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

CNVD-2025-06064

Vulnerability from cnvd - Published: 2025-03-28
VLAI
Title
LibreChat拒绝服务漏洞(CNVD-2025-06064)
Description
LibreChat是的一个增强的ChatGPT克隆。 LibreChat存在拒绝服务漏洞,该漏洞源于某些API端点接收到格式错误的输入时未正确处理,攻击者可利用该漏洞导致服务器崩溃。
Severity
Patch Name
LibreChat拒绝服务漏洞(CNVD-2025-06064)的补丁
Patch Description
LibreChat是的一个增强的ChatGPT克隆。 LibreChat存在拒绝服务漏洞,该漏洞源于某些API端点接收到格式错误的输入时未正确处理,攻击者可利用该漏洞导致服务器崩溃。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://github.com/danny-avila/librechat/commit/95a212534f1c5991bd1231a34ac3668b4b592cc3

Reference
https://github.com/danny-avila/librechat/commit/95a212534f1c5991bd1231a34ac3668b4b592cc3
Impacted products
Name
LibreChat LibreChat <0.7.6
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2024-11173",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2024-11173"
    }
  },
  "description": "LibreChat\u662f\u7684\u4e00\u4e2a\u589e\u5f3a\u7684ChatGPT\u514b\u9686\u3002\n\nLibreChat\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u67d0\u4e9bAPI\u7aef\u70b9\u63a5\u6536\u5230\u683c\u5f0f\u9519\u8bef\u7684\u8f93\u5165\u65f6\u672a\u6b63\u786e\u5904\u7406\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u670d\u52a1\u5668\u5d29\u6e83\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://github.com/danny-avila/librechat/commit/95a212534f1c5991bd1231a34ac3668b4b592cc3",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2025-06064",
  "openTime": "2025-03-28",
  "patchDescription": "LibreChat\u662f\u7684\u4e00\u4e2a\u589e\u5f3a\u7684ChatGPT\u514b\u9686\u3002\r\n\r\nLibreChat\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u67d0\u4e9bAPI\u7aef\u70b9\u63a5\u6536\u5230\u683c\u5f0f\u9519\u8bef\u7684\u8f93\u5165\u65f6\u672a\u6b63\u786e\u5904\u7406\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u670d\u52a1\u5668\u5d29\u6e83\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": "LibreChat\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff08CNVD-2025-06064\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "LibreChat LibreChat \u003c0.7.6"
  },
  "referenceLink": "https://github.com/danny-avila/librechat/commit/95a212534f1c5991bd1231a34ac3668b4b592cc3",
  "serverity": "\u4e2d",
  "submitTime": "2025-03-27",
  "title": "LibreChat\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\uff08CNVD-2025-06064\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…