CVE-2025-61687
Flowiseai Flowise 3.0.7
Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:H/A:HSummary
CVE-2025-61687 is a high-severity Unrestricted Upload of File with Dangerous Type (CWE-434) vulnerability in Flowiseai Flowise. Its CVSS base score is 8.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to SI-3 (Malicious Code Protection) and CM-7 (Least Functionality) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2025-61687 is a file upload vulnerability in version 3.0.7 of FlowiseAI, an open-source drag-and-drop user interface for building customized large language model (LLM) flows. The issue stems from inadequate validation during file uploads, as the system fails to check file extensions, MIME types, or file content. This allows authenticated users to upload arbitrary files, including malicious Node.js web shells, which are persistently stored on the server. The vulnerability is rated high severity with a CVSS v3.1 base score of 8.3 (AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:H/A:H) and is associated with CWE-434 (Unrestricted Upload of File with Dangerous Type).
Authenticated attackers with low privileges can exploit this vulnerability remotely and with low complexity to upload Node.js-based web shells via the affected upload endpoints. These shells persist on the server and expose HTTP endpoints capable of executing arbitrary commands if triggered, such as through administrator error or chained vulnerabilities. While the uploaded files do not auto-execute, successful triggering leads to remote code execution (RCE), resulting in high impacts to integrity and availability, with low confidentiality impact.
No patched versions of FlowiseAI were available as of the CVE's publication on 2025-10-06T16:15:35.223. The vulnerable code is exposed in the FlowiseAI GitHub repository, specifically in packages/components/src/storageUtils.ts (lines 1104-1111, 170-175, and 533-541) and packages/server/src/controllers/attachments/index.ts (lines 4-11) and packages/server/src/routes/attachments/index.ts (line 8). Practitioners should audit these locations, restrict upload permissions, and implement comprehensive file validation until official fixes are released.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-33191
Vulnerability Data
Flowise is a drag & drop user interface to build a customized large language model flow. A file upload vulnerability in version 3.0.7 of FlowiseAI allows authenticated users to upload arbitrary files without proper validation. This enables attackers to persistently…
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store malicious Node.js web shells on the server, potentially leading to Remote Code Execution (RCE). The system fails to validate file extensions, MIME types, or file content during uploads. As a result, malicious scripts such as Node.js-based web shells can be uploaded and stored persistently on the server. These shells expose HTTP endpoints capable of executing arbitrary commands if triggered. The uploaded shell does not automatically execute, but its presence allows future exploitation via administrator error or chained vulnerabilities. This presents a high-severity threat to system integrity and confidentiality. As of time of publication, no known patched versions are available.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: flowise, large language model
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V5.1.1
Mitigating Controls (NIST 800-53 r5) AI
Malicious-code protection at entry points blocks dangerous file types from being accepted and executed.
Least functionality restricts the file types and automatic processing capabilities the system will accept.
Mobile-code controls define, authorize, and block unacceptable uploaded code before automatic processing occurs.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Restricting execution of unauthorized software directly blocks dangerous uploaded files from running.
Hardened configuration baselines can enforce allowed file types and processing rules.
Secure development practices include input validation and file-type restrictions that prevent this weakness.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Configuration and acceptance testing verify that file-upload handling enforces allowed types and does not permit dangerous content to be stored or executed.
Secure-coding guidelines and security testing explicitly address restrictions on allowed file types and upload handling, reducing the risk that dangerous file uploads are accepted without validation.
Mandated testing for malicious content and known vulnerabilities reduces the likelihood that an outsourced component will contain or accept dangerous file types that could later be uploaded or executed.
Application allow-listing and pre-use scanning of received files directly blocks the introduction of executable content that has not been vetted, eliminating the primary vector for unrestricted dangerous file uploads.