CNVD-2024-22235

Vulnerability from cnvd - Published: 2024-05-13
VLAI
Title
Apache Ambari跨站脚本漏洞(CNVD-2024-22235)
Description
Apache Ambari是美国阿帕奇(Apache)基金会的一个应用软件。提供开发用于配置,管理和监视Apache Hadoop集群的软件来简化Hadoop管理。 Apache Ambari存在跨站脚本漏洞,攻击者可利用该漏洞获取受害者的基于cookie的身份验证凭据。
Severity
Patch Name
Apache Ambari跨站脚本漏洞(CNVD-2024-22235)的补丁
Patch Description
Apache Ambari是美国阿帕奇(Apache)基金会的一个应用软件。提供开发用于配置,管理和监视Apache Hadoop集群的软件来简化Hadoop管理。 Apache Ambari存在跨站脚本漏洞,攻击者可利用该漏洞获取受害者的基于cookie的身份验证凭据。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://lists.apache.org/thread/6hn0thq743vz9gh283s2d87wz8tqh37c

Reference
https://cxsecurity.com/cveshow/CVE-2023-50378/
Impacted products
Name
Apache Ambari >=2.7.0,<=2.7.7
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2023-50378"
    }
  },
  "description": "Apache Ambari\u662f\u7f8e\u56fd\u963f\u5e15\u5947\uff08Apache\uff09\u57fa\u91d1\u4f1a\u7684\u4e00\u4e2a\u5e94\u7528\u8f6f\u4ef6\u3002\u63d0\u4f9b\u5f00\u53d1\u7528\u4e8e\u914d\u7f6e\uff0c\u7ba1\u7406\u548c\u76d1\u89c6Apache Hadoop\u96c6\u7fa4\u7684\u8f6f\u4ef6\u6765\u7b80\u5316Hadoop\u7ba1\u7406\u3002\n\nApache Ambari\u5b58\u5728\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u83b7\u53d6\u53d7\u5bb3\u8005\u7684\u57fa\u4e8ecookie\u7684\u8eab\u4efd\u9a8c\u8bc1\u51ed\u636e\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://lists.apache.org/thread/6hn0thq743vz9gh283s2d87wz8tqh37c",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2024-22235",
  "openTime": "2024-05-13",
  "patchDescription": "Apache Ambari\u662f\u7f8e\u56fd\u963f\u5e15\u5947\uff08Apache\uff09\u57fa\u91d1\u4f1a\u7684\u4e00\u4e2a\u5e94\u7528\u8f6f\u4ef6\u3002\u63d0\u4f9b\u5f00\u53d1\u7528\u4e8e\u914d\u7f6e\uff0c\u7ba1\u7406\u548c\u76d1\u89c6Apache Hadoop\u96c6\u7fa4\u7684\u8f6f\u4ef6\u6765\u7b80\u5316Hadoop\u7ba1\u7406\u3002\r\n\r\nApache Ambari\u5b58\u5728\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u83b7\u53d6\u53d7\u5bb3\u8005\u7684\u57fa\u4e8ecookie\u7684\u8eab\u4efd\u9a8c\u8bc1\u51ed\u636e\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": "Apache Ambari\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff08CNVD-2024-22235\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "Apache Ambari \u003e=2.7.0\uff0c\u003c=2.7.7"
  },
  "referenceLink": "https://cxsecurity.com/cveshow/CVE-2023-50378/",
  "serverity": "\u4e2d",
  "submitTime": "2024-03-05",
  "title": "Apache Ambari\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff08CNVD-2024-22235\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

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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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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