CNVD-2015-07809
Vulnerability from cnvd - Published: 2015-11-27
VLAI
Title
SAP Manufacturing Integration and Intelligence加密降级漏洞
Description
SAP Manufacturing Integration and Intelligence(又名MII,前称xMII)是德国思爱普(SAP)公司的一套将核心的生产制造系统与企业流程集成的平台。该平台提供了用于企业自由创建融合了制造执行和企业工作流程的复合应用和SAP ERP系统与SAP ME系统的集成等功能。
SAP MII中存在安全漏洞,该漏洞源于程序使用弱加密算法(Base64和DES)。攻击者可利用该漏洞实施降级攻击,破解密码。
Severity
中
Patch Name
SAP Manufacturing Integration and Intelligence加密降级漏洞的补丁
Patch Description
SAP Manufacturing Integration and Intelligence(又名MII,前称xMII)是德国思爱普(SAP)公司的一套将核心的生产制造系统与企业流程集成的平台。该平台提供了用于企业自由创建融合了制造执行和企业工作流程的复合应用和SAP ERP系统与SAP ME系统的集成等功能。
SAP MII中存在安全漏洞,该漏洞源于程序使用弱加密算法(Base64和DES)。攻击者可利用该漏洞实施降级攻击,破解密码。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
目前厂商已经发布了升级补丁以修复此安全问题,详情请关注厂商主页: http://www.sap.com
Reference
http://erpscan.com/advisories/erpscan-15-031-using-base64-and-des-in-sap-mii/
Impacted products
| Name | SAP MII |
|---|
{
"cves": {
"cve": {
"cveNumber": "CVE-2015-8329"
}
},
"description": "SAP Manufacturing Integration and Intelligence\uff08\u53c8\u540dMII,\u524d\u79f0xMII\uff09\u662f\u5fb7\u56fd\u601d\u7231\u666e\uff08SAP\uff09\u516c\u53f8\u7684\u4e00\u5957\u5c06\u6838\u5fc3\u7684\u751f\u4ea7\u5236\u9020\u7cfb\u7edf\u4e0e\u4f01\u4e1a\u6d41\u7a0b\u96c6\u6210\u7684\u5e73\u53f0\u3002\u8be5\u5e73\u53f0\u63d0\u4f9b\u4e86\u7528\u4e8e\u4f01\u4e1a\u81ea\u7531\u521b\u5efa\u878d\u5408\u4e86\u5236\u9020\u6267\u884c\u548c\u4f01\u4e1a\u5de5\u4f5c\u6d41\u7a0b\u7684\u590d\u5408\u5e94\u7528\u548cSAP ERP\u7cfb\u7edf\u4e0eSAP ME\u7cfb\u7edf\u7684\u96c6\u6210\u7b49\u529f\u80fd\u3002\r\n\r\nSAP MII\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u7a0b\u5e8f\u4f7f\u7528\u5f31\u52a0\u5bc6\u7b97\u6cd5\uff08Base64\u548cDES\uff09\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5b9e\u65bd\u964d\u7ea7\u653b\u51fb\uff0c\u7834\u89e3\u5bc6\u7801\u3002",
"discovererName": "Mathieu GELI",
"formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u7ecf\u53d1\u5e03\u4e86\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6b64\u5b89\u5168\u95ee\u9898\uff0c\u8be6\u60c5\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\uff1a\r\nhttp://www.sap.com",
"isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
"number": "CNVD-2015-07809",
"openTime": "2015-11-27",
"patchDescription": "SAP Manufacturing Integration and Intelligence\uff08\u53c8\u540dMII,\u524d\u79f0xMII\uff09\u662f\u5fb7\u56fd\u601d\u7231\u666e\uff08SAP\uff09\u516c\u53f8\u7684\u4e00\u5957\u5c06\u6838\u5fc3\u7684\u751f\u4ea7\u5236\u9020\u7cfb\u7edf\u4e0e\u4f01\u4e1a\u6d41\u7a0b\u96c6\u6210\u7684\u5e73\u53f0\u3002\u8be5\u5e73\u53f0\u63d0\u4f9b\u4e86\u7528\u4e8e\u4f01\u4e1a\u81ea\u7531\u521b\u5efa\u878d\u5408\u4e86\u5236\u9020\u6267\u884c\u548c\u4f01\u4e1a\u5de5\u4f5c\u6d41\u7a0b\u7684\u590d\u5408\u5e94\u7528\u548cSAP ERP\u7cfb\u7edf\u4e0eSAP ME\u7cfb\u7edf\u7684\u96c6\u6210\u7b49\u529f\u80fd\u3002\r\n\r\nSAP MII\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u7a0b\u5e8f\u4f7f\u7528\u5f31\u52a0\u5bc6\u7b97\u6cd5\uff08Base64\u548cDES\uff09\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5b9e\u65bd\u964d\u7ea7\u653b\u51fb\uff0c\u7834\u89e3\u5bc6\u7801\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": "SAP Manufacturing Integration and Intelligence\u52a0\u5bc6\u964d\u7ea7\u6f0f\u6d1e\u7684\u8865\u4e01",
"products": {
"product": "SAP MII"
},
"referenceLink": "http://erpscan.com/advisories/erpscan-15-031-using-base64-and-des-in-sap-mii/",
"serverity": "\u4e2d",
"submitTime": "2015-11-26",
"title": "SAP Manufacturing Integration and Intelligence\u52a0\u5bc6\u964d\u7ea7\u6f0f\u6d1e"
}
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.
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
Loading timeline…
Loading…
Loading…
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.
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.