Vulnerability-Lookup

CNVD-2020-73498

Vulnerability from cnvd - Published: 2020-12-23

Title

Coastercms跨站脚本漏洞

Description

Coastercms是Coastercms团队的一个在线商城的建站系统。 Coastercms v5.8.18版本存在跨站脚本漏洞，该漏洞允许攻击者可以窃取cookie，并使其重定向到任何恶意网站，因为它触发了产品应用程序的主页。

Severity

低

Formal description

目前厂商暂未发布修复措施解决此安全问题，建议使用此软件的用户随时关注厂商主页或参考网址以获取解决办法： http://demo.coastercms.org/

Reference

https://nvd.nist.gov/vuln/detail/CVE-2020-35275

Impacted products

Name
coastercms Coastercms v5.8.18

Show details on source website

JSON

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{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2020-35275",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2020-35275"
    }
  },
  "description": "Coastercms\u662fCoastercms\u56e2\u961f\u7684\u4e00\u4e2a\u5728\u7ebf\u5546\u57ce\u7684\u5efa\u7ad9\u7cfb\u7edf\u3002\n\nCoastercms v5.8.18\u7248\u672c\u5b58\u5728\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u5141\u8bb8\u653b\u51fb\u8005\u53ef\u4ee5\u7a83\u53d6cookie\uff0c\u5e76\u4f7f\u5176\u91cd\u5b9a\u5411\u5230\u4efb\u4f55\u6076\u610f\u7f51\u7ad9\uff0c\u56e0\u4e3a\u5b83\u89e6\u53d1\u4e86\u4ea7\u54c1\u5e94\u7528\u7a0b\u5e8f\u7684\u4e3b\u9875\u3002",
  "formalWay": "\u76ee\u524d\u5382\u5546\u6682\u672a\u53d1\u5e03\u4fee\u590d\u63aa\u65bd\u89e3\u51b3\u6b64\u5b89\u5168\u95ee\u9898\uff0c\u5efa\u8bae\u4f7f\u7528\u6b64\u8f6f\u4ef6\u7684\u7528\u6237\u968f\u65f6\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u6216\u53c2\u8003\u7f51\u5740\u4ee5\u83b7\u53d6\u89e3\u51b3\u529e\u6cd5\uff1a\r\nhttp://demo.coastercms.org/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2020-73498",
  "openTime": "2020-12-23",
  "products": {
    "product": "coastercms Coastercms v5.8.18"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2020-35275",
  "serverity": "\u4f4e",
  "submitTime": "2020-12-22",
  "title": "Coastercms\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e"
}

CVE-2020-35275 (GCVE-0-2020-35275)

Vulnerability from cvelistv5 – Published: 2020-12-21 14:51 – Updated: 2026-07-09 00:12

Summary

Coastercms v5.8.18 is affected by cross-site Scripting (XSS). A user can steal a cookie and make the user redirect to any malicious website because it is trigged on the main home page of the product/application.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

4 references

URL	Tags
http://demo.coastercms.org/admin/home
http://demo.coastercms.org/admin/login
http://demo.coastercms.org/homepage/blog
https://www.exploit-db.com/exploits/49181

Show details on NVD website

JSON

To clipboard

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        "title": "CVE Program Container"
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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.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

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.