CNVD-2018-05755

Vulnerability from cnvd - Published: 2018-03-20
VLAI
Title
Sean Barrett stb_vorbis缓冲区溢出漏洞
Description
Sean Barrett stb_vorbis是一款基于C++的单文件公共域库。 Sean Barrett stb_vorbis 1.12及之前版本中全部的vorbis decoding路径存在缓冲区溢出漏洞。攻击者可借助特制的Ogg Vorbis文件利用该漏洞破坏内存,造成拒绝服务,执行主机程序。
Severity
中
Patch Name
Sean Barrett stb_vorbis缓冲区溢出漏洞的补丁
Patch Description
Sean Barrett stb_vorbis是一款基于C++的单文件公共域库。 Sean Barrett stb_vorbis 1.12及之前版本中全部的vorbis decoding路径存在缓冲区溢出漏洞。攻击者可借助特制的Ogg Vorbis文件利用该漏洞破坏内存,造成拒绝服务,执行主机程序。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/nothings/stb/commit/244d83bc3d859293f55812d48b3db168e581f6ab

Reference
https://github.com/nothings/stb/commit/244d83bc3d859293f55812d48b3db168e581f6ab
Impacted products
Name
Sean Barrett stb_vorbis <=1.12
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2018-1000050"
    }
  },
  "description": "Sean Barrett stb_vorbis\u662f\u4e00\u6b3e\u57fa\u4e8eC++\u7684\u5355\u6587\u4ef6\u516c\u5171\u57df\u5e93\u3002\r\n\r\nSean Barrett stb_vorbis 1.12\u53ca\u4e4b\u524d\u7248\u672c\u4e2d\u5168\u90e8\u7684vorbis decoding\u8def\u5f84\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684Ogg Vorbis\u6587\u4ef6\u5229\u7528\u8be5\u6f0f\u6d1e\u7834\u574f\u5185\u5b58\uff0c\u9020\u6210\u62d2\u7edd\u670d\u52a1\uff0c\u6267\u884c\u4e3b\u673a\u7a0b\u5e8f\u3002",
  "discovererName": "unknow",
  "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/nothings/stb/commit/244d83bc3d859293f55812d48b3db168e581f6ab",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2018-05755",
  "openTime": "2018-03-20",
  "patchDescription": "Sean Barrett stb_vorbis\u662f\u4e00\u6b3e\u57fa\u4e8eC++\u7684\u5355\u6587\u4ef6\u516c\u5171\u57df\u5e93\u3002\r\n\r\nSean Barrett stb_vorbis 1.12\u53ca\u4e4b\u524d\u7248\u672c\u4e2d\u5168\u90e8\u7684vorbis decoding\u8def\u5f84\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684Ogg Vorbis\u6587\u4ef6\u5229\u7528\u8be5\u6f0f\u6d1e\u7834\u574f\u5185\u5b58\uff0c\u9020\u6210\u62d2\u7edd\u670d\u52a1\uff0c\u6267\u884c\u4e3b\u673a\u7a0b\u5e8f\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": "Sean Barrett stb_vorbis\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Sean Barrett stb_vorbis \u003c=1.12"
  },
  "referenceLink": "https://github.com/nothings/stb/commit/244d83bc3d859293f55812d48b3db168e581f6ab",
  "serverity": "\u4e2d",
  "submitTime": "2018-02-26",
  "title": "Sean Barrett stb_vorbis\u7f13\u51b2\u533a\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

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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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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