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CNVD-2018-00230

Vulnerability from cnvd - Published: 2018-01-04
VLAI
Title
Jenkins跨站脚本漏洞(CNVD-2018-00230)
Description
Jenkins是一个用Java编写的开源的持续集成工具。 2.93及更早版本的Jenkins存在存储型跨站脚本漏洞。远程认证管理员可通过工作配置表单中的特制工具名利用该漏洞进行跨站脚本攻击。
Severity
Formal description

目前没有详细的解决方案提供: https://jenkins.io/

Reference
https://jenkins.io/security/advisory/2017-12-05/
Impacted products
Name
Jenkins CI Jenkins <=2.93
Show details on source website

{
  "bids": {
    "bid": {
      "bidNumber": "102130"
    }
  },
  "cves": {
    "cve": {
      "cveNumber": "CVE-2017-17383"
    }
  },
  "description": "Jenkins\u662f\u4e00\u4e2a\u7528Java\u7f16\u5199\u7684\u5f00\u6e90\u7684\u6301\u7eed\u96c6\u6210\u5de5\u5177\u3002\r\n\r\n2.93\u53ca\u66f4\u65e9\u7248\u672c\u7684Jenkins\u5b58\u5728\u5b58\u50a8\u578b\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u8ba4\u8bc1\u7ba1\u7406\u5458\u53ef\u901a\u8fc7\u5de5\u4f5c\u914d\u7f6e\u8868\u5355\u4e2d\u7684\u7279\u5236\u5de5\u5177\u540d\u5229\u7528\u8be5\u6f0f\u6d1e\u8fdb\u884c\u8de8\u7ad9\u811a\u672c\u653b\u51fb\u3002",
  "discovererName": "Dhiraj Datar of Lakhshya Cyber Security Labs.",
  "formalWay": "\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u7684\u89e3\u51b3\u65b9\u6848\u63d0\u4f9b\uff1a\r\nhttps://jenkins.io/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2018-00230",
  "openTime": "2018-01-04",
  "products": {
    "product": "Jenkins CI Jenkins \u003c=2.93"
  },
  "referenceLink": "https://jenkins.io/security/advisory/2017-12-05/",
  "serverity": "\u4f4e",
  "submitTime": "2017-12-06",
  "title": "Jenkins\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff08CNVD-2018-00230\uff09"
}



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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.
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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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