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CNVD-2022-59018

Vulnerability from cnvd - Published: 2022-08-24
VLAI
Title
PEEL Shopping CMS SQL注入漏洞
Description
PEEL Shopping CMS是一个购物平台。 PEEL Shopping CMS 9.4.0版本存在SQL注入漏洞,该漏洞源于utilisateurs.php缺少对于SQL数据的过滤。属于管理员组的攻击者可利用该漏洞注入恶意 SQL 查询,以影响应用程序的执行逻辑并从数据库中检索信息。
Severity
Formal description

厂商尚未提供漏洞修复方案,请关注厂商主页更新: http://peel.com/

Reference
https://github.com/advisto/peel-shopping/issues/5
Impacted products
Name
PEEL Shopping CMS PEEL Shopping CMS 9.4.0
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-41672",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-41672"
    }
  },
  "description": "PEEL Shopping CMS\u662f\u4e00\u4e2a\u8d2d\u7269\u5e73\u53f0\u3002\n\nPEEL Shopping CMS 9.4.0\u7248\u672c\u5b58\u5728SQL\u6ce8\u5165\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8eutilisateurs.php\u7f3a\u5c11\u5bf9\u4e8eSQL\u6570\u636e\u7684\u8fc7\u6ee4\u3002\u5c5e\u4e8e\u7ba1\u7406\u5458\u7ec4\u7684\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u6ce8\u5165\u6076\u610f SQL \u67e5\u8be2\uff0c\u4ee5\u5f71\u54cd\u5e94\u7528\u7a0b\u5e8f\u7684\u6267\u884c\u903b\u8f91\u5e76\u4ece\u6570\u636e\u5e93\u4e2d\u68c0\u7d22\u4fe1\u606f\u3002",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0\uff1a\r\nhttp://peel.com/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-59018",
  "openTime": "2022-08-24",
  "products": {
    "product": "PEEL Shopping CMS PEEL Shopping CMS 9.4.0"
  },
  "referenceLink": "https://github.com/advisto/peel-shopping/issues/5",
  "serverity": "\u4e2d",
  "submitTime": "2022-06-17",
  "title": "PEEL Shopping CMS SQL\u6ce8\u5165\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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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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