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CNVD-2021-99269

Vulnerability from cnvd - Published: 2021-12-13
VLAI
Title
Yellowfin不安全直接对象引用漏洞
Description
Yellowfin是一款商业智能自动化分析、跨厂商叙事和协作软件套件。 Yellowfin 9.6.1之前版本存在不安全直接对象引用漏洞。攻击者可通过向页面“MIImage.i4”发送特制HTTP GET请求利用该漏洞枚举和下载已上传的图像。
Severity
Patch Name
Yellowfin不安全直接对象引用漏洞的补丁
Patch Description
Yellowfin是一款商业智能自动化分析、跨厂商叙事和协作软件套件。 Yellowfin 9.6.1之前版本存在不安全直接对象引用漏洞。攻击者可通过向页面“MIImage.i4”发送特制HTTP GET请求利用该漏洞枚举和下载已上传的图像。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://wiki.yellowfinbi.com/display/yfcurrent/Release+Notes+for+Yellowfin+9#ReleaseNotesforYellowfin9-Yellowfin9.6

Reference
https://nvd.nist.gov/vuln/detail/CVE-2021-36389
Impacted products
Name
Yellowfin Yellowfin <9.6.1
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-36389",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-36389"
    }
  },
  "description": "Yellowfin\u662f\u4e00\u6b3e\u5546\u4e1a\u667a\u80fd\u81ea\u52a8\u5316\u5206\u6790\u3001\u8de8\u5382\u5546\u53d9\u4e8b\u548c\u534f\u4f5c\u8f6f\u4ef6\u5957\u4ef6\u3002\n\nYellowfin 9.6.1\u4e4b\u524d\u7248\u672c\u5b58\u5728\u4e0d\u5b89\u5168\u76f4\u63a5\u5bf9\u8c61\u5f15\u7528\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u5411\u9875\u9762\u201cMIImage.i4\u201d\u53d1\u9001\u7279\u5236HTTP GET\u8bf7\u6c42\u5229\u7528\u8be5\u6f0f\u6d1e\u679a\u4e3e\u548c\u4e0b\u8f7d\u5df2\u4e0a\u4f20\u7684\u56fe\u50cf\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://wiki.yellowfinbi.com/display/yfcurrent/Release+Notes+for+Yellowfin+9#ReleaseNotesforYellowfin9-Yellowfin9.6",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-99269",
  "openTime": "2021-12-13",
  "patchDescription": "Yellowfin\u662f\u4e00\u6b3e\u5546\u4e1a\u667a\u80fd\u81ea\u52a8\u5316\u5206\u6790\u3001\u8de8\u5382\u5546\u53d9\u4e8b\u548c\u534f\u4f5c\u8f6f\u4ef6\u5957\u4ef6\u3002\r\n\r\nYellowfin 9.6.1\u4e4b\u524d\u7248\u672c\u5b58\u5728\u4e0d\u5b89\u5168\u76f4\u63a5\u5bf9\u8c61\u5f15\u7528\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u5411\u9875\u9762\u201cMIImage.i4\u201d\u53d1\u9001\u7279\u5236HTTP GET\u8bf7\u6c42\u5229\u7528\u8be5\u6f0f\u6d1e\u679a\u4e3e\u548c\u4e0b\u8f7d\u5df2\u4e0a\u4f20\u7684\u56fe\u50cf\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": "Yellowfin\u4e0d\u5b89\u5168\u76f4\u63a5\u5bf9\u8c61\u5f15\u7528\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Yellowfin Yellowfin \u003c9.6.1"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2021-36389",
  "serverity": "\u4e2d",
  "submitTime": "2021-10-15",
  "title": "Yellowfin\u4e0d\u5b89\u5168\u76f4\u63a5\u5bf9\u8c61\u5f15\u7528\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

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.

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Detection rules are retrieved from Rulezet.

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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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