Flowise v3.0.1 < 3.0.8 and all versions after with 'ALLOW_BUILTIN_DEP' enabled contain an authenticated remote code execution vulnerability and node VM sandbox escape due to insecure use of integrated modules (Puppeteer and Playwright) within the nodevm execution environment. An authenticated attacker able to create or run a tool that leverages Puppeteer/Playwright can specify attacker-controlled browser binary paths and parameters. When the tool executes, the attacker-controlled executable/parameters are run on the host and circumvent the intended nodevm sandbox restrictions, resulting in execution of arbitrary code in the context of the host. This vulnerability was incorrectly assigned as a duplicate CVE-2025-26319 by the developers and should be considered distinct from that identifier.
Flowise is a drag & drop user interface to build a customized large language model flow. In versions prior to 3.0.8, WriteFileTool and ReadFileTool in Flowise do not restrict file path access, allowing authenticated attackers to exploit this vulnerability to read and write arbitrary files to any path in the file system, potentially leading to remote command execution. Flowise 3.0.8 fixes this vulnerability.
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 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.
Flowise is a drag & drop user interface to build a customized large language model flow. In version 3.0.5, a Server-Side Request Forgery (SSRF) vulnerability was discovered in the /api/v1/fetch-links endpoint of the Flowise application. This vulnerability allows an attacker to use the Flowise server as a proxy to access internal network web services and explore their link structures. This issue has been patched in version 3.0.6.
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.
Flowise is a drag & drop user interface to build a customized large language model flow. In version 3.0.5 and earlier, the `forgot-password` endpoint in Flowise returns sensitive information including a valid password reset `tempToken` without authentication or verification. This enables any attacker to generate a reset token for arbitrary users and directly reset their password, leading to a complete account takeover (ATO). This vulnerability applies to both the cloud service (`cloud.flowiseai.com`) and self-hosted/local Flowise deployments that expose the same API. Commit 9e178d68873eb876073846433a596590d3d9c863 in version 3.0.6 secures password reset endpoints. Several recommended remediation steps are available. Do not return reset tokens or sensitive account details in API responses. Tokens must only be delivered securely via the registered email channel. Ensure `forgot-password` responds with a generic success message regardless of input, to avoid user enumeration. Require strong validation of the `tempToken` (e.g., single-use, short expiry, tied to request origin, validated against email delivery). Apply the same fixes to both cloud and self-hosted/local deployments. Log and monitor password reset requests for suspicious activity. Consider multi-factor verification for sensitive accounts.
The Custom MCPs feature is designed to execute OS commands, for instance, using tools like `npx` to spin up local MCP Servers. However, Flowise's inherent authentication and authorization model is minimal and lacks role-based access controls (RBAC). Furthermore, in Flowise versions before 3.0.1 the default installation operates without authentication unless explicitly configured. This combination allows unauthenticated network attackers to execute unsandboxed OS commands.