CNVD-2017-00455

Vulnerability from cnvd - Published: 2017-01-16
VLAI
Title
多个Samsung Android Mobile Phones拒绝服务漏洞
Description
Samsung Android是韩国三星(Samsung)公司的一系列Android智能手机。 Samsung Android设备中存在安全漏洞。攻击者可借助特制的资源配置文件利用该漏洞造成系统崩溃,导致拒绝服务。
Severity
Patch Name
多个Samsung Android Mobile Phones拒绝服务漏洞的补丁
Patch Description
Samsung Android是韩国三星(Samsung)公司的一系列Android智能手机。 Samsung Android设备中存在安全漏洞。攻击者可借助特制的资源配置文件利用该漏洞造成系统崩溃,导致拒绝服务。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: http://security.samsungmobile.com/smrupdate.html#SMR-JAN-2017

Reference
http://security.samsungmobile.com/smrupdate.html#SMR-JAN-2017
Impacted products
Name
['Samsung Mobile Phones 4.4', 'Samsung Mobile Phones 5.0', 'Samsung Mobile Phones 5.1', 'Samsung Mobile Phones 6.0']
Show details on source website

{
  "bids": {
    "bid": {
      "bidNumber": "95319"
    }
  },
  "cves": {
    "cve": {
      "cveNumber": "CVE-2017-5217"
    }
  },
  "description": "Samsung Android\u662f\u97e9\u56fd\u4e09\u661f\uff08Samsung\uff09\u516c\u53f8\u7684\u4e00\u7cfb\u5217Android\u667a\u80fd\u624b\u673a\u3002\r\n\r\nSamsung Android\u8bbe\u5907\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684\u8d44\u6e90\u914d\u7f6e\u6587\u4ef6\u5229\u7528\u8be5\u6f0f\u6d1e\u9020\u6210\u7cfb\u7edf\u5d29\u6e83\uff0c\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\u3002",
  "discovererName": "Ryan Johnson and Angelos Stavrou of Kryptowire.",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttp://security.samsungmobile.com/smrupdate.html#SMR-JAN-2017",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2017-00455",
  "openTime": "2017-01-16",
  "patchDescription": "Samsung Android\u662f\u97e9\u56fd\u4e09\u661f\uff08Samsung\uff09\u516c\u53f8\u7684\u4e00\u7cfb\u5217Android\u667a\u80fd\u624b\u673a\u3002\r\n\r\nSamsung Android\u8bbe\u5907\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684\u8d44\u6e90\u914d\u7f6e\u6587\u4ef6\u5229\u7528\u8be5\u6f0f\u6d1e\u9020\u6210\u7cfb\u7edf\u5d29\u6e83\uff0c\u5bfc\u81f4\u62d2\u7edd\u670d\u52a1\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": "\u591a\u4e2aSamsung Android Mobile Phones\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": [
      "Samsung Mobile Phones 4.4",
      "Samsung Mobile Phones 5.0",
      "Samsung Mobile Phones 5.1",
      "Samsung Mobile Phones 6.0"
    ]
  },
  "referenceLink": "http://security.samsungmobile.com/smrupdate.html#SMR-JAN-2017",
  "serverity": "\u9ad8",
  "submitTime": "2017-01-11",
  "title": "\u591a\u4e2aSamsung Android Mobile Phones\u62d2\u7edd\u670d\u52a1\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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