CNVD-2016-02338

Vulnerability from cnvd - Published: 2016-04-19
VLAI
Title
Apache Subversion mod_dav_svn整数溢出漏洞
Description
Apache Subversion是一套开源的版本控制系统,该系统可兼容并发版本系统(CVS)。 Apache Subversion的mod_dav_svn中的util.c文件中存在整数溢出漏洞。远程攻击者可提交特殊的skel-encoded请求正文进行拒绝服务攻击。
Severity
中
Patch Name
Apache Subversion mod_dav_svn整数溢出漏洞的补丁
Patch Description
Apache Subversion是一套开源的版本控制系统,该系统可兼容并发版本系统(CVS)。 Apache Subversion的mod_dav_svn中的util.c文件中存在整数溢出漏洞。远程攻击者可提交特殊的skel-encoded请求正文进行拒绝服务攻击。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

用户可参考如下厂商提供的安全补丁以修复该漏洞: http://subversion.apache.org/security/CVE-2015-5343-advisory.txt

Reference
http://subversion.apache.org/security/CVE-2015-5343-advisory.txt
Impacted products
Name
['Apache Subversion 1.7.x', 'Apache Subversion', 'Apache Subversion 1.8.x<1.8.15', 'Apache Subversion 1.9.x<1.9.3']
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2015-5343"
    }
  },
  "description": "Apache Subversion\u662f\u4e00\u5957\u5f00\u6e90\u7684\u7248\u672c\u63a7\u5236\u7cfb\u7edf\uff0c\u8be5\u7cfb\u7edf\u53ef\u517c\u5bb9\u5e76\u53d1\u7248\u672c\u7cfb\u7edf(CVS)\u3002\r\n\r\nApache Subversion\u7684mod_dav_svn\u4e2d\u7684util.c\u6587\u4ef6\u4e2d\u5b58\u5728\u6574\u6570\u6ea2\u51fa\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u63d0\u4ea4\u7279\u6b8a\u7684skel-encoded\u8bf7\u6c42\u6b63\u6587\u8fdb\u884c\u62d2\u7edd\u670d\u52a1\u653b\u51fb\u3002",
  "discovererName": "Apache",
  "formalWay": "\u7528\u6237\u53ef\u53c2\u8003\u5982\u4e0b\u5382\u5546\u63d0\u4f9b\u7684\u5b89\u5168\u8865\u4e01\u4ee5\u4fee\u590d\u8be5\u6f0f\u6d1e\uff1a\r\nhttp://subversion.apache.org/security/CVE-2015-5343-advisory.txt",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2016-02338",
  "openTime": "2016-04-19",
  "patchDescription": "Apache Subversion\u662f\u4e00\u5957\u5f00\u6e90\u7684\u7248\u672c\u63a7\u5236\u7cfb\u7edf\uff0c\u8be5\u7cfb\u7edf\u53ef\u517c\u5bb9\u5e76\u53d1\u7248\u672c\u7cfb\u7edf(CVS)\u3002\r\n\r\nApache Subversion\u7684mod_dav_svn\u4e2d\u7684util.c\u6587\u4ef6\u4e2d\u5b58\u5728\u6574\u6570\u6ea2\u51fa\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u63d0\u4ea4\u7279\u6b8a\u7684skel-encoded\u8bf7\u6c42\u6b63\u6587\u8fdb\u884c\u62d2\u7edd\u670d\u52a1\u653b\u51fb\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 Subversion mod_dav_svn\u6574\u6570\u6ea2\u51fa\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": [
      "Apache Subversion 1.7.x",
      "Apache Subversion",
      "Apache Subversion 1.8.x\u003c1.8.15",
      "Apache Subversion 1.9.x\u003c1.9.3"
    ]
  },
  "referenceLink": "http://subversion.apache.org/security/CVE-2015-5343-advisory.txt",
  "serverity": "\u4e2d",
  "submitTime": "2016-04-16",
  "title": "Apache Subversion mod_dav_svn\u6574\u6570\u6ea2\u51fa\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

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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.
  • 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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