CNVD-2019-17166

Vulnerability from cnvd - Published: 2019-06-13
VLAI
Title
Frappe ERPNext SQL注入漏洞
Description
Frappe ERPNext是一套开源的ERP(企业资源计划)系统。该系统包括财务管理、库存管理、客户关系管理、项目管理和人力资源管理等功能。 Frappe ERPNext 10.1.6版本中的‘sort_by’参数存在SQL注入漏洞,远程攻击者可通过发送特制的Web请求利用该漏洞查看、添加、修改或删除后端数据库中的信息。
Severity
中
Patch Name
Frappe ERPNext SQL注入漏洞的补丁
Patch Description
Frappe ERPNext是一套开源的ERP(企业资源计划)系统。该系统包括财务管理、库存管理、客户关系管理、项目管理和人力资源管理等功能。 Frappe ERPNext 10.1.6版本中的‘sort_by’参数存在SQL注入漏洞,远程攻击者可通过发送特制的Web请求利用该漏洞查看、添加、修改或删除后端数据库中的信息。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

厂商已发布了漏洞修复程序,请及时关注更新: https://github.com/CVEProject/cvelist/tree/master/2018/3xxx

Reference
https://github.com/CVEProject/cvelist/tree/master/2018/3xxx
Impacted products
Name
Frappe ERPNext 10.1.6
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2018-3884",
      "cveUrl": "http://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2018-3884"
    }
  },
  "description": "Frappe ERPNext\u662f\u4e00\u5957\u5f00\u6e90\u7684ERP\uff08\u4f01\u4e1a\u8d44\u6e90\u8ba1\u5212\uff09\u7cfb\u7edf\u3002\u8be5\u7cfb\u7edf\u5305\u62ec\u8d22\u52a1\u7ba1\u7406\u3001\u5e93\u5b58\u7ba1\u7406\u3001\u5ba2\u6237\u5173\u7cfb\u7ba1\u7406\u3001\u9879\u76ee\u7ba1\u7406\u548c\u4eba\u529b\u8d44\u6e90\u7ba1\u7406\u7b49\u529f\u80fd\u3002\n\nFrappe ERPNext 10.1.6\u7248\u672c\u4e2d\u7684\u2018sort_by\u2019\u53c2\u6570\u5b58\u5728SQL\u6ce8\u5165\u6f0f\u6d1e\uff0c\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u53d1\u9001\u7279\u5236\u7684Web\u8bf7\u6c42\u5229\u7528\u8be5\u6f0f\u6d1e\u67e5\u770b\u3001\u6dfb\u52a0\u3001\u4fee\u6539\u6216\u5220\u9664\u540e\u7aef\u6570\u636e\u5e93\u4e2d\u7684\u4fe1\u606f\u3002",
  "discovererName": "Yuri K",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://github.com/CVEProject/cvelist/tree/master/2018/3xxx",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2019-17166",
  "openTime": "2019-06-13",
  "patchDescription": "Frappe ERPNext\u662f\u4e00\u5957\u5f00\u6e90\u7684ERP\uff08\u4f01\u4e1a\u8d44\u6e90\u8ba1\u5212\uff09\u7cfb\u7edf\u3002\u8be5\u7cfb\u7edf\u5305\u62ec\u8d22\u52a1\u7ba1\u7406\u3001\u5e93\u5b58\u7ba1\u7406\u3001\u5ba2\u6237\u5173\u7cfb\u7ba1\u7406\u3001\u9879\u76ee\u7ba1\u7406\u548c\u4eba\u529b\u8d44\u6e90\u7ba1\u7406\u7b49\u529f\u80fd\u3002\r\n\r\nFrappe ERPNext 10.1.6\u7248\u672c\u4e2d\u7684\u2018sort_by\u2019\u53c2\u6570\u5b58\u5728SQL\u6ce8\u5165\u6f0f\u6d1e\uff0c\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u53d1\u9001\u7279\u5236\u7684Web\u8bf7\u6c42\u5229\u7528\u8be5\u6f0f\u6d1e\u67e5\u770b\u3001\u6dfb\u52a0\u3001\u4fee\u6539\u6216\u5220\u9664\u540e\u7aef\u6570\u636e\u5e93\u4e2d\u7684\u4fe1\u606f\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": "Frappe ERPNext SQL\u6ce8\u5165\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "Frappe ERPNext 10.1.6"
  },
  "referenceLink": "https://github.com/CVEProject/cvelist/tree/master/2018/3xxx",
  "serverity": "\u4e2d",
  "submitTime": "2018-09-11",
  "title": "Frappe ERPNext SQL\u6ce8\u5165\u6f0f\u6d1e"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

Drag nodes to arrange them. Double-click a related vulnerability to open it, or a source to visit its link. The Physics button on the left tunes the layout and the simulation; the legend at the bottom left hides or shows nodes by kind and by sighting type.

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.
Vulnerability timeline

Sightings and recorded dates, grouped by day · UTC

JSON
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.

Events included in the timeline

Loading timeline…


    Loading…

    Loading…

    Loading…

    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.