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CNVD-2020-62464

Vulnerability from cnvd - Published: 2020-11-12
VLAI
Title
Foxit PhantomPDF远程代码执行漏洞(CNVD-2020-62464)
Description
PhantomPDF是中国福昕(Foxit)公司的一款面向企业级用户的PDF文档处理软件。 Foxit PhantomPDF对嵌入在PDF文件中的U3D对象的处理存在远程代码执行漏洞。该漏洞源于在将用户提供的数据复制到固定长度的栈缓冲区之前未能对数据长度进行正确验证。攻击者可利用该漏洞在当前进程的上下文中执行代码。
Severity
Patch Name
Foxit PhantomPDF远程代码执行漏洞(CNVD-2020-62464)的补丁
Patch Description
PhantomPDF是中国福昕(Foxit)公司的一款面向企业级用户的PDF文档处理软件。 Foxit PhantomPDF对嵌入在PDF文件中的U3D对象的处理存在远程代码执行漏洞。该漏洞源于在将用户提供的数据复制到固定长度的栈缓冲区之前未能对数据长度进行正确验证。攻击者可利用该漏洞在当前进程的上下文中执行代码。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

厂商已发布了漏洞修复程序,请及时关注更新: https://www.foxitsoftware.com/support/security-bulletins.html

Reference
https://www.zerodayinitiative.com/advisories/ZDI-20-1235/ https://nvd.nist.gov/vuln/detail/CVE-2020-17413
Impacted products
Name
Foxit PhantomPDF
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-17413",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2020-17413"
    }
  },
  "description": "PhantomPDF\u662f\u4e2d\u56fd\u798f\u6615\uff08Foxit\uff09\u516c\u53f8\u7684\u4e00\u6b3e\u9762\u5411\u4f01\u4e1a\u7ea7\u7528\u6237\u7684PDF\u6587\u6863\u5904\u7406\u8f6f\u4ef6\u3002\n\nFoxit PhantomPDF\u5bf9\u5d4c\u5165\u5728PDF\u6587\u4ef6\u4e2d\u7684U3D\u5bf9\u8c61\u7684\u5904\u7406\u5b58\u5728\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\u6f0f\u6d1e\u3002\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u5728\u5c06\u7528\u6237\u63d0\u4f9b\u7684\u6570\u636e\u590d\u5236\u5230\u56fa\u5b9a\u957f\u5ea6\u7684\u6808\u7f13\u51b2\u533a\u4e4b\u524d\u672a\u80fd\u5bf9\u6570\u636e\u957f\u5ea6\u8fdb\u884c\u6b63\u786e\u9a8c\u8bc1\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5728\u5f53\u524d\u8fdb\u7a0b\u7684\u4e0a\u4e0b\u6587\u4e2d\u6267\u884c\u4ee3\u7801\u3002",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://www.foxitsoftware.com/support/security-bulletins.html",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2020-62464",
  "openTime": "2020-11-12",
  "patchDescription": "PhantomPDF\u662f\u4e2d\u56fd\u798f\u6615\uff08Foxit\uff09\u516c\u53f8\u7684\u4e00\u6b3e\u9762\u5411\u4f01\u4e1a\u7ea7\u7528\u6237\u7684PDF\u6587\u6863\u5904\u7406\u8f6f\u4ef6\u3002\r\n\r\nFoxit PhantomPDF\u5bf9\u5d4c\u5165\u5728PDF\u6587\u4ef6\u4e2d\u7684U3D\u5bf9\u8c61\u7684\u5904\u7406\u5b58\u5728\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\u6f0f\u6d1e\u3002\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u5728\u5c06\u7528\u6237\u63d0\u4f9b\u7684\u6570\u636e\u590d\u5236\u5230\u56fa\u5b9a\u957f\u5ea6\u7684\u6808\u7f13\u51b2\u533a\u4e4b\u524d\u672a\u80fd\u5bf9\u6570\u636e\u957f\u5ea6\u8fdb\u884c\u6b63\u786e\u9a8c\u8bc1\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5728\u5f53\u524d\u8fdb\u7a0b\u7684\u4e0a\u4e0b\u6587\u4e2d\u6267\u884c\u4ee3\u7801\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 PhantomPDF\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\u6f0f\u6d1e\uff08CNVD-2020-62464\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "Foxit PhantomPDF"
  },
  "referenceLink": "https://www.zerodayinitiative.com/advisories/ZDI-20-1235/\r\nhttps://nvd.nist.gov/vuln/detail/CVE-2020-17413",
  "serverity": "\u4e2d",
  "submitTime": "2020-09-30",
  "title": "Foxit PhantomPDF\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\u6f0f\u6d1e\uff08CNVD-2020-62464\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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