684\u4e00\u5957\u6d41\u7a0b\u81ea\u52a8\u5316\u89e3\u51b3\u65b9\u6848\u3002\r\n\r\nIBM Robotic Process Automation with Automation Anywhere 10.0.0.0\u7248\u672c\u4e2d\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u7a0b\u5e8f\u672a\u80fd\u6b63\u786e\u7684\u8fc7\u6ee4\u7528\u6237\u63d0\u4ea4\u7684\u8f93\u5165\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5411Web UI\u4e2d\u6ce8\u5165\u4efb\u610f\u7684JavaScript\u4ee3\u7801\u3002",
  "discovererName": "IBM",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6f0f\u6d1e\uff0c\u8865\u4e01\u83b7\u53d6\u94fe\u63a5\uff1a\r\nhttp://www-01.ibm.com/support/docview.wss?uid=swg22011185",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2017-37860",
  "openTime": "2017-12-22",
  "patchDescription": "IBM Robotic Process Automation with Automation Anywhere\u662f\u7f8e\u56fdIBM\u516c\u53f8\u548cAutomation Anywhere\u5171\u540c\u5f00\u53d1\u7684\u4e00\u5957\u6d41\u7a0b\u81ea\u52a8\u5316\u89e3\u51b3\u65b9\u6848\u3002\r\n\r\nIBM Robotic Process Automation with Automation Anywhere 10.0.0.0\u7248\u672c\u4e2d\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u7a0b\u5e8f\u672a\u80fd\u6b63\u786e\u7684\u8fc7\u6ee4\u7528\u6237\u63d0\u4ea4\u7684\u8f93\u5165\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5411Web UI\u4e2d\u6ce8\u5165\u4efb\u610f\u7684JavaScript\u4ee3\u7801\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": "IBM RPA with Automation Anywhere\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "IBM Robotic Process Automation with Automation Anywhere 10.0.0.0"
  },
  "referenceLink": "https://www.securityfocus.com/bid/102217",
  "serverity": "\u4e2d",
  "submitTime": "2017-12-20",
  "title": "IBM RPA with Automation Anywhere\u8de8\u7ad9\u811a\u672c\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.
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  • 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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