CNVD-2025-17307

Vulnerability from cnvd - Published: 2025-07-31
VLAI
Title
WordPress Mine CloudVod跨站脚本漏洞
Description
WordPress Mine CloudVod是一款用于音视频播放和在线教育管理的插件。 WordPress Mine CloudVod存在跨站脚本漏洞,该漏洞源于输入清理和输出转义不足,攻击者可利用该漏洞通过注入恶意脚本,这些脚本将在用户访问注入的页面时执行。
Severity
中
Formal description

目前厂商尚未发布升级程序修复该安全问题,详情见厂商官网: https://wordpress.org/

Reference
https://nvd.nist.gov/vuln/detail/CVE-2025-8071
Impacted products
Name
WordPress Mine CloudVod <=2.1.10
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2025-8071",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2025-8071"
    }
  },
  "description": "WordPress Mine CloudVod\u662f\u4e00\u6b3e\u7528\u4e8e\u97f3\u89c6\u9891\u64ad\u653e\u548c\u5728\u7ebf\u6559\u80b2\u7ba1\u7406\u7684\u63d2\u4ef6\u3002\n\nWordPress Mine CloudVod\u5b58\u5728\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u8f93\u5165\u6e05\u7406\u548c\u8f93\u51fa\u8f6c\u4e49\u4e0d\u8db3\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u901a\u8fc7\u6ce8\u5165\u6076\u610f\u811a\u672c\uff0c\u8fd9\u4e9b\u811a\u672c\u5c06\u5728\u7528\u6237\u8bbf\u95ee\u6ce8\u5165\u7684\u9875\u9762\u65f6\u6267\u884c\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5c1a\u672a\u53d1\u5e03\u5347\u7ea7\u7a0b\u5e8f\u4fee\u590d\u8be5\u5b89\u5168\u95ee\u9898\uff0c\u8be6\u60c5\u89c1\u5382\u5546\u5b98\u7f51\uff1a\r\nhttps://wordpress.org/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2025-17307",
  "openTime": "2025-07-31",
  "products": {
    "product": "WordPress Mine CloudVod \u003c=2.1.10"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2025-8071",
  "serverity": "\u4e2d",
  "submitTime": "2025-07-30",
  "title": "WordPress Mine CloudVod\u8de8\u7ad9\u811a\u672c\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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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.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

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How durations are calculated

Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.

Each result shows its source dates. A negative interval means the end event came first; when date-only inputs leave the order open, the result says so. Date-only inputs are approximate. The earliest evidence wins: KEV report dates and sightings are labelled as such. Records describing another vulnerability are listed but never calculated from, and a PoC alone does not establish exploitation. Missing patch evidence does not prove that no patch exists. Filters below change the event list only.

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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.