CNVD-2021-101181

Vulnerability from cnvd - Published: 2021-12-21
VLAI
Title
ShinHer StudyOnline System跨站脚本漏洞
Description
ShinHer StudyOnline System是中国欣河(ShinHer)公司的一种校务系统。 ShinHer StudyOnline System存在跨站脚本漏洞,该漏洞源于ShinHer StudyOnline系统留言板的List Add功能不过滤标题参数中的特殊字符。攻击者可利用该漏洞使用用户权限登录后,可以注入JavaScript并执行存储的XSS攻击。
Severity
低
Patch Name
ShinHer StudyOnline System跨站脚本漏洞的补丁
Patch Description
ShinHer StudyOnline System是中国欣河(ShinHer)公司的一种校务系统。 ShinHer StudyOnline System存在跨站脚本漏洞,该漏洞源于ShinHer StudyOnline系统留言板的List Add功能不过滤标题参数中的特殊字符。攻击者可利用该漏洞使用用户权限登录后,可以注入JavaScript并执行存储的XSS攻击。 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,详情请关注厂商主页: https://www.twcert.org.tw/tw/cp-132-5199-61238-1.html

Reference
https://www.twcert.org.tw/tw/cp-132-5199-61238-1.html
Impacted products
Name
ShinHer StudyOnline System v2021
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-42329"
    }
  },
  "description": "ShinHer StudyOnline System\u662f\u4e2d\u56fd\u6b23\u6cb3\uff08ShinHer\uff09\u516c\u53f8\u7684\u4e00\u79cd\u6821\u52a1\u7cfb\u7edf\u3002\n\nShinHer StudyOnline System\u5b58\u5728\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eShinHer StudyOnline\u7cfb\u7edf\u7559\u8a00\u677f\u7684List Add\u529f\u80fd\u4e0d\u8fc7\u6ee4\u6807\u9898\u53c2\u6570\u4e2d\u7684\u7279\u6b8a\u5b57\u7b26\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u4f7f\u7528\u7528\u6237\u6743\u9650\u767b\u5f55\u540e\uff0c\u53ef\u4ee5\u6ce8\u5165JavaScript\u5e76\u6267\u884c\u5b58\u50a8\u7684XSS\u653b\u51fb\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6f0f\u6d1e\uff0c\u8be6\u60c5\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\uff1a\r\nhttps://www.twcert.org.tw/tw/cp-132-5199-61238-1.html",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-101181",
  "openTime": "2021-12-21",
  "patchDescription": "ShinHer StudyOnline System\u662f\u4e2d\u56fd\u6b23\u6cb3\uff08ShinHer\uff09\u516c\u53f8\u7684\u4e00\u79cd\u6821\u52a1\u7cfb\u7edf\u3002\r\n\r\nShinHer StudyOnline System\u5b58\u5728\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eShinHer StudyOnline\u7cfb\u7edf\u7559\u8a00\u677f\u7684List Add\u529f\u80fd\u4e0d\u8fc7\u6ee4\u6807\u9898\u53c2\u6570\u4e2d\u7684\u7279\u6b8a\u5b57\u7b26\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u4f7f\u7528\u7528\u6237\u6743\u9650\u767b\u5f55\u540e\uff0c\u53ef\u4ee5\u6ce8\u5165JavaScript\u5e76\u6267\u884c\u5b58\u50a8\u7684XSS\u653b\u51fb\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": "ShinHer StudyOnline System\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "ShinHer StudyOnline System v2021"
  },
  "referenceLink": "https://www.twcert.org.tw/tw/cp-132-5199-61238-1.html",
  "serverity": "\u4f4e",
  "submitTime": "2021-10-19",
  "title": "ShinHer StudyOnline System\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 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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