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CNVD-2022-18048

Vulnerability from cnvd - Published: 2022-03-10
VLAI
Title
Ruby缓冲区溢出漏洞(CNVD-2022-18048)
Description
Ruby是松本行弘个人开发者的一种跨平台、面向对象的动态类型编程语言。 Ruby 3.0.3之前版本存在缓冲区溢出漏洞,该漏洞源于在传递非常大的数据时会导致缓冲区溢出字符串(>700 MB)到CGI.escape_html。目前没有详细的漏洞细节提供。
Severity
Patch Name
Ruby缓冲区溢出漏洞(CNVD-2022-18048)的补丁
Patch Description
Ruby是松本行弘个人开发者的一种跨平台、面向对象的动态类型编程语言。 Ruby 3.0.3之前版本存在缓冲区溢出漏洞,该漏洞源于在传递非常大的数据时会导致缓冲区溢出字符串(>700 MB)到CGI.escape_html。目前没有详细的漏洞细节提供。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://www.ruby-lang.org/en/news/2021/11/24/buffer-overrun-in-cgi-escape_html-cve-2021-41816/

Reference
https://www.auscert.org.au/bulletins/ESB-2021.4000
Impacted products
Name
Ruby Ruby <3.0.3
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-41816"
    }
  },
  "description": "Ruby\u662f\u677e\u672c\u884c\u5f18\u4e2a\u4eba\u5f00\u53d1\u8005\u7684\u4e00\u79cd\u8de8\u5e73\u53f0\u3001\u9762\u5411\u5bf9\u8c61\u7684\u52a8\u6001\u7c7b\u578b\u7f16\u7a0b\u8bed\u8a00\u3002\n\nRuby 3.0.3\u4e4b\u524d\u7248\u672c\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u5728\u4f20\u9012\u975e\u5e38\u5927\u7684\u6570\u636e\u65f6\u4f1a\u5bfc\u81f4\u7f13\u51b2\u533a\u6ea2\u51fa\u5b57\u7b26\u4e32\uff08\uff1e700 MB\uff09\u5230CGI.escape_html\u3002\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u7684\u6f0f\u6d1e\u7ec6\u8282\u63d0\u4f9b\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://www.ruby-lang.org/en/news/2021/11/24/buffer-overrun-in-cgi-escape_html-cve-2021-41816/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-18048",
  "openTime": "2022-03-10",
  "patchDescription": "Ruby\u662f\u677e\u672c\u884c\u5f18\u4e2a\u4eba\u5f00\u53d1\u8005\u7684\u4e00\u79cd\u8de8\u5e73\u53f0\u3001\u9762\u5411\u5bf9\u8c61\u7684\u52a8\u6001\u7c7b\u578b\u7f16\u7a0b\u8bed\u8a00\u3002\r\n\r\nRuby 3.0.3\u4e4b\u524d\u7248\u672c\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u5728\u4f20\u9012\u975e\u5e38\u5927\u7684\u6570\u636e\u65f6\u4f1a\u5bfc\u81f4\u7f13\u51b2\u533a\u6ea2\u51fa\u5b57\u7b26\u4e32\uff08\uff1e700 MB\uff09\u5230CGI.escape_html\u3002\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u7684\u6f0f\u6d1e\u7ec6\u8282\u63d0\u4f9b\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": "Ruby\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2022-18048\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "Ruby Ruby \u003c3.0.3"
  },
  "referenceLink": "https://www.auscert.org.au/bulletins/ESB-2021.4000",
  "serverity": "\u9ad8",
  "submitTime": "2021-11-29",
  "title": "Ruby\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2022-18048\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.
  • 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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Detection rules are retrieved from Rulezet.

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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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