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CNVD-2022-19074

Vulnerability from cnvd - Published: 2022-03-14
VLAI
Title
Fortinet FortiWeb缓冲区溢出漏洞(CNVD-2022-19074)
Description
Fortinet FortiWeb是美国飞塔(Fortinet)公司的一款Web应用层防火墙,它能够阻断如跨站点脚本、SQL注入、Cookie中毒、schema中毒等攻击的威胁,保证Web应用程序的安全性并保护敏感的数据库内容。 Fortinet FortiWeb 6.4.2之前版本存在缓冲区溢出漏洞,经过身份验证的攻击者可利用该漏洞通过特制的命令执行任意代码。
Severity
Patch Name
Fortinet FortiWeb缓冲区溢出漏洞(CNVD-2022-19074)的补丁
Patch Description
Fortinet FortiWeb是美国飞塔(Fortinet)公司的一款Web应用层防火墙,它能够阻断如跨站点脚本、SQL注入、Cookie中毒、schema中毒等攻击的威胁,保证Web应用程序的安全性并保护敏感的数据库内容。 Fortinet FortiWeb 6.4.2之前版本存在缓冲区溢出漏洞,经过身份验证的攻击者可利用该漏洞通过特制的命令执行任意代码。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://fortiguard.com/advisory/FG-IR-21-132

Reference
https://fortiguard.com/advisory/FG-IR-21-132
Impacted products
Name
Fortinet Fortinet FortiWeb <6.4.2
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-36193",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-36193"
    }
  },
  "description": "Fortinet FortiWeb\u662f\u7f8e\u56fd\u98de\u5854\uff08Fortinet\uff09\u516c\u53f8\u7684\u4e00\u6b3eWeb\u5e94\u7528\u5c42\u9632\u706b\u5899\uff0c\u5b83\u80fd\u591f\u963b\u65ad\u5982\u8de8\u7ad9\u70b9\u811a\u672c\u3001SQL\u6ce8\u5165\u3001Cookie\u4e2d\u6bd2\u3001schema\u4e2d\u6bd2\u7b49\u653b\u51fb\u7684\u5a01\u80c1\uff0c\u4fdd\u8bc1Web\u5e94\u7528\u7a0b\u5e8f\u7684\u5b89\u5168\u6027\u5e76\u4fdd\u62a4\u654f\u611f\u7684\u6570\u636e\u5e93\u5185\u5bb9\u3002\n\nFortinet FortiWeb 6.4.2\u4e4b\u524d\u7248\u672c\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u7ecf\u8fc7\u8eab\u4efd\u9a8c\u8bc1\u7684\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u901a\u8fc7\u7279\u5236\u7684\u547d\u4ee4\u6267\u884c\u4efb\u610f\u4ee3\u7801\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://fortiguard.com/advisory/FG-IR-21-132",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-19074",
  "openTime": "2022-03-14",
  "patchDescription": "Fortinet FortiWeb\u662f\u7f8e\u56fd\u98de\u5854\uff08Fortinet\uff09\u516c\u53f8\u7684\u4e00\u6b3eWeb\u5e94\u7528\u5c42\u9632\u706b\u5899\uff0c\u5b83\u80fd\u591f\u963b\u65ad\u5982\u8de8\u7ad9\u70b9\u811a\u672c\u3001SQL\u6ce8\u5165\u3001Cookie\u4e2d\u6bd2\u3001schema\u4e2d\u6bd2\u7b49\u653b\u51fb\u7684\u5a01\u80c1\uff0c\u4fdd\u8bc1Web\u5e94\u7528\u7a0b\u5e8f\u7684\u5b89\u5168\u6027\u5e76\u4fdd\u62a4\u654f\u611f\u7684\u6570\u636e\u5e93\u5185\u5bb9\u3002\r\n\r\nFortinet FortiWeb 6.4.2\u4e4b\u524d\u7248\u672c\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u7ecf\u8fc7\u8eab\u4efd\u9a8c\u8bc1\u7684\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u901a\u8fc7\u7279\u5236\u7684\u547d\u4ee4\u6267\u884c\u4efb\u610f\u4ee3\u7801\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": "Fortinet FortiWeb\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2022-19074\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "Fortinet Fortinet FortiWeb \u003c6.4.2"
  },
  "referenceLink": "https://fortiguard.com/advisory/FG-IR-21-132",
  "serverity": "\u4e2d",
  "submitTime": "2022-02-08",
  "title": "Fortinet FortiWeb\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2022-19074\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.
  • 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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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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