- CVSS
- CRITICAL · 10v3.1CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
- Published
- 2025-09-22
- Weakness
- CWE-94
- Source
- nvd.nist.gov/vuln/detail/CVE-2025-59528
Description
Flowise is a drag & drop user interface to build a customized large language model flow. In version 3.0.5, Flowise is vulnerable to remote code execution. The CustomMCP node allows users to input configuration settings for connecting to an external MCP server. This node parses the user-provided mcpServerConfig string to build the MCP server configuration. However, during this process, it executes JavaScript code without any security validation. Specifically, inside the convertToValidJSONString function, user input is directly passed to the Function() constructor, which evaluates and executes the input as JavaScript code. Since this runs with full Node.js runtime privileges, it can access dangerous modules such as child_process and fs. This issue has been patched in version 3.0.6.
References
- https://github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/packages/components/nodes/tools/MCP/CustomMCP/CustomMCP.ts#L132
- https://github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/packages/components/nodes/tools/MCP/CustomMCP/CustomMCP.ts#L220
- https://github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/packages/components/nodes/tools/MCP/CustomMCP/CustomMCP.ts#L262-L270
- https://github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/packages/server/src/controllers/nodes/index.ts#L57-L78
- https://github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/packages/server/src/routes/node-load-methods/index.ts#L5
- https://github.com/FlowiseAI/Flowise/blob/5930f1119c655bcf8d2200ae827a1f5b9fec81d0/packages/server/src/services/nodes/index.ts#L91-L94
How GTK Cyber trains on this
AI security training at GTK Cyber covers the LLM and ML-pipeline vulnerability classes that vulnerabilities like CVE-2025-59528 fall into. Our hands-on courses are taught by Charles Givre and other practitioners who break and defend production AI systems.