CNVD-2016-03705

Vulnerability from cnvd - Published: 2016-05-31
VLAI
Title
Sensio Labs Symfony拒绝服务漏洞
Description
Sensio Labs Symfony是法国Sensio Labs公司的一套免费的、基于MVC架构的PHP开发框架。该框架提供常用的功能组件及工具,可用于快速创建复杂的WEB程序。 Sensio Labs Symfony中存在安全漏洞。攻击者可通过提交不存在的较大字段的用户名利用该漏洞消耗会话存储空间。
Severity
Patch Name
Sensio Labs Symfony拒绝服务漏洞的补丁
Patch Description
Sensio Labs Symfony是法国Sensio Labs公司的一套免费的、基于MVC架构的PHP开发框架。该框架提供常用的功能组件及工具,可用于快速创建复杂的WEB程序。 Sensio Labs Symfony中存在安全漏洞。攻击者可通过提交不存在的较大字段的用户名利用该漏洞消耗会话存储空间。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此安全问题,详情请关注厂商主页: http://symfony.com/

Reference
https://www.auscert.org.au/render.html?it=35146
Impacted products
Name
SensioLabs Symfony
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2016-4423"
    }
  },
  "description": "Sensio Labs Symfony\u662f\u6cd5\u56fdSensio Labs\u516c\u53f8\u7684\u4e00\u5957\u514d\u8d39\u7684\u3001\u57fa\u4e8eMVC\u67b6\u6784\u7684PHP\u5f00\u53d1\u6846\u67b6\u3002\u8be5\u6846\u67b6\u63d0\u4f9b\u5e38\u7528\u7684\u529f\u80fd\u7ec4\u4ef6\u53ca\u5de5\u5177\uff0c\u53ef\u7528\u4e8e\u5feb\u901f\u521b\u5efa\u590d\u6742\u7684WEB\u7a0b\u5e8f\u3002\r\n\r\nSensio Labs Symfony\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u63d0\u4ea4\u4e0d\u5b58\u5728\u7684\u8f83\u5927\u5b57\u6bb5\u7684\u7528\u6237\u540d\u5229\u7528\u8be5\u6f0f\u6d1e\u6d88\u8017\u4f1a\u8bdd\u5b58\u50a8\u7a7a\u95f4\u3002",
  "discovererName": "Australian Computer Emergency Response Team",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u7ecf\u53d1\u5e03\u4e86\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6b64\u5b89\u5168\u95ee\u9898\uff0c\u8be6\u60c5\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\uff1a\r\nhttp://symfony.com/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2016-03705",
  "openTime": "2016-05-31",
  "patchDescription": "Sensio Labs Symfony\u662f\u6cd5\u56fdSensio Labs\u516c\u53f8\u7684\u4e00\u5957\u514d\u8d39\u7684\u3001\u57fa\u4e8eMVC\u67b6\u6784\u7684PHP\u5f00\u53d1\u6846\u67b6\u3002\u8be5\u6846\u67b6\u63d0\u4f9b\u5e38\u7528\u7684\u529f\u80fd\u7ec4\u4ef6\u53ca\u5de5\u5177\uff0c\u53ef\u7528\u4e8e\u5feb\u901f\u521b\u5efa\u590d\u6742\u7684WEB\u7a0b\u5e8f\u3002\r\n\r\nSensio Labs Symfony\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u63d0\u4ea4\u4e0d\u5b58\u5728\u7684\u8f83\u5927\u5b57\u6bb5\u7684\u7528\u6237\u540d\u5229\u7528\u8be5\u6f0f\u6d1e\u6d88\u8017\u4f1a\u8bdd\u5b58\u50a8\u7a7a\u95f4\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": "Sensio Labs Symfony\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "SensioLabs Symfony"
  },
  "referenceLink": "https://www.auscert.org.au/render.html?it=35146",
  "serverity": "\u4e2d",
  "submitTime": "2016-05-30",
  "title": "Sensio Labs Symfony\u62d2\u7edd\u670d\u52a1\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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