CNVD-2020-54075

Vulnerability from cnvd - Published: 2020-09-23
VLAI
Title
Xpdf无效内存访问漏洞(CNVD-2020-54075)
Description
Xpdf是一个免费PDF查看器和工具包,包括文本提取器、图像转换器、HTML转换器等。 Xpdf 4.0.2中的Error.cc中的fprintf函数存在无效内存访问漏洞。攻击者可通过将特制PDF文件发送到pdftohtml二进制文件利用该漏洞导致拒绝服务(分段错误)。
Severity
中
Patch Name
Xpdf无效内存访问漏洞(CNVD-2020-54075)的补丁
Patch Description
Xpdf是一个免费PDF查看器和工具包,包括文本提取器、图像转换器、HTML转换器等。 Xpdf 4.0.2中的Error.cc中的fprintf函数存在无效内存访问漏洞。攻击者可通过将特制PDF文件发送到pdftohtml二进制文件利用该漏洞导致拒绝服务(分段错误)。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

目前厂商已发布升级补丁以修复漏洞,补丁获取链接: https://forum.xpdfreader.com/viewtopic.php?f=3&t=42028

Reference
https://nvd.nist.gov/vuln/detail/CVE-2020-24999
Impacted products
Name
Foo Labs Xpdf 4.0.2
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-24999",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2020-24999"
    }
  },
  "description": "Xpdf\u662f\u4e00\u4e2a\u514d\u8d39PDF\u67e5\u770b\u5668\u548c\u5de5\u5177\u5305\uff0c\u5305\u62ec\u6587\u672c\u63d0\u53d6\u5668\u3001\u56fe\u50cf\u8f6c\u6362\u5668\u3001HTML\u8f6c\u6362\u5668\u7b49\u3002\n\nXpdf 4.0.2\u4e2d\u7684Error.cc\u4e2d\u7684fprintf\u51fd\u6570\u5b58\u5728\u65e0\u6548\u5185\u5b58\u8bbf\u95ee\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u5c06\u7279\u5236PDF\u6587\u4ef6\u53d1\u9001\u5230pdftohtml\u4e8c\u8fdb\u5236\u6587\u4ef6\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\uff08\u5206\u6bb5\u9519\u8bef\uff09\u3002",
  "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://forum.xpdfreader.com/viewtopic.php?f=3\u0026t=42028",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2020-54075",
  "openTime": "2020-09-23",
  "patchDescription": "Xpdf\u662f\u4e00\u4e2a\u514d\u8d39PDF\u67e5\u770b\u5668\u548c\u5de5\u5177\u5305\uff0c\u5305\u62ec\u6587\u672c\u63d0\u53d6\u5668\u3001\u56fe\u50cf\u8f6c\u6362\u5668\u3001HTML\u8f6c\u6362\u5668\u7b49\u3002\r\n\r\nXpdf 4.0.2\u4e2d\u7684Error.cc\u4e2d\u7684fprintf\u51fd\u6570\u5b58\u5728\u65e0\u6548\u5185\u5b58\u8bbf\u95ee\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u5c06\u7279\u5236PDF\u6587\u4ef6\u53d1\u9001\u5230pdftohtml\u4e8c\u8fdb\u5236\u6587\u4ef6\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\uff08\u5206\u6bb5\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": "Xpdf\u65e0\u6548\u5185\u5b58\u8bbf\u95ee\u6f0f\u6d1e\uff08CNVD-2020-54075\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "Foo Labs Xpdf 4.0.2"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2020-24999",
  "serverity": "\u4e2d",
  "submitTime": "2020-09-04",
  "title": "Xpdf\u65e0\u6548\u5185\u5b58\u8bbf\u95ee\u6f0f\u6d1e\uff08CNVD-2020-54075\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

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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