CNVD-2022-54896
Vulnerability from cnvd - Published: 2022-08-03
VLAI
Title
IBM QRadar SIEM权限许可和访问控制问题漏洞
Description
IBM QRadar SIEM是美国IBM公司的一套利用安全智能保护资产和信息远离高级威胁的解决方案。该方案提供对整个IT架构范围进行监督、生成详细的数据访问和用户活动报告等功能。
IBM QRadar SIEM存在权限许可和访问控制问题漏洞。攻击者利用该漏洞绕过IBM QRadar SIEM的限制,以提升他的权限。
Severity
中
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: https://www.ibm.com/cn-zh/qradar
Reference
https://nvd.nist.gov/vuln/detail/CVE-2021-39088
Impacted products
| Name | IBM IBM QRadar SIEM |
|---|
{
"cves": {
"cve": {
"cveNumber": "CVE-2021-39088",
"cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-39088"
}
},
"description": "IBM QRadar SIEM\u662f\u7f8e\u56fdIBM\u516c\u53f8\u7684\u4e00\u5957\u5229\u7528\u5b89\u5168\u667a\u80fd\u4fdd\u62a4\u8d44\u4ea7\u548c\u4fe1\u606f\u8fdc\u79bb\u9ad8\u7ea7\u5a01\u80c1\u7684\u89e3\u51b3\u65b9\u6848\u3002\u8be5\u65b9\u6848\u63d0\u4f9b\u5bf9\u6574\u4e2aIT\u67b6\u6784\u8303\u56f4\u8fdb\u884c\u76d1\u7763\u3001\u751f\u6210\u8be6\u7ec6\u7684\u6570\u636e\u8bbf\u95ee\u548c\u7528\u6237\u6d3b\u52a8\u62a5\u544a\u7b49\u529f\u80fd\u3002\n\nIBM QRadar SIEM\u5b58\u5728\u6743\u9650\u8bb8\u53ef\u548c\u8bbf\u95ee\u63a7\u5236\u95ee\u9898\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u5229\u7528\u8be5\u6f0f\u6d1e\u7ed5\u8fc7IBM QRadar SIEM\u7684\u9650\u5236\uff0c\u4ee5\u63d0\u5347\u4ed6\u7684\u6743\u9650\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\nhttps://www.ibm.com/cn-zh/qradar",
"isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
"number": "CNVD-2022-54896",
"openTime": "2022-08-03",
"products": {
"product": "IBM IBM QRadar SIEM"
},
"referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2021-39088",
"serverity": "\u4e2d",
"submitTime": "2022-07-28",
"title": "IBM QRadar SIEM\u6743\u9650\u8bb8\u53ef\u548c\u8bbf\u95ee\u63a7\u5236\u95ee\u9898\u6f0f\u6d1e"
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
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
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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.