CNVD-2015-00115
Vulnerability from cnvd - Published: 2015-01-07
VLAI
Title
Owl Intranet Knowledgebase存在多个跨站脚本漏洞
Description
Owl Intranet Knowledgebase是一款多用户文档管理系统。
Owl Intranet Knowledgebase 1.10存在多个跨站脚本漏洞,允许远程攻击者通过身份验证利用对browsephp或到prefsphp的标题字段的搜索注入任意web脚本或HTML。
Severity
低
Patch Name
Owl Intranet Knowledgebase存在多个跨站脚本漏洞的补丁
Patch Description
Owl Intranet Knowledgebase是一款多用户文档管理系统。
Owl Intranet Knowledgebase 1.10存在多个跨站脚本漏洞,允许远程攻击者通过身份验证利用对browsephp或到prefsphp的标题字段的搜索注入任意web脚本或HTML。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
用户可参考如下厂商提供的安全公告获取补丁以修复该漏洞: http://www.xchg.info/?p=400
Reference
http://www.xchg.info/?p=400
http://web.nvd.nist.gov/view/vuln/detail?vulnId=CVE-2013-4754
Impacted products
| Name | Sourceforge Owl Intranet Knowledgebase 1.10 |
|---|
{
"cves": {
"cve": {
"cveNumber": "CVE-2013-4754"
}
},
"description": "Owl Intranet Knowledgebase\u662f\u4e00\u6b3e\u591a\u7528\u6237\u6587\u6863\u7ba1\u7406\u7cfb\u7edf\u3002\r\n\r\nOwl Intranet Knowledgebase 1.10\u5b58\u5728\u591a\u4e2a\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u5141\u8bb8\u8fdc\u7a0b\u653b\u51fb\u8005\u901a\u8fc7\u8eab\u4efd\u9a8c\u8bc1\u5229\u7528\u5bf9browsephp\u6216\u5230prefsphp\u7684\u6807\u9898\u5b57\u6bb5\u7684\u641c\u7d22\u6ce8\u5165\u4efb\u610fweb\u811a\u672c\u6216HTML\u3002",
"discovererName": "unkown",
"formalWay": "\u7528\u6237\u53ef\u53c2\u8003\u5982\u4e0b\u5382\u5546\u63d0\u4f9b\u7684\u5b89\u5168\u516c\u544a\u83b7\u53d6\u8865\u4e01\u4ee5\u4fee\u590d\u8be5\u6f0f\u6d1e\uff1a\r\nhttp://www.xchg.info/?p=400",
"isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
"number": "CNVD-2015-00115",
"openTime": "2015-01-07",
"patchDescription": "Owl Intranet Knowledgebase\u662f\u4e00\u6b3e\u591a\u7528\u6237\u6587\u6863\u7ba1\u7406\u7cfb\u7edf\u3002\r\n\r\nOwl Intranet Knowledgebase 1.10\u5b58\u5728\u591a\u4e2a\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\uff0c\u5141\u8bb8\u8fdc\u7a0b\u653b\u51fb\u8005\u901a\u8fc7\u8eab\u4efd\u9a8c\u8bc1\u5229\u7528\u5bf9browsephp\u6216\u5230prefsphp\u7684\u6807\u9898\u5b57\u6bb5\u7684\u641c\u7d22\u6ce8\u5165\u4efb\u610fweb\u811a\u672c\u6216HTML\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": "Owl Intranet Knowledgebase\u5b58\u5728\u591a\u4e2a\u8de8\u7ad9\u811a\u672c\u6f0f\u6d1e\u7684\u8865\u4e01",
"products": {
"product": "Sourceforge Owl Intranet Knowledgebase 1.10"
},
"referenceLink": "http://www.xchg.info/?p=400\r\nhttp://web.nvd.nist.gov/view/vuln/detail?vulnId=CVE-2013-4754",
"serverity": "\u4f4e",
"submitTime": "2015-01-04",
"title": "Owl Intranet Knowledgebase\u5b58\u5728\u591a\u4e2a\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
| 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.
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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.
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.
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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.