GCVE Workshop - 22 September 2026 (14:00-18:00), Luxembourg Before The Vulnopticon Conference - Registration

CNVD-2025-24049

Vulnerability from cnvd - Published: 2025-10-17
VLAI
Title
Huawei HarmonyOS拒绝服务漏洞(CNVD-2025-24049)
Description
Huawei HarmonyOS是中国华为(Huawei)公司的一个操作系统。提供一个基于微内核的全场景分布式操作系统。 Huawei HarmonyOS存在拒绝服务漏洞,攻击者可利用该漏洞影响可用性。
Severity
Patch Name
Huawei HarmonyOS拒绝服务漏洞(CNVD-2025-24049)的补丁
Patch Description
Huawei HarmonyOS是中国华为(Huawei)公司的一个操作系统。提供一个基于微内核的全场景分布式操作系统。 Huawei HarmonyOS存在拒绝服务漏洞,攻击者可利用该漏洞影响可用性。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

厂商已发布了漏洞修复程序,请及时关注更新: https://consumer.huawei.com/en/support/bulletin/2025/10/

Reference
https://consumer.huawei.com/en/support/bulletin/2025/10/
Impacted products
Name
['Huawei HarmonyOS 5.0.1', 'Huawei HarmonyOS 5.1.0']
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2025-58292",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2025-58292"
    }
  },
  "description": "Huawei HarmonyOS\u662f\u4e2d\u56fd\u534e\u4e3a\uff08Huawei\uff09\u516c\u53f8\u7684\u4e00\u4e2a\u64cd\u4f5c\u7cfb\u7edf\u3002\u63d0\u4f9b\u4e00\u4e2a\u57fa\u4e8e\u5fae\u5185\u6838\u7684\u5168\u573a\u666f\u5206\u5e03\u5f0f\u64cd\u4f5c\u7cfb\u7edf\u3002\n\nHuawei HarmonyOS\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5f71\u54cd\u53ef\u7528\u6027\u3002",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://consumer.huawei.com/en/support/bulletin/2025/10/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2025-24049",
  "openTime": "2025-10-17",
  "patchDescription": "Huawei HarmonyOS\u662f\u4e2d\u56fd\u534e\u4e3a\uff08Huawei\uff09\u516c\u53f8\u7684\u4e00\u4e2a\u64cd\u4f5c\u7cfb\u7edf\u3002\u63d0\u4f9b\u4e00\u4e2a\u57fa\u4e8e\u5fae\u5185\u6838\u7684\u5168\u573a\u666f\u5206\u5e03\u5f0f\u64cd\u4f5c\u7cfb\u7edf\u3002\r\n\r\nHuawei HarmonyOS\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5f71\u54cd\u53ef\u7528\u6027\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": "Huawei HarmonyOS\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff08CNVD-2025-24049\uff09\u7684\u8865\u4e01",
  "products": {
    "product": [
      "Huawei HarmonyOS 5.0.1",
      "Huawei HarmonyOS 5.1.0"
    ]
  },
  "referenceLink": "https://consumer.huawei.com/en/support/bulletin/2025/10/",
  "serverity": "\u4f4e",
  "submitTime": "2025-10-15",
  "title": "Huawei HarmonyOS\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff08CNVD-2025-24049\uff09"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

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.


Loading…