nvd,anchore_overrides
Flowiseai
Vulnerabilities
67
Known exploited
0
Critical
16
High
39
Top vulnerabilities
CVE-2025-59528Flowise 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.
CVE-2026-40933Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, due to unsafe serialization of stdio commands in the MCP adapter, an authenticated attacker can add an MCP stdio server with an arbitrary command, achieving command execution. The vulnerability lies in a bug in the input sanitization from the “Custom MCP” configuration in http://localhost:3000/canvas - where any user can add a new MCP, when doing so - adding a new MCP using stdio, the user can add any command, even though your code have input sanitization checks such as validateCommandInjection and validateArgsForLocalFileAccess, and a list of predefined specific safe commands - these commands, for example "npx" can be combined with code execution arguments ("-c touch /tmp/pwn") that enable direct code execution on the underlying OS. This vulnerability is fixed in 3.1.0.
CVE-2025-61913Flowise 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.
CVE-2026-41268Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, Flowise is vulnerable to a critical unauthenticated remote command execution (RCE) vulnerability. It can be exploited via a parameter override bypass using the FILE-STORAGE:: keyword combined with a NODE_OPTIONS environment variable injection. This allows for the execution of arbitrary system commands with root privileges within the containerized Flowise instance, requiring only a single HTTP request and no authentication or knowledge of the instance. This vulnerability is fixed in 3.1.0.
CVE-2026-41267Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, an improper mass assignment (JSON injection) vulnerability in the account registration endpoint of Flowise Cloud allows unauthenticated attackers to inject server-managed fields and nested objects during account creation. This enables client-controlled manipulation of ownership metadata, timestamps, organization association, and role mappings, breaking trust boundaries in a multi-tenant environment. This vulnerability is fixed in 3.1.0.
CVE-2025-8943The 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.
CVE-2025-58434Flowise 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.
CVE-2025-55346User-controlled input flows to an unsafe implementation of a dynamic Function constructor, allowing network attackers to run arbitrary unsandboxed JS code in the context of the host, by sending a simple POST request.
CVE-2025-26319FlowiseAI Flowise v2.2.6 was discovered to contain an arbitrary file upload vulnerability in /api/v1/attachments.
CVE-2025-59434Flowise is a drag & drop user interface to build a customized large language model flow. Prior to August 2025 Cloud-Hosted Flowise, an authenticated vulnerability in Flowise Cloud allows any user on the free tier to access sensitive environment variables from other tenants via the Custom JavaScript Function node. This includes secrets such as OpenAI API keys, AWS credentials, Supabase tokens, and Google Cloud secrets — resulting in a full cross-tenant data exposure. This issue has been patched in the August 2025 Cloud-Hosted Flowise.
CVE-2026-46442Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, POST /api/v1/node-custom-function lacks route-level authorization, allowing any authenticated user or API key to submit arbitrary JavaScript to the Custom JS Function node. When E2B_APIKEY is not configured — the common deployment case — Flowise executes this code inside a NodeVM sandbox. This sandbox can be escaped, allowing an attacker to reach the host process object and execute system commands via child_process. The result is authenticated remote code execution on the Flowise server host. This issue has been patched in version 3.1.2.
CVE-2026-41137Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, The CSVAgent allows providing a custom Pandas CSV read code. Due to lack of sanitization, an attacker can provide a command injection payload that will get interpolated and executed by the server. This vulnerability is fixed in 3.1.0.
CVE-2026-41274Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the GraphCypherQAChain node forwards user-provided input directly into the Cypher query execution pipeline without proper sanitization. An attacker can inject arbitrary Cypher commands that are executed on the underlying Neo4j database, enabling data exfiltration, modification, or deletion. This vulnerability is fixed in 3.1.0.
CVE-2026-41265Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the specific flaw exists within the run method of the Airtable_Agents class. The issue results from the lack of proper sandboxing when evaluating an LLM generated python script. Using prompt injection techniques, an unauthenticated attacker with the ability to send prompts to a chatflow using the Airtable Agent node may convince an LLM to respond with a malicious python script that executes attacker controlled commands on the flowise server. This vulnerability is fixed in 3.1.0.
CVE-2026-41264Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the specific flaw exists within the run method of the CSV_Agents class. The issue results from the lack of proper sandboxing when evaluating an LLM generated python script. An attacker can leverage this vulnerability to execute code in the context of the user running the server. Using prompt injection techniques, an unauthenticated attacker with the ability to send prompts to a chatflow using the CSV Agent node may convince an LLM to respond with a malicious python script that executes attacker controlled commands on the Flowise server. This vulnerability is fixed in 3.1.0.
CVE-2026-46440Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, the checkBasicAuth endpoint validates credentials in plaintext without rate limiting and with direct comparison. This issue has been patched in version 3.1.2.
CVE-2026-41269Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the Chatflow configuration file upload settings can be modified to allow the application/javascript MIME type. This lets an attacker upload .js files even though the frontend doesn’t normally allow JavaScript uploads. This enables attackers to persistently store malicious Node.js web shells on the server, potentially leading to Remote Code Execution (RCE). This vulnerability is fixed in 3.1.0.
CVE-2026-41138Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, there is a remote code execution vulnerability in AirtableAgent.ts caused by lack of input verification when using Pandas. The user’s input is directly applied to the question parameter within the prompt template and it is reflected to the Python code without any sanitization. This vulnerability is fixed in 3.1.0.
CVE-2026-31829Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.0.13, Flowise exposes an HTTP Node in AgentFlow and Chatflow that performs server-side HTTP requests using user-controlled URLs. By default, there are no restrictions on target hosts, including private/internal IP ranges (RFC 1918), localhost, or cloud metadata endpoints. This enables Server-Side Request Forgery (SSRF), allowing any user interacting with a publicly exposed chatflow to force the Flowise server to make requests to internal network resources that are inaccessible from the public internet. This vulnerability is fixed in 3.0.13.
CVE-2026-30823Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.0.13, there is an IDOR vulnerability, leading to account takeover and enterprise feature bypass via SSO configuration. This issue has been patched in version 3.0.13.
CVE-2025-61687Flowise 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.
CVE-2026-46444Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, all CRUD endpoints for OpenAI Assistants Vector Store have no authentication middleware and the route path /api/v1/openai-assistants-vector-store is not in WHITELIST_URLS. However, it is also not protected by the main auth middleware when accessed via API key — the route requires API key auth (not whitelisted), but no permission checks exist on any operation. This issue has been patched in version 3.1.2.
CVE-2026-41278Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the GET /api/v1/public-chatflows/:id endpoint returns the full chatflow object without sanitization for public chatflows. Docker validation revealed this is worse than initially assessed: the sanitizeFlowDataForPublicEndpoint function does NOT exist in the released v3.0.13 Docker image. Both public-chatflows AND public-chatbotConfig return completely raw flowData including credential IDs, plaintext API keys, and password-type fields. This vulnerability is fixed in 3.1.0.
CVE-2026-30820Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.0.13, Flowise trusts any HTTP client that sets the header x-request-from: internal, allowing an authenticated tenant session to bypass all /api/v1/** authorization checks. With only a browser cookie, a low-privilege tenant can invoke internal administration endpoints (API key management, credential stores, custom function execution, etc.), effectively escalating privilege. This issue has been patched in version 3.0.13.
CVE-2025-34267Flowise 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.