Vulnerability-Lookup

CNVD-2022-56261

Vulnerability from cnvd - Published: 2022-08-11

Title

SAP NetWeaver代码问题漏洞（CNVD-2022-56261）

Description

SAP Netweaver是德国思爱普（SAP）公司的一套面向服务的集成化应用平台。该平台主要为SAP应用程序提供开发和运行环境。 SAP NetWeaver存在代码问题漏洞。目前没有详细的漏洞细节提供。

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.sap.cn/index.html?campaigncode=crm-ya22-int-1517075&source=ppc-cn-baidu_ads-search-5715097-10407713-s4hana_s4hana-BZ_PC_Video

Reference

https://nvd.nist.gov/vuln/detail/CVE-2022-28217

Impacted products

Name
['SPA NetWeaver 7.4', 'SPA NetWeaver 7.31', 'SPA NetWeaver 7.30', 'SPA NetWeaver 7.50', 'SPA NetWeaver 7.20']

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    "cve": {
      "cveNumber": "CVE-2022-28217",
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  "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.sap.cn/index.html?campaigncode=crm-ya22-int-1517075\u0026source=ppc-cn-baidu_ads-search-5715097-10407713-s4hana_s4hana-BZ_PC_Video",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2022-56261",
  "openTime": "2022-08-11",
  "products": {
    "product": [
      "SPA NetWeaver 7.4",
      "SPA NetWeaver 7.31",
      "SPA NetWeaver 7.30",
      "SPA NetWeaver 7.50",
      "SPA NetWeaver 7.20"
    ]
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2022-28217",
  "serverity": "\u4e2d",
  "submitTime": "2022-07-01",
  "title": "SAP NetWeaver\u4ee3\u7801\u95ee\u9898\u6f0f\u6d1e\uff08CNVD-2022-56261\uff09"
}

CVE-2022-28217 (GCVE-0-2022-28217)

Vulnerability from cvelistv5 – Published: 2022-06-13 16:04 – Updated: 2024-08-03 05:48

Summary

Some part of SAP NetWeaver (EP Web Page Composer) does not sufficiently validate an XML document accepted from an untrusted source, which allows an adversary to exploit unprotected XML parking at endpoints, and a possibility to conduct SSRF attacks that could compromise system�s Availability by causing system to crash.

Severity

No CVSS data available.

CWE

CWE-918

Assigner

sap mitre root

References

2 references

URL	Tags
https://www.sap.com/documents/2022/02/fa865ea4-16…	x_refsource_MISC
https://launchpad.support.sap.com/#/notes/3148377	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
SAP SE	SAP NetWeaver (EP Web Page Composer)	Affected: 7.20 Affected: 7.30 Affected: 7.31 Affected: 7.40 Affected: 7.50

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JSON

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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.