CNVD-2017-05415

Vulnerability from cnvd - Published: 2017-04-26
VLAI
Title
libplist 'parse_string_node()'函数本地拒绝服务漏洞
Description
libplist是一个小型的可移植C库,处理二进制或XML的Apple Property List文件。 libimobiledevice libplist 1.12版本,bplist.c中parse_string_node函数存在拒绝服务漏洞,本地用户通过构造的plist文件,可造成拒绝服务(内存分配错误)。
Severity
低
Patch Name
libplist 'parse_string_node()'函数本地拒绝服务漏洞的补丁
Patch Description
libplist是一个小型的可移植C库,处理二进制或XML的Apple Property List文件。 libimobiledevice libplist 1.12版本,bplist.c中parse_string_node函数存在拒绝服务漏洞,本地用户通过构造的plist文件,可造成拒绝服务(内存分配错误)。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这个安全问题,请到厂商的主页下载: https://github.com/libimobiledevice/libplist/commit/32ee5213fe64f1e10ec76c1ee861ee6f233120ddhttps://github.com/libimobiledevice/libplist/issues/94

Reference
http://www.securityfocus.com/bid/97290
Impacted products
Name
libimobiledevice libplist 1.12
Show details on source website

{
  "bids": {
    "bid": {
      "bidNumber": "97290"
    }
  },
  "cves": {
    "cve": {
      "cveNumber": "CVE-2017-6436",
      "cveUrl": "http://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2017-6436"
    }
  },
  "description": "libplist\u662f\u4e00\u4e2a\u5c0f\u578b\u7684\u53ef\u79fb\u690dC\u5e93\uff0c\u5904\u7406\u4e8c\u8fdb\u5236\u6216XML\u7684Apple Property List\u6587\u4ef6\u3002\r\n\r\nlibimobiledevice libplist 1.12\u7248\u672c\uff0cbplist.c\u4e2dparse_string_node\u51fd\u6570\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff0c\u672c\u5730\u7528\u6237\u901a\u8fc7\u6784\u9020\u7684plist\u6587\u4ef6\uff0c\u53ef\u9020\u6210\u62d2\u7edd\u670d\u52a1\uff08\u5185\u5b58\u5206\u914d\u9519\u8bef\uff09\u3002",
  "discovererName": "zhunki",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u7ecf\u53d1\u5e03\u4e86\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u8fd9\u4e2a\u5b89\u5168\u95ee\u9898\uff0c\u8bf7\u5230\u5382\u5546\u7684\u4e3b\u9875\u4e0b\u8f7d\uff1a\r\nhttps://github.com/libimobiledevice/libplist/commit/32ee5213fe64f1e10ec76c1ee861ee6f233120ddhttps://github.com/libimobiledevice/libplist/issues/94",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2017-05415",
  "openTime": "2017-04-26",
  "patchDescription": "libplist\u662f\u4e00\u4e2a\u5c0f\u578b\u7684\u53ef\u79fb\u690dC\u5e93\uff0c\u5904\u7406\u4e8c\u8fdb\u5236\u6216XML\u7684Apple Property List\u6587\u4ef6\u3002\r\n\r\nlibimobiledevice libplist 1.12\u7248\u672c\uff0cbplist.c\u4e2dparse_string_node\u51fd\u6570\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff0c\u672c\u5730\u7528\u6237\u901a\u8fc7\u6784\u9020\u7684plist\u6587\u4ef6\uff0c\u53ef\u9020\u6210\u62d2\u7edd\u670d\u52a1\uff08\u5185\u5b58\u5206\u914d\u9519\u8bef\uff09\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": "libplist \u0027parse_string_node()\u0027\u51fd\u6570\u672c\u5730\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "libimobiledevice libplist 1.12"
  },
  "referenceLink": "http://www.securityfocus.com/bid/97290",
  "serverity": "\u4f4e",
  "submitTime": "2017-04-05",
  "title": "libplist \u0027parse_string_node()\u0027\u51fd\u6570\u672c\u5730\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

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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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  • 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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