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CNVD-2020-04935

Vulnerability from cnvd - Published: 2020-02-13
VLAI
Title
Adive Framework跨站请求伪造漏洞
Description
Adive Framework是一款基于PHP的MySQL数据库管理框架。 Adive Framework中存在跨站请求伪造漏洞。该漏洞源于WEB应用未充分验证请求是否来自可信用户。攻击者可利用该漏洞通过受影响客户端向服务器发送非预期的请求。
Severity
Patch Name
Adive Framework跨站请求伪造漏洞的补丁
Patch Description
Adive Framework是一款基于PHP的MySQL数据库管理框架。 Adive Framework中存在跨站请求伪造漏洞。该漏洞源于WEB应用未充分验证请求是否来自可信用户。攻击者可利用该漏洞通过受影响客户端向服务器发送非预期的请求。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,补丁获取链接: https://github.com/ferdinandmartin/adive-php7/blob/master/README.md

Reference
https://packetstormsecurity.com/files/156106/Adive-Framework-2.0.8-Cross-Site-Request-Forgery.html
Impacted products
Name
adive Adive Framework
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-7991",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2020-7991"
    }
  },
  "description": "Adive Framework\u662f\u4e00\u6b3e\u57fa\u4e8ePHP\u7684MySQL\u6570\u636e\u5e93\u7ba1\u7406\u6846\u67b6\u3002\n\nAdive Framework\u4e2d\u5b58\u5728\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\u6f0f\u6d1e\u3002\u8be5\u6f0f\u6d1e\u6e90\u4e8eWEB\u5e94\u7528\u672a\u5145\u5206\u9a8c\u8bc1\u8bf7\u6c42\u662f\u5426\u6765\u81ea\u53ef\u4fe1\u7528\u6237\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u901a\u8fc7\u53d7\u5f71\u54cd\u5ba2\u6237\u7aef\u5411\u670d\u52a1\u5668\u53d1\u9001\u975e\u9884\u671f\u7684\u8bf7\u6c42\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6f0f\u6d1e\uff0c\u8865\u4e01\u83b7\u53d6\u94fe\u63a5\uff1a\r\nhttps://github.com/ferdinandmartin/adive-php7/blob/master/README.md",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2020-04935",
  "openTime": "2020-02-13",
  "patchDescription": "Adive Framework\u662f\u4e00\u6b3e\u57fa\u4e8ePHP\u7684MySQL\u6570\u636e\u5e93\u7ba1\u7406\u6846\u67b6\u3002\r\n\r\nAdive Framework\u4e2d\u5b58\u5728\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\u6f0f\u6d1e\u3002\u8be5\u6f0f\u6d1e\u6e90\u4e8eWEB\u5e94\u7528\u672a\u5145\u5206\u9a8c\u8bc1\u8bf7\u6c42\u662f\u5426\u6765\u81ea\u53ef\u4fe1\u7528\u6237\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u901a\u8fc7\u53d7\u5f71\u54cd\u5ba2\u6237\u7aef\u5411\u670d\u52a1\u5668\u53d1\u9001\u975e\u9884\u671f\u7684\u8bf7\u6c42\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": "Adive Framework\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "adive Adive Framework"
  },
  "referenceLink": "https://packetstormsecurity.com/files/156106/Adive-Framework-2.0.8-Cross-Site-Request-Forgery.html",
  "serverity": "\u9ad8",
  "submitTime": "2020-02-11",
  "title": "Adive Framework\u8de8\u7ad9\u8bf7\u6c42\u4f2a\u9020\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

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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Detection rules are retrieved from Rulezet.

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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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