CNVD-2021-03337

Vulnerability from cnvd - Published: 2021-01-07
VLAI
Title
Gotenberg目录遍历漏洞
Description
Gotenberg是一个由Docker驱动的无状态API,用于将HTML、Markdown和Office文档转换为PDF。 Gotenberg 6.2.1及更早版本的文件上传功能存在目录遍历漏洞。攻击者可利用该漏洞在预期文件夹之外上传和覆盖任意可写文件,从而可导致拒绝服务、程序行为更改,或执行代码。
Severity
高
Patch Name
Gotenberg目录遍历漏洞的补丁
Patch Description
Gotenberg是一个由Docker驱动的无状态API,用于将HTML、Markdown和Office文档转换为PDF。 Gotenberg 6.2.1及更早版本的文件上传功能存在目录遍历漏洞。攻击者可利用该漏洞在预期文件夹之外上传和覆盖任意可写文件,从而可导致拒绝服务、程序行为更改,或执行代码。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://github.com/thecodingmachine/gotenberg/pull/208

Reference
https://nvd.nist.gov/vuln/detail/CVE-2020-13450
Impacted products
Name
Gotenberg Gotenberg <=6.2.1
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-13450",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2020-13450"
    }
  },
  "description": "Gotenberg\u662f\u4e00\u4e2a\u7531Docker\u9a71\u52a8\u7684\u65e0\u72b6\u6001API\uff0c\u7528\u4e8e\u5c06HTML\u3001Markdown\u548cOffice\u6587\u6863\u8f6c\u6362\u4e3aPDF\u3002\n\nGotenberg 6.2.1\u53ca\u66f4\u65e9\u7248\u672c\u7684\u6587\u4ef6\u4e0a\u4f20\u529f\u80fd\u5b58\u5728\u76ee\u5f55\u904d\u5386\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5728\u9884\u671f\u6587\u4ef6\u5939\u4e4b\u5916\u4e0a\u4f20\u548c\u8986\u76d6\u4efb\u610f\u53ef\u5199\u6587\u4ef6\uff0c\u4ece\u800c\u53ef\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\u3001\u7a0b\u5e8f\u884c\u4e3a\u66f4\u6539\uff0c\u6216\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://github.com/thecodingmachine/gotenberg/pull/208",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-03337",
  "openTime": "2021-01-07",
  "patchDescription": "Gotenberg\u662f\u4e00\u4e2a\u7531Docker\u9a71\u52a8\u7684\u65e0\u72b6\u6001API\uff0c\u7528\u4e8e\u5c06HTML\u3001Markdown\u548cOffice\u6587\u6863\u8f6c\u6362\u4e3aPDF\u3002\r\n\r\nGotenberg 6.2.1\u53ca\u66f4\u65e9\u7248\u672c\u7684\u6587\u4ef6\u4e0a\u4f20\u529f\u80fd\u5b58\u5728\u76ee\u5f55\u904d\u5386\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5728\u9884\u671f\u6587\u4ef6\u5939\u4e4b\u5916\u4e0a\u4f20\u548c\u8986\u76d6\u4efb\u610f\u53ef\u5199\u6587\u4ef6\uff0c\u4ece\u800c\u53ef\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\u3001\u7a0b\u5e8f\u884c\u4e3a\u66f4\u6539\uff0c\u6216\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": "Gotenberg\u76ee\u5f55\u904d\u5386\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Gotenberg Gotenberg \u003c=6.2.1"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2020-13450",
  "serverity": "\u9ad8",
  "submitTime": "2021-01-08",
  "title": "Gotenberg\u76ee\u5f55\u904d\u5386\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.
  • 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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