CNVD-2021-100286
Vulnerability from cnvd - Published: 2021-12-16
VLAI
Title
Grafana路径遍历漏洞(CNVD-2021-100286)
Description
Grafana是Grafana实验室的一套提供可视化监控界面的开源监控工具。该工具主要用于监控和分析Graphite、InfluxDB和Prometheus等。
Grafana 中存在路径遍历漏洞,该漏洞源于产品未对csv文件做有效处理。该漏洞只存在于配置了testdata db数据源的数据库中。攻击者可通过该漏洞进行目录遍历。
Severity
低
Patch Name
Grafana路径遍历漏洞(CNVD-2021-100286)的补丁
Patch Description
Grafana是Grafana实验室的一套提供可视化监控界面的开源监控工具。该工具主要用于监控和分析Graphite、InfluxDB和Prometheus等。
Grafana 中存在路径遍历漏洞,该漏洞源于产品未对csv文件做有效处理。该漏洞只存在于配置了testdata db数据源的数据库中。攻击者可通过该漏洞进行目录遍历。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
目前厂商已发布升级补丁以修复漏洞,补丁获取链接: https://github.com/grafana/grafana/security/advisories/GHSA-7533-c8qv-jm9m
Reference
https://nvd.nist.gov/vuln/detail/CVE-2021-43815
Impacted products
| Name | ['Grafana Grafana <7.5.12', 'Grafana Grafana >=8.0.0,<8.3.2'] |
|---|
{
"cves": {
"cve": {
"cveNumber": "CVE-2021-43815"
}
},
"description": "Grafana\u662fGrafana\u5b9e\u9a8c\u5ba4\u7684\u4e00\u5957\u63d0\u4f9b\u53ef\u89c6\u5316\u76d1\u63a7\u754c\u9762\u7684\u5f00\u6e90\u76d1\u63a7\u5de5\u5177\u3002\u8be5\u5de5\u5177\u4e3b\u8981\u7528\u4e8e\u76d1\u63a7\u548c\u5206\u6790Graphite\u3001InfluxDB\u548cPrometheus\u7b49\u3002\n\nGrafana \u4e2d\u5b58\u5728\u8def\u5f84\u904d\u5386\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u4ea7\u54c1\u672a\u5bf9csv\u6587\u4ef6\u505a\u6709\u6548\u5904\u7406\u3002\u8be5\u6f0f\u6d1e\u53ea\u5b58\u5728\u4e8e\u914d\u7f6e\u4e86testdata db\u6570\u636e\u6e90\u7684\u6570\u636e\u5e93\u4e2d\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u8be5\u6f0f\u6d1e\u8fdb\u884c\u76ee\u5f55\u904d\u5386\u3002",
"formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6f0f\u6d1e\uff0c\u8865\u4e01\u83b7\u53d6\u94fe\u63a5\uff1a\r\nhttps://github.com/grafana/grafana/security/advisories/GHSA-7533-c8qv-jm9m",
"isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
"number": "CNVD-2021-100286",
"openTime": "2021-12-16",
"patchDescription": "Grafana\u662fGrafana\u5b9e\u9a8c\u5ba4\u7684\u4e00\u5957\u63d0\u4f9b\u53ef\u89c6\u5316\u76d1\u63a7\u754c\u9762\u7684\u5f00\u6e90\u76d1\u63a7\u5de5\u5177\u3002\u8be5\u5de5\u5177\u4e3b\u8981\u7528\u4e8e\u76d1\u63a7\u548c\u5206\u6790Graphite\u3001InfluxDB\u548cPrometheus\u7b49\u3002\r\n\r\nGrafana \u4e2d\u5b58\u5728\u8def\u5f84\u904d\u5386\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u4ea7\u54c1\u672a\u5bf9csv\u6587\u4ef6\u505a\u6709\u6548\u5904\u7406\u3002\u8be5\u6f0f\u6d1e\u53ea\u5b58\u5728\u4e8e\u914d\u7f6e\u4e86testdata db\u6570\u636e\u6e90\u7684\u6570\u636e\u5e93\u4e2d\u3002\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u8be5\u6f0f\u6d1e\u8fdb\u884c\u76ee\u5f55\u904d\u5386\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": "Grafana\u8def\u5f84\u904d\u5386\u6f0f\u6d1e\uff08CNVD-2021-100286\uff09\u7684\u8865\u4e01",
"products": {
"product": [
"Grafana Grafana \u003c7.5.12",
"Grafana Grafana \u003e=8.0.0\uff0c\u003c8.3.2"
]
},
"referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2021-43815",
"serverity": "\u4f4e",
"submitTime": "2021-12-14",
"title": "Grafana\u8def\u5f84\u904d\u5386\u6f0f\u6d1e\uff08CNVD-2021-100286\uff09"
}
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Nomenclature
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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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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.