Vulnerability-Lookup

CNVD-2026-20428

Vulnerability from cnvd - Published: 2026-05-18

Title

Apache CloudStack竞争条件问题漏洞

Description

Apache CloudStack是美国阿帕奇（Apache）基金会的一套基础架构即服务（IaaS）云计算平台。该平台主要用于部署和管理大型虚拟机网络。 Apache CloudStack存在竞争条件问题漏洞。该漏洞源于资源计数和增量逻辑中存在多个检查时间使用时间竞争条件以及缺少验证，攻击者可利用该漏洞导致用户超出分配限制，从而降低基础设施资源并导致拒绝服务。

Severity

高

Patch Name

Apache CloudStack竞争条件问题漏洞的补丁

Patch Description

Formal description

厂商已发布了漏洞修复程序，请及时关注更新： https://cloudstack.apache.org/downloads/

Reference

https://nvd.nist.gov/vuln/detail/CVE-2025-69233

Impacted products

Name
['Apache CloudStack >=4.0.0，<4.20.3.0', 'Apache CloudStack >=4.21.0.0，<4.22.0.1']

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{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2025-69233",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2025-69233"
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  "number": "CNVD-2026-20428",
  "openTime": "2026-05-18",
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  "serverity": "\u9ad8",
  "submitTime": "2026-05-11",
  "title": "Apache CloudStack\u7ade\u4e89\u6761\u4ef6\u95ee\u9898\u6f0f\u6d1e"
}

CVE-2025-69233 (GCVE-0-2025-69233)

Vulnerability from cvelistv5 – Published: 2026-05-08 12:19 – Updated: 2026-05-09 06:43

Title

Apache CloudStack: Domain/account resources limits not honored

Summary

Due to multiple time-of-check time-of-use race conditions in the resource count check and increment logic, as well as missing validations, users of the platform are able to exceed the allocation limits configured for their accounts/domains. This can be used by an attacker to degrade the infrastructure's resources and lead to denial of service conditions. Users are recommended to upgrade to Apache CloudStack versions 4.20.3.0 or 4.22.0.1, or later, which fixes this issue.

Severity

6.5 (Medium)


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

SSVC

Exploitation: none Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-05-08 13:55 UTC

CWE

CWE-367 - Time-of-check Time-of-use (TOCTOU) Race Condition
CWE-770 - Allocation of Resources Without Limits or Throttling

Assigner

apache mitre root

References

2 references

URL	Tags
https://lists.apache.org/thread/n8mt5b7wkpysstb8w…	vendor-advisory
http://www.openwall.com/lists/oss-security/2026/05/09/5

Impacted products

1 product

Vendor	Product	Version
Apache Software Foundation	Apache CloudStack	Affected: 4.0.0 , ≤ 4.20.2.0 (semver) Affected: 4.21.0.0 , ≤ 4.22.0.0 (semver)

Credits

Fernando Oliveira <ferolicar82@gmail.com> Gustavo Viana <viana.gust@gmail.com>

Show details on NVD website

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.