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CNVD-2026-00694

Vulnerability from cnvd - Published: 2026-01-07
VLAI
Title
Computer Laboratory System文件上传漏洞
Description
Computer Laboratory System是一个计算机实验室系统。 Computer Laboratory System存在文件上传漏洞,该漏洞源于文件technical_staff_pic.php中参数image的错误操作,攻击者可利用该漏洞导致任意文件上传。
Severity
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://code-projects.org/

Reference
https://nvd.nist.gov/vuln/detail/CVE-2025-14642
Impacted products
Name
Computer Laboratory System Computer Laboratory System 1.0
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2025-14642",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2025-14642"
    }
  },
  "description": "Computer Laboratory System\u662f\u4e00\u4e2a\u8ba1\u7b97\u673a\u5b9e\u9a8c\u5ba4\u7cfb\u7edf\u3002\n\nComputer Laboratory System\u5b58\u5728\u6587\u4ef6\u4e0a\u4f20\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u6587\u4ef6technical_staff_pic.php\u4e2d\u53c2\u6570image\u7684\u9519\u8bef\u64cd\u4f5c\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u4efb\u610f\u6587\u4ef6\u4e0a\u4f20\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://code-projects.org/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2026-00694",
  "openTime": "2026-01-07",
  "products": {
    "product": "Computer Laboratory System Computer Laboratory System 1.0"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2025-14642",
  "serverity": "\u4e2d",
  "submitTime": "2025-12-25",
  "title": "Computer Laboratory System\u6587\u4ef6\u4e0a\u4f20\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

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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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