CNVD-2020-59478

Vulnerability from cnvd - Published: 2020-10-30
VLAI
Title
Apple OS X libxpc任意文件覆盖漏洞
Description
Apple OS X是美国苹果(Apple)公司的一套为Mac计算机所开发的专用操作系统。 OS X libxpc存在安全漏洞,该漏洞是由于产品设计缺陷未限制文件上传,该漏洞使得恶意应用程序能够覆盖任意文件。目前没有详细的漏洞细节提供。
Severity
Patch Name
Apple OS X libxpc任意文件覆盖漏洞的补丁
Patch Description
Apple OS X是美国苹果(Apple)公司的一套为Mac计算机所开发的专用操作系统。 OS X libxpc存在安全漏洞,该漏洞是由于产品设计缺陷未限制文件上传,该漏洞使得恶意应用程序能够覆盖任意文件。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

厂商已发布了漏洞修复程序,请及时关注更新: https://support.apple.com/

Reference
https://support.apple.com/kb/HT211171
Impacted products
Name
Apple Apple OS X libxpc
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-9994",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2020-9994"
    }
  },
  "description": "Apple OS X\u662f\u7f8e\u56fd\u82f9\u679c\uff08Apple\uff09\u516c\u53f8\u7684\u4e00\u5957\u4e3aMac\u8ba1\u7b97\u673a\u6240\u5f00\u53d1\u7684\u4e13\u7528\u64cd\u4f5c\u7cfb\u7edf\u3002\n\nOS X libxpc\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u662f\u7531\u4e8e\u4ea7\u54c1\u8bbe\u8ba1\u7f3a\u9677\u672a\u9650\u5236\u6587\u4ef6\u4e0a\u4f20\uff0c\u8be5\u6f0f\u6d1e\u4f7f\u5f97\u6076\u610f\u5e94\u7528\u7a0b\u5e8f\u80fd\u591f\u8986\u76d6\u4efb\u610f\u6587\u4ef6\u3002\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u7684\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://support.apple.com/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2020-59478",
  "openTime": "2020-10-30",
  "patchDescription": "Apple OS X\u662f\u7f8e\u56fd\u82f9\u679c\uff08Apple\uff09\u516c\u53f8\u7684\u4e00\u5957\u4e3aMac\u8ba1\u7b97\u673a\u6240\u5f00\u53d1\u7684\u4e13\u7528\u64cd\u4f5c\u7cfb\u7edf\u3002\r\n\r\nOS X libxpc\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u662f\u7531\u4e8e\u4ea7\u54c1\u8bbe\u8ba1\u7f3a\u9677\u672a\u9650\u5236\u6587\u4ef6\u4e0a\u4f20\uff0c\u8be5\u6f0f\u6d1e\u4f7f\u5f97\u6076\u610f\u5e94\u7528\u7a0b\u5e8f\u80fd\u591f\u8986\u76d6\u4efb\u610f\u6587\u4ef6\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": "Apple OS X libxpc\u4efb\u610f\u6587\u4ef6\u8986\u76d6\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Apple  Apple OS X libxpc"
  },
  "referenceLink": "https://support.apple.com/kb/HT211171",
  "serverity": "\u4e2d",
  "submitTime": "2020-10-25",
  "title": "Apple OS X libxpc\u4efb\u610f\u6587\u4ef6\u8986\u76d6\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…