CNVD-2020-35186

Vulnerability from cnvd - Published: 2020-06-30
VLAI
Title
Mattermost Mobile Apps存在未明漏洞(CNVD-2020-35186)
Description
Mattermost Mobile Apps是美国Mattermost公司的一款消息传递移动应用程序。 Mattermost Mobile Apps 1.26.0之前版本中存在安全漏洞,该漏洞源于在用户退出登录后,程序未能清除Cookie数据,攻击者可利用该漏洞获取敏感信息。
Severity
Patch Name
Mattermost Mobile Apps存在未明漏洞(CNVD-2020-35186)的补丁
Patch Description
Mattermost Mobile Apps是美国Mattermost公司的一款消息传递移动应用程序。 Mattermost Mobile Apps 1.26.0之前版本中存在安全漏洞,该漏洞源于在用户退出登录后,程序未能清除Cookie数据,攻击者可利用该漏洞获取敏感信息。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://mattermost.com/security-updates/

Reference
https://nvd.nist.gov/vuln/detail/CVE-2019-20849
Impacted products
Name
Mattermost Mobile Apps <1.26.0
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2019-20849"
    }
  },
  "description": "Mattermost Mobile Apps\u662f\u7f8e\u56fdMattermost\u516c\u53f8\u7684\u4e00\u6b3e\u6d88\u606f\u4f20\u9012\u79fb\u52a8\u5e94\u7528\u7a0b\u5e8f\u3002\n\nMattermost Mobile Apps 1.26.0\u4e4b\u524d\u7248\u672c\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u5728\u7528\u6237\u9000\u51fa\u767b\u5f55\u540e\uff0c\u7a0b\u5e8f\u672a\u80fd\u6e05\u9664Cookie\u6570\u636e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u83b7\u53d6\u654f\u611f\u4fe1\u606f\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://mattermost.com/security-updates/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2020-35186",
  "openTime": "2020-06-30",
  "patchDescription": "Mattermost Mobile Apps\u662f\u7f8e\u56fdMattermost\u516c\u53f8\u7684\u4e00\u6b3e\u6d88\u606f\u4f20\u9012\u79fb\u52a8\u5e94\u7528\u7a0b\u5e8f\u3002\r\n\r\nMattermost Mobile Apps 1.26.0\u4e4b\u524d\u7248\u672c\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u5728\u7528\u6237\u9000\u51fa\u767b\u5f55\u540e\uff0c\u7a0b\u5e8f\u672a\u80fd\u6e05\u9664Cookie\u6570\u636e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u83b7\u53d6\u654f\u611f\u4fe1\u606f\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": "Mattermost Mobile Apps\u5b58\u5728\u672a\u660e\u6f0f\u6d1e\uff08CNVD-2020-35186\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "Mattermost Mobile Apps \u003c1.26.0"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2019-20849",
  "serverity": "\u4e2d",
  "submitTime": "2020-06-22",
  "title": "Mattermost Mobile Apps\u5b58\u5728\u672a\u660e\u6f0f\u6d1e\uff08CNVD-2020-35186\uff09"
}



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…