GCVE Workshop - 22 September 2026 (14:00-18:00), Luxembourg Before The Vulnopticon Conference - Registration

CNVD-2022-22269

Vulnerability from cnvd - Published: 2022-03-24
VLAI
Title
Cockpit存在未明漏洞
Description
Cockpit是一个交互式服务器管理界面。 Cockpit存在安全漏洞,该漏洞源于<iFrame> HTML条目内的另一个网站从驾驶舱服务器呈现页面可能会被恶意网站用于点击劫持或类似攻击。目前没有详细漏洞细节提供。
Severity
Patch Name
Cockpit存在未明漏洞的补丁
Patch Description
Cockpit是一个交互式服务器管理界面。 Cockpit存在安全漏洞,该漏洞源于<iFrame> HTML条目内的另一个网站从驾驶舱服务器呈现页面可能会被恶意网站用于点击劫持或类似攻击。目前没有详细漏洞细节提供。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

厂商已发布了漏洞修复程序,请及时关注更新: https://github.com/cockpit-project/cockpit/commit/8d9bc10d8128aae03dfde62fd00075fe492ead10

Reference
https://bugzilla.redhat.com/show_bug.cgi?id=1980688
Impacted products
Name
Cockpit Cockpit null
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-3660"
    }
  },
  "description": "Cockpit\u662f\u4e00\u4e2a\u4ea4\u4e92\u5f0f\u670d\u52a1\u5668\u7ba1\u7406\u754c\u9762\u3002\n\nCockpit\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\uff1ciFrame\uff1e HTML\u6761\u76ee\u5185\u7684\u53e6\u4e00\u4e2a\u7f51\u7ad9\u4ece\u9a7e\u9a76\u8231\u670d\u52a1\u5668\u5448\u73b0\u9875\u9762\u53ef\u80fd\u4f1a\u88ab\u6076\u610f\u7f51\u7ad9\u7528\u4e8e\u70b9\u51fb\u52ab\u6301\u6216\u7c7b\u4f3c\u653b\u51fb\u3002\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u6f0f\u6d1e\u7ec6\u8282\u63d0\u4f9b\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/cockpit-project/cockpit/commit/8d9bc10d8128aae03dfde62fd00075fe492ead10",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-22269",
  "openTime": "2022-03-24",
  "patchDescription": "Cockpit\u662f\u4e00\u4e2a\u4ea4\u4e92\u5f0f\u670d\u52a1\u5668\u7ba1\u7406\u754c\u9762\u3002\r\n\r\nCockpit\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\uff1ciFrame\uff1e HTML\u6761\u76ee\u5185\u7684\u53e6\u4e00\u4e2a\u7f51\u7ad9\u4ece\u9a7e\u9a76\u8231\u670d\u52a1\u5668\u5448\u73b0\u9875\u9762\u53ef\u80fd\u4f1a\u88ab\u6076\u610f\u7f51\u7ad9\u7528\u4e8e\u70b9\u51fb\u52ab\u6301\u6216\u7c7b\u4f3c\u653b\u51fb\u3002\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\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": "Cockpit\u5b58\u5728\u672a\u660e\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Cockpit Cockpit null"
  },
  "referenceLink": "https://bugzilla.redhat.com/show_bug.cgi?id=1980688",
  "serverity": "\u4e2d",
  "submitTime": "2022-03-14",
  "title": "Cockpit\u5b58\u5728\u672a\u660e\u6f0f\u6d1e"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

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.


Loading…