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CNVD-2025-24788

Vulnerability from cnvd - Published: 2025-10-24
VLAI
Title
Flowise文件上传漏洞(CNVD-2025-24788)
Description
Flowise是FlowiseAI开源的一个用于轻松构建LLM应用程序的工具。 Flowise 3.0.7版本存在文件上传漏洞,该漏洞源于文件上传过程中未验证文件扩展名、MIME类型或文件内容,攻击者可利用该漏洞导致远程代码执行。
Severity
Patch Name
Flowise文件上传漏洞(CNVD-2025-24788)的补丁
Patch Description
Flowise是FlowiseAI开源的一个用于轻松构建LLM应用程序的工具。 Flowise 3.0.7版本存在文件上传漏洞,该漏洞源于文件上传过程中未验证文件扩展名、MIME类型或文件内容,攻击者可利用该漏洞导致远程代码执行。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/FlowiseAI/Flowise/releases

Reference
https://github.com/FlowiseAI/Flowise/blob/d29db16bfcf9a4be8febc3d19d52263e8c3d0055/packages/components/src/storageUtils.ts#L1104-L1111
Impacted products
Name
FlowiseAI Flowise 3.0.7
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2025-61687",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2025-61687"
    }
  },
  "description": "Flowise\u662fFlowiseAI\u5f00\u6e90\u7684\u4e00\u4e2a\u7528\u4e8e\u8f7b\u677e\u6784\u5efaLLM\u5e94\u7528\u7a0b\u5e8f\u7684\u5de5\u5177\u3002\n\nFlowise 3.0.7\u7248\u672c\u5b58\u5728\u6587\u4ef6\u4e0a\u4f20\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u6587\u4ef6\u4e0a\u4f20\u8fc7\u7a0b\u4e2d\u672a\u9a8c\u8bc1\u6587\u4ef6\u6269\u5c55\u540d\u3001MIME\u7c7b\u578b\u6216\u6587\u4ef6\u5185\u5bb9\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\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/FlowiseAI/Flowise/releases",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2025-24788",
  "openTime": "2025-10-24",
  "patchDescription": "Flowise\u662fFlowiseAI\u5f00\u6e90\u7684\u4e00\u4e2a\u7528\u4e8e\u8f7b\u677e\u6784\u5efaLLM\u5e94\u7528\u7a0b\u5e8f\u7684\u5de5\u5177\u3002\r\n\r\nFlowise 3.0.7\u7248\u672c\u5b58\u5728\u6587\u4ef6\u4e0a\u4f20\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u6587\u4ef6\u4e0a\u4f20\u8fc7\u7a0b\u4e2d\u672a\u9a8c\u8bc1\u6587\u4ef6\u6269\u5c55\u540d\u3001MIME\u7c7b\u578b\u6216\u6587\u4ef6\u5185\u5bb9\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u8fdc\u7a0b\u4ee3\u7801\u6267\u884c\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": "Flowise\u6587\u4ef6\u4e0a\u4f20\u6f0f\u6d1e\uff08CNVD-2025-24788\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "FlowiseAI Flowise 3.0.7"
  },
  "referenceLink": "https://github.com/FlowiseAI/Flowise/blob/d29db16bfcf9a4be8febc3d19d52263e8c3d0055/packages/components/src/storageUtils.ts#L1104-L1111",
  "serverity": "\u9ad8",
  "submitTime": "2025-10-21",
  "title": "Flowise\u6587\u4ef6\u4e0a\u4f20\u6f0f\u6d1e\uff08CNVD-2025-24788\uff09"
}



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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

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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.

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Detection rules are retrieved from Rulezet.

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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.


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