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CNVD-2025-08783

Vulnerability from cnvd - Published: 2025-04-29
VLAI
Title
Adobe Commerce访问控制错误漏洞(CNVD-2025-08783)
Description
Adobe Commerce是一款面向商家和品牌的全球领先的数字商务解决方案。 Adobe Commerce存在访问控制错误漏洞,该漏洞源于访问控制不当,目前没有详细的漏洞细节提供。
Severity
Patch Name
Adobe Commerce访问控制错误漏洞(CNVD-2025-08783)的补丁
Patch Description
Adobe Commerce是一款面向商家和品牌的全球领先的数字商务解决方案。 Adobe Commerce存在访问控制错误漏洞,该漏洞源于访问控制不当,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

目前厂商已发布升级程序修复该安全问题,详情见厂商官网: https://helpx.adobe.com/security/products/magento/apsb25-26.html

Reference
https://nvd.nist.gov/vuln/detail/CVE-2025-27190
Impacted products
Name
['Adobe Commerce <=2.4.7-p4', 'Adobe Commerce <=2.4.6-p9', 'Adobe Commerce <=2.4.5-p11', 'Adobe Commerce <=2.4.4-p12', 'Adobe Commerce <=2.4.8-beta2']
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2025-27190",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2025-27190"
    }
  },
  "description": "Adobe Commerce\u662f\u4e00\u6b3e\u9762\u5411\u5546\u5bb6\u548c\u54c1\u724c\u7684\u5168\u7403\u9886\u5148\u7684\u6570\u5b57\u5546\u52a1\u89e3\u51b3\u65b9\u6848\u3002\n\nAdobe Commerce\u5b58\u5728\u8bbf\u95ee\u63a7\u5236\u9519\u8bef\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u8bbf\u95ee\u63a7\u5236\u4e0d\u5f53\uff0c\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u7684\u6f0f\u6d1e\u7ec6\u8282\u63d0\u4f9b\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u7a0b\u5e8f\u4fee\u590d\u8be5\u5b89\u5168\u95ee\u9898\uff0c\u8be6\u60c5\u89c1\u5382\u5546\u5b98\u7f51\uff1a\r\nhttps://helpx.adobe.com/security/products/magento/apsb25-26.html",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2025-08783",
  "openTime": "2025-04-29",
  "patchDescription": "Adobe Commerce\u662f\u4e00\u6b3e\u9762\u5411\u5546\u5bb6\u548c\u54c1\u724c\u7684\u5168\u7403\u9886\u5148\u7684\u6570\u5b57\u5546\u52a1\u89e3\u51b3\u65b9\u6848\u3002\r\n\r\nAdobe Commerce\u5b58\u5728\u8bbf\u95ee\u63a7\u5236\u9519\u8bef\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u8bbf\u95ee\u63a7\u5236\u4e0d\u5f53\uff0c\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": "Adobe Commerce\u8bbf\u95ee\u63a7\u5236\u9519\u8bef\u6f0f\u6d1e\uff08CNVD-2025-08783\uff09\u7684\u8865\u4e01",
  "products": {
    "product": [
      "Adobe Commerce \u003c=2.4.7-p4",
      "Adobe Commerce  \u003c=2.4.6-p9",
      "Adobe Commerce \u003c=2.4.5-p11",
      "Adobe Commerce \u003c=2.4.4-p12",
      "Adobe Commerce \u003c=2.4.8-beta2"
    ]
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2025-27190",
  "serverity": "\u4e2d",
  "submitTime": "2025-04-18",
  "title": "Adobe Commerce\u8bbf\u95ee\u63a7\u5236\u9519\u8bef\u6f0f\u6d1e\uff08CNVD-2025-08783\uff09"
}



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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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