CNVD-2016-00169

Vulnerability from cnvd - Published: 2016-01-13
VLAI
Title
IBM Security QRadar SIEM目录遍历漏洞
Description
IBM Security QRadar SIEM是IBM公司的一套可对分散在整个网络中的数千个设备和应用中的日志源事件数据进行整合的解决方案。 IBM Security QRadar SIEM 7.2.5 Patch 6之前7.2.x版本中存在目录遍历漏洞。远程攻击者可借助特制的URL利用该漏洞读取任意文件。
Severity
Patch Name
IBM Security QRadar SIEM目录遍历漏洞的补丁
Patch Description
IBM Security QRadar SIEM是IBM公司的一套可对分散在整个网络中的数千个设备和应用中的日志源事件数据进行整合的解决方案。 IBM Security QRadar SIEM 7.2.5 Patch 6之前7.2.x版本中存在目录遍历漏洞。远程攻击者可借助特制的URL利用该漏洞读取任意文件。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

用户可参考如下供应商提供的安全公告获得补丁信息:
http://www-01.ibm.com/support/docview.wss?uid=swg21967647

Reference
http://www-01.ibm.com/support/docview.wss?uid=swg21967647
Impacted products
Name
IBM Security QRadar SIEM 7.2.x(<7.2.5 Patch 6)
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2015-2007"
    }
  },
  "description": "IBM Security QRadar SIEM\u662fIBM\u516c\u53f8\u7684\u4e00\u5957\u53ef\u5bf9\u5206\u6563\u5728\u6574\u4e2a\u7f51\u7edc\u4e2d\u7684\u6570\u5343\u4e2a\u8bbe\u5907\u548c\u5e94\u7528\u4e2d\u7684\u65e5\u5fd7\u6e90\u4e8b\u4ef6\u6570\u636e\u8fdb\u884c\u6574\u5408\u7684\u89e3\u51b3\u65b9\u6848\u3002\r\n\r\nIBM Security QRadar SIEM 7.2.5 Patch 6\u4e4b\u524d7.2.x\u7248\u672c\u4e2d\u5b58\u5728\u76ee\u5f55\u904d\u5386\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684URL\u5229\u7528\u8be5\u6f0f\u6d1e\u8bfb\u53d6\u4efb\u610f\u6587\u4ef6\u3002",
  "discovererName": "IBM",
  "formalWay": "\u7528\u6237\u53ef\u53c2\u8003\u5982\u4e0b\u4f9b\u5e94\u5546\u63d0\u4f9b\u7684\u5b89\u5168\u516c\u544a\u83b7\u5f97\u8865\u4e01\u4fe1\u606f\uff1a  \r\nhttp://www-01.ibm.com/support/docview.wss?uid=swg21967647",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2016-00169",
  "openTime": "2016-01-13",
  "patchDescription": "IBM Security QRadar SIEM\u662fIBM\u516c\u53f8\u7684\u4e00\u5957\u53ef\u5bf9\u5206\u6563\u5728\u6574\u4e2a\u7f51\u7edc\u4e2d\u7684\u6570\u5343\u4e2a\u8bbe\u5907\u548c\u5e94\u7528\u4e2d\u7684\u65e5\u5fd7\u6e90\u4e8b\u4ef6\u6570\u636e\u8fdb\u884c\u6574\u5408\u7684\u89e3\u51b3\u65b9\u6848\u3002\r\n\r\nIBM Security QRadar SIEM 7.2.5 Patch 6\u4e4b\u524d7.2.x\u7248\u672c\u4e2d\u5b58\u5728\u76ee\u5f55\u904d\u5386\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684URL\u5229\u7528\u8be5\u6f0f\u6d1e\u8bfb\u53d6\u4efb\u610f\u6587\u4ef6\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 Security QRadar SIEM\u76ee\u5f55\u904d\u5386\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "IBM Security QRadar SIEM 7.2.x(\u003c7.2.5 Patch 6)"
  },
  "referenceLink": "http://www-01.ibm.com/support/docview.wss?uid=swg21967647",
  "serverity": "\u4e2d",
  "submitTime": "2016-01-06",
  "title": "IBM Security QRadar SIEM\u76ee\u5f55\u904d\u5386\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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