Vulnerability-Lookup

CNVD-2020-44064

Vulnerability from cnvd - Published: 2020-08-03

Title

Cisco Data Center Network Manager命令注入漏洞

Description

Cisco Data Center Network Manager（DCNM）是美国思科（Cisco）公司的一套数据中心管理系统。该系统适用于Cisco Nexus和MDS系列交换机，提供存储可视化、配置和故障排除等功能。 Cisco DCNM 11.4(1)之前版本中的REST API端点存在安全漏洞，该漏洞源于程序没有正确验证用户输入。远程攻击者可借助特制请求利用该漏洞在系统上注入任意命令。

Severity

高

Patch Name

Cisco Data Center Network Manager命令注入漏洞的补丁

Patch Description

Formal description

厂商已发布了漏洞修复程序，请及时关注更新： https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-dcnm-rest-inj-BCt8pwAJ

Reference

https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-dcnm-rest-inj-BCt8pwAJ

Impacted products

Name
Cisco Cisco Data Center Network Manager <11.4(1)

Show details on source website

JSON

To clipboard

{
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    "cve": {
      "cveNumber": "CVE-2020-3384",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2020-3384"
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  "number": "CNVD-2020-44064",
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  "products": {
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  "referenceLink": "https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-dcnm-rest-inj-BCt8pwAJ",
  "serverity": "\u9ad8",
  "submitTime": "2020-07-30",
  "title": "Cisco Data Center Network Manager\u547d\u4ee4\u6ce8\u5165\u6f0f\u6d1e"
}

CVE-2020-3384 (GCVE-0-2020-3384)

Vulnerability from cvelistv5 – Published: 2020-07-31 00:00 – Updated: 2024-11-13 18:18

Title

Cisco Data Center Network Manager Command Injection Vulnerability

Summary

A vulnerability in specific REST API endpoints of Cisco Data Center Network Manager (DCNM) could allow an authenticated, remote attacker to inject arbitrary commands on the underlying operating system with the privileges of the logged-in user. The vulnerability is due to insufficient validation of user-supplied input to the API. An attacker could exploit this vulnerability by sending a crafted request to the API. A successful exploit could allow the attacker to inject arbitrary commands on the underlying operating system.

Severity

8.2 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:L/A:L

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-11-13 17:25 UTC

CWE

CWE-184

Assigner

cisco mitre root

References

1 reference

URL	Tags
https://tools.cisco.com/security/center/content/C…	vendor-advisoryx_refsource_CISCO

Impacted products

1 product

Vendor	Product	Version
Cisco	Cisco Data Center Network Manager	Affected: n/a

Date Public

2020-07-29 00:00

Show details on NVD website

JSON

To clipboard

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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.