CNVD-2016-10514

Vulnerability from cnvd - Published: 2016-11-02
VLAI
Title
Foxit Reader和PhantomPDF拒绝服务漏洞(CNVD-2016-10514)
Description
Foxit Reader是中国福昕(Foxit)软件公司的一款PDF文档阅读器。Foxit PhantomPDF是一个商业版。 基于Windows平台上的Foxit Reader和PhantomPDF 8.1之前版本中的ConvertToPDF插件存在拒绝服务漏洞。当gflags应用启用时,远程攻击者可借助特制的TIFF图像利用该漏洞造成拒绝服务(越边界读取和应用程序崩溃)。
Severity
Patch Name
Foxit Reader和PhantomPDF存在拒绝服务漏洞(CNVD-2016-10514)的补丁
Patch Description
Foxit Reader是中国福昕(Foxit)软件公司的一款PDF文档阅读器。Foxit PhantomPDF是一个商业版。 基于Windows平台上的Foxit Reader和PhantomPDF 8.1之前版本中的ConvertToPDF插件存在拒绝服务漏洞。当gflags应用启用时,远程攻击者可借助特制的TIFF图像利用该漏洞造成拒绝服务(越边界读取和应用程序崩溃)。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,补丁获取链接: https://www.foxitsoftware.com/support/security-bulletins.php

Reference
https://www.foxitsoftware.com/support/security-bulletins.php
Impacted products
Name
['Foxit Reader on Windows <=8.0.5', 'Foxit PhantomPDF on Windows <=8.0.5']
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2016-8875"
    }
  },
  "description": "Foxit Reader\u662f\u4e2d\u56fd\u798f\u6615\uff08Foxit\uff09\u8f6f\u4ef6\u516c\u53f8\u7684\u4e00\u6b3ePDF\u6587\u6863\u9605\u8bfb\u5668\u3002Foxit PhantomPDF\u662f\u4e00\u4e2a\u5546\u4e1a\u7248\u3002\r\n\r\n\u57fa\u4e8eWindows\u5e73\u53f0\u4e0a\u7684Foxit Reader\u548cPhantomPDF 8.1\u4e4b\u524d\u7248\u672c\u4e2d\u7684ConvertToPDF\u63d2\u4ef6\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\u3002\u5f53gflags\u5e94\u7528\u542f\u7528\u65f6\uff0c\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684TIFF\u56fe\u50cf\u5229\u7528\u8be5\u6f0f\u6d1e\u9020\u6210\u62d2\u7edd\u670d\u52a1\uff08\u8d8a\u8fb9\u754c\u8bfb\u53d6\u548c\u5e94\u7528\u7a0b\u5e8f\u5d29\u6e83\uff09\u3002",
  "discovererName": "unknown",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u7ecf\u53d1\u5e03\u4e86\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6b64\u5b89\u5168\u95ee\u9898\uff0c\u8865\u4e01\u83b7\u53d6\u94fe\u63a5\uff1a\r\nhttps://www.foxitsoftware.com/support/security-bulletins.php",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2016-10514",
  "openTime": "2016-11-02",
  "patchDescription": "Foxit Reader\u662f\u4e2d\u56fd\u798f\u6615\uff08Foxit\uff09\u8f6f\u4ef6\u516c\u53f8\u7684\u4e00\u6b3ePDF\u6587\u6863\u9605\u8bfb\u5668\u3002Foxit PhantomPDF\u662f\u4e00\u4e2a\u5546\u4e1a\u7248\u3002\r\n\r\n\u57fa\u4e8eWindows\u5e73\u53f0\u4e0a\u7684Foxit Reader\u548cPhantomPDF 8.1\u4e4b\u524d\u7248\u672c\u4e2d\u7684ConvertToPDF\u63d2\u4ef6\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\u3002\u5f53gflags\u5e94\u7528\u542f\u7528\u65f6\uff0c\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684TIFF\u56fe\u50cf\u5229\u7528\u8be5\u6f0f\u6d1e\u9020\u6210\u62d2\u7edd\u670d\u52a1\uff08\u8d8a\u8fb9\u754c\u8bfb\u53d6\u548c\u5e94\u7528\u7a0b\u5e8f\u5d29\u6e83\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": "Foxit Reader\u548cPhantomPDF\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff08CNVD-2016-10514\uff09\u7684\u8865\u4e01",
  "products": {
    "product": [
      "Foxit Reader on Windows \u003c=8.0.5",
      "Foxit PhantomPDF on Windows \u003c=8.0.5"
    ]
  },
  "referenceLink": "https://www.foxitsoftware.com/support/security-bulletins.php",
  "serverity": "\u4e2d",
  "submitTime": "2016-11-01",
  "title": "Foxit Reader\u548cPhantomPDF\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff08CNVD-2016-10514\uff09"
}



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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.
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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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