CNVD-2022-87367

Vulnerability from cnvd - Published: 2022-12-14
VLAI
Title
Trend Micro Apex One越界访问漏洞
Description
Trend Micro Apex One是美国趋势科技(Trend Micro)公司的一款终端防护软件。 Trend Micro Apex One 2019 (on-prem)、SaaS版本存在越界访问漏洞,攻击者可利用漏洞创建特制消息以导致特定服务进程的内存损坏,这可能导致本地权限提升。
Severity
Patch Name
Trend Micro Apex One越界访问漏洞的补丁
Patch Description
Trend Micro Apex One是美国趋势科技(Trend Micro)公司的一款终端防护软件。 Trend Micro Apex One 2019 (on-prem)、SaaS版本存在越界访问漏洞,攻击者可利用漏洞创建特制消息以导致特定服务进程的内存损坏,这可能导致本地权限提升。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

目前厂商已发布升级补丁以修复漏洞,补丁获取链接: https://success.trendmicro.com/solution/000291645

Reference
https://success.trendmicro.com/solution/000291645
Impacted products
Name
['Trend Micro Apex One SaaS', 'Trend Micro Apex One 2019 (on-prem)']
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2022-41745",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2022-41745"
    }
  },
  "description": "Trend Micro Apex One\u662f\u7f8e\u56fd\u8d8b\u52bf\u79d1\u6280\uff08Trend Micro\uff09\u516c\u53f8\u7684\u4e00\u6b3e\u7ec8\u7aef\u9632\u62a4\u8f6f\u4ef6\u3002\n\nTrend Micro Apex One 2019 (on-prem)\u3001SaaS\u7248\u672c\u5b58\u5728\u8d8a\u754c\u8bbf\u95ee\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u6f0f\u6d1e\u521b\u5efa\u7279\u5236\u6d88\u606f\u4ee5\u5bfc\u81f4\u7279\u5b9a\u670d\u52a1\u8fdb\u7a0b\u7684\u5185\u5b58\u635f\u574f\uff0c\u8fd9\u53ef\u80fd\u5bfc\u81f4\u672c\u5730\u6743\u9650\u63d0\u5347\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6f0f\u6d1e\uff0c\u8865\u4e01\u83b7\u53d6\u94fe\u63a5\uff1a\r\nhttps://success.trendmicro.com/solution/000291645",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-87367",
  "openTime": "2022-12-14",
  "patchDescription": "Trend Micro Apex One\u662f\u7f8e\u56fd\u8d8b\u52bf\u79d1\u6280\uff08Trend Micro\uff09\u516c\u53f8\u7684\u4e00\u6b3e\u7ec8\u7aef\u9632\u62a4\u8f6f\u4ef6\u3002\r\n\r\nTrend Micro Apex One 2019 (on-prem)\u3001SaaS\u7248\u672c\u5b58\u5728\u8d8a\u754c\u8bbf\u95ee\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u6f0f\u6d1e\u521b\u5efa\u7279\u5236\u6d88\u606f\u4ee5\u5bfc\u81f4\u7279\u5b9a\u670d\u52a1\u8fdb\u7a0b\u7684\u5185\u5b58\u635f\u574f\uff0c\u8fd9\u53ef\u80fd\u5bfc\u81f4\u672c\u5730\u6743\u9650\u63d0\u5347\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": "Trend Micro Apex One\u8d8a\u754c\u8bbf\u95ee\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": [
      "Trend Micro Apex One SaaS",
      "Trend Micro Apex One 2019 (on-prem)"
    ]
  },
  "referenceLink": "https://success.trendmicro.com/solution/000291645",
  "serverity": "\u4f4e",
  "submitTime": "2022-10-12",
  "title": "Trend Micro Apex One\u8d8a\u754c\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

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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