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CNVD-2019-39582

Vulnerability from cnvd - Published: 2019-11-07
VLAI
Title
Philips IntelliSpace Perinatal未授权访问漏洞
Description
Philips IntelliSpace Perinatal是欧洲飞利浦(Philips)公司的一套用于医疗行业的产科护理信息管理解决方案。 Philips IntelliSpace Perinatal K及之前版本中存在未授权访问漏洞,攻击者可利用该漏洞绕过应用程序的限制,访问Windows操作系统中未授权的信息。
Severity
Formal description

厂商尚未提供漏洞修复方案,请关注厂商主页更新: https://www.philips.com

Reference
https://www.us-cert.gov/ics/advisories/icsma-19-297-01
Impacted products
Name
Philips IntelliSpace Perinatal <=K
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2019-13546"
    }
  },
  "description": "Philips IntelliSpace Perinatal\u662f\u6b27\u6d32\u98de\u5229\u6d66\uff08Philips\uff09\u516c\u53f8\u7684\u4e00\u5957\u7528\u4e8e\u533b\u7597\u884c\u4e1a\u7684\u4ea7\u79d1\u62a4\u7406\u4fe1\u606f\u7ba1\u7406\u89e3\u51b3\u65b9\u6848\u3002\n\nPhilips IntelliSpace Perinatal K\u53ca\u4e4b\u524d\u7248\u672c\u4e2d\u5b58\u5728\u672a\u6388\u6743\u8bbf\u95ee\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u7ed5\u8fc7\u5e94\u7528\u7a0b\u5e8f\u7684\u9650\u5236\uff0c\u8bbf\u95eeWindows\u64cd\u4f5c\u7cfb\u7edf\u4e2d\u672a\u6388\u6743\u7684\u4fe1\u606f\u3002",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0\uff1a\r\nhttps://www.philips.com",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2019-39582",
  "openTime": "2019-11-07",
  "products": {
    "product": "Philips IntelliSpace Perinatal \u003c=K"
  },
  "referenceLink": "https://www.us-cert.gov/ics/advisories/icsma-19-297-01",
  "serverity": "\u9ad8",
  "submitTime": "2019-10-28",
  "title": "Philips IntelliSpace Perinatal\u672a\u6388\u6743\u8bbf\u95ee\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

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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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