CNVD-2022-38526

Vulnerability from cnvd - Published: 2022-05-19
VLAI
Title
Apache Superse SQL注入漏洞
Description
Apache Superset是一个现代的,工业级的Business Intelligence的Web应用。 Apache Superse中存在SQL注入漏洞。攻击者可以利用该漏洞执行任意SQL语句,如查询数据、下载数据、写入webshell、执行系统命令以及绕过登录限制等。
Severity
Patch Name
Apache Superse SQL注入漏洞的补丁
Patch Description
Apache Superset是一个现代的,工业级的Business Intelligence的Web应用。 Apache Superse中存在SQL注入漏洞。攻击者可以利用该漏洞执行任意SQL语句,如查询数据、下载数据、写入webshell、执行系统命令以及绕过登录限制等。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

目前厂商已经发布了升级补丁以修复这个安全问题,请到厂商的主页下载: https://lists.apache.org/thread/94th50j5d0y2fw7ysx0g7w3t6jk3z7q6

Reference
https://nvd.nist.gov/vuln/detail/CVE-2022-27479
Impacted products
Name
Apache Superset <1.4.2
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2022-27479",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2022-27479"
    }
  },
  "description": "Apache Superset\u662f\u4e00\u4e2a\u73b0\u4ee3\u7684\uff0c\u5de5\u4e1a\u7ea7\u7684Business Intelligence\u7684Web\u5e94\u7528\u3002\n\nApache Superse\u4e2d\u5b58\u5728SQL\u6ce8\u5165\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u4ee5\u5229\u7528\u8be5\u6f0f\u6d1e\u6267\u884c\u4efb\u610fSQL\u8bed\u53e5\uff0c\u5982\u67e5\u8be2\u6570\u636e\u3001\u4e0b\u8f7d\u6570\u636e\u3001\u5199\u5165webshell\u3001\u6267\u884c\u7cfb\u7edf\u547d\u4ee4\u4ee5\u53ca\u7ed5\u8fc7\u767b\u5f55\u9650\u5236\u7b49\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u7ecf\u53d1\u5e03\u4e86\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u8fd9\u4e2a\u5b89\u5168\u95ee\u9898\uff0c\u8bf7\u5230\u5382\u5546\u7684\u4e3b\u9875\u4e0b\u8f7d\uff1a\r\nhttps://lists.apache.org/thread/94th50j5d0y2fw7ysx0g7w3t6jk3z7q6",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-38526",
  "openTime": "2022-05-19",
  "patchDescription": "Apache Superset\u662f\u4e00\u4e2a\u73b0\u4ee3\u7684\uff0c\u5de5\u4e1a\u7ea7\u7684Business Intelligence\u7684Web\u5e94\u7528\u3002\r\n\r\nApache Superse\u4e2d\u5b58\u5728SQL\u6ce8\u5165\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u4ee5\u5229\u7528\u8be5\u6f0f\u6d1e\u6267\u884c\u4efb\u610fSQL\u8bed\u53e5\uff0c\u5982\u67e5\u8be2\u6570\u636e\u3001\u4e0b\u8f7d\u6570\u636e\u3001\u5199\u5165webshell\u3001\u6267\u884c\u7cfb\u7edf\u547d\u4ee4\u4ee5\u53ca\u7ed5\u8fc7\u767b\u5f55\u9650\u5236\u7b49\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 Superse SQL\u6ce8\u5165\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Apache Superset \u003c1.4.2"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2022-27479",
  "serverity": "\u9ad8",
  "submitTime": "2022-04-14",
  "title": "Apache Superse SQL\u6ce8\u5165\u6f0f\u6d1e"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

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.


Loading…