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CNVD-2021-95945

Vulnerability from cnvd - Published: 2021-12-10
VLAI
Title
Unitrends Backup格式化字符串错误漏洞
Description
Unitrends Backup是消除数据丢失、 勒索软件和风险。 Unitrends Backup 10.5.5之前版本存在格式化字符串错误漏洞,该漏洞源于创建的HTTP请求可能会在有特权的vaultServer应用程序中引发格式字符串漏洞。 目前没有详细漏洞细节提供。
Severity
Patch Name
Unitrends Backup格式化字符串错误漏洞的补丁
Patch Description
Unitrends Backup是消除数据丢失、 勒索软件和风险。 Unitrends Backup 10.5.5之前版本存在格式化字符串错误漏洞,该漏洞源于创建的HTTP请求可能会在有特权的vaultServer应用程序中引发格式字符串漏洞。 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://helpdesk.kaseya.com/hc/en-gb/articles/4412762258961

Reference
https://helpdesk.kaseya.com/hc/en-gb/articles/4412762258961
Impacted products
Name
Unitrends Unitrends Backup <10.5.5
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-43041",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-43041"
    }
  },
  "description": "Unitrends Backup\u662f\u6d88\u9664\u6570\u636e\u4e22\u5931\u3001 \u52d2\u7d22\u8f6f\u4ef6\u548c\u98ce\u9669\u3002\n\nUnitrends Backup 10.5.5\u4e4b\u524d\u7248\u672c\u5b58\u5728\u683c\u5f0f\u5316\u5b57\u7b26\u4e32\u9519\u8bef\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u521b\u5efa\u7684HTTP\u8bf7\u6c42\u53ef\u80fd\u4f1a\u5728\u6709\u7279\u6743\u7684vaultServer\u5e94\u7528\u7a0b\u5e8f\u4e2d\u5f15\u53d1\u683c\u5f0f\u5b57\u7b26\u4e32\u6f0f\u6d1e\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://helpdesk.kaseya.com/hc/en-gb/articles/4412762258961",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-95945",
  "openTime": "2021-12-10",
  "patchDescription": "Unitrends Backup\u662f\u6d88\u9664\u6570\u636e\u4e22\u5931\u3001 \u52d2\u7d22\u8f6f\u4ef6\u548c\u98ce\u9669\u3002\r\n\r\nUnitrends Backup 10.5.5\u4e4b\u524d\u7248\u672c\u5b58\u5728\u683c\u5f0f\u5316\u5b57\u7b26\u4e32\u9519\u8bef\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u521b\u5efa\u7684HTTP\u8bf7\u6c42\u53ef\u80fd\u4f1a\u5728\u6709\u7279\u6743\u7684vaultServer\u5e94\u7528\u7a0b\u5e8f\u4e2d\u5f15\u53d1\u683c\u5f0f\u5b57\u7b26\u4e32\u6f0f\u6d1e\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": "Unitrends Backup\u683c\u5f0f\u5316\u5b57\u7b26\u4e32\u9519\u8bef\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Unitrends Unitrends Backup \u003c10.5.5"
  },
  "referenceLink": "https://helpdesk.kaseya.com/hc/en-gb/articles/4412762258961",
  "serverity": "\u4e2d",
  "submitTime": "2021-12-09",
  "title": "Unitrends Backup\u683c\u5f0f\u5316\u5b57\u7b26\u4e32\u9519\u8bef\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

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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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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