flowiseai vulnerabilities

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the text-to-speech generation endpoint (POST /api/v1/text-to-speech/generate) is whitelisted (no auth) and accepts a credentialId directly in the request body. When called without a chatflowId, the endpoint uses the provided credentialId to decrypt the stored credential (e.g., OpenAI or ElevenLabs API key) and generate speech. This vulnerability is fixed in 3.1.0.

Flowise 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.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, a Mass Assignment vulnerability in the DocumentStore creation endpoint allows authenticated users to control the primary key (id) and internal state fields of DocumentStore entities. Because the service uses repository.save() with a client-supplied primary key, the POST create endpoint behaves as an implicit UPSERT operation. This enables overwriting existing DocumentStore objects. In multi-workspace or multi-tenant deployments, this can lead to cross-workspace object takeover and broken object-level authorization (IDOR), allowing an attacker to reassign or modify DocumentStore objects belonging to other workspaces. This vulnerability is fixed in 3.1.0.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, this vulnerability allows remote attackers to bypass authentication on affected installations of FlowiseAI Flowise. Authentication is not required to exploit this vulnerability. The specific flaw exists within the resetPassword method of the AccountService class. There is no check performed to ensure that a password reset token has actually been generated for a user account. By default the value of the reset token stored in a users account is null, or an empty string if they've reset their password before. An attacker with knowledge of the user's email address can submit a request to the "/api/v1/account/reset-password" endpoint containing a null or empty string reset token value and reset that user's password to a value of their choosing. This vulnerability is fixed in 3.1.0.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the password reset functionality on cloud.flowiseai.com sends a reset password link over the unsecured HTTP protocol instead of HTTPS. This behavior introduces the risk of a man-in-the-middle (MITM) attack, where an attacker on the same network as the user (e.g., public Wi-Fi) can intercept the reset link and gain unauthorized access to the victim’s account. This vulnerability is fixed in 3.1.0.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, Flowise contains an authentication bypass vulnerability that allows an unauthenticated attacker to obtain OAuth 2.0 access tokens associated with a public chatflow. By accessing a public chatflow configuration endpoint, an attacker can retrieve internal workflow data, including OAuth credential identifiers, which can then be used to refresh and obtain valid OAuth 2.0 access tokens without authentication. This vulnerability is fixed in 3.1.0.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the core security wrappers (secureAxiosRequest and secureFetch) intended to prevent Server-Side Request Forgery (SSRF) contain multiple logic flaws. These flaws allow attackers to bypass the allow/deny lists via DNS Rebinding (Time-of-Check Time-of-Use) or by exploiting the default configuration which fails to enforce any deny list. This vulnerability is fixed in 3.1.0.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, a Server-Side Request Forgery (SSRF) vulnerability exists in FlowiseAI's POST/GET API Chain components that allows unauthenticated attackers to force the server to make arbitrary HTTP requests to internal and external systems. By injecting malicious prompt templates, attackers can bypass the intended API documentation constraints and redirect requests to sensitive internal services, potentially leading to internal network reconnaissance and data exfiltration. This vulnerability is fixed in 3.1.0.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, a Server-Side Request Forgery (SSRF) protection bypass vulnerability exists in the Custom Function feature. While the application implements SSRF protection via HTTP_DENY_LIST for axios and node-fetch libraries, the built-in Node.js http, https, and net modules are allowed in the NodeVM sandbox without equivalent protection. This allows authenticated users to bypass SSRF controls and access internal network resources (e.g., cloud provider metadata services) This vulnerability is fixed in 3.1.0.

Flowise 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.

Flowise 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.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, /api/v1/public-chatbotConfig/:id ep exposes sensitive data including API keys, HTTP authorization headers and internal configuration without any authentication. An attacker with knowledge just of a chatflow UUID can retrieve credentials stored in password type fields and HTTP headers, leading to credential theft and more. This vulnerability is fixed in 3.1.0.

Flowise 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.

Flowise 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.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.0.13, the NVIDIA NIM router (/api/v1/nvidia-nim/*) is whitelisted in the global authentication middleware, allowing unauthenticated access to privileged container management and token generation endpoints. This issue has been patched in version 3.0.13.

Flowise 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.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.0.13, unauthenticated users can inject arbitrary values into internal database fields when creating leads. This issue has been patched in version 3.0.13.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.0.13, the /api/v1/attachments/:chatflowId/:chatId endpoint is listed in WHITELIST_URLS, allowing unauthenticated access to the file upload API. While the server validates uploads based on the MIME types defined in chatbotConfig.fullFileUpload.allowedUploadFileTypes, it implicitly trusts the client-provided Content-Type header (file.mimetype) without verifying the file's actual content (magic bytes) or extension (file.originalname). Consequently, an attacker can bypass this restriction by spoofing the Content-Type as a permitted type (e.g., application/pdf) while uploading malicious scripts or arbitrary files. Once uploaded via addArrayFilesToStorage, these files persist in backend storage (S3, GCS, or local disk). This vulnerability serves as a critical entry point that, when chained with other features like static hosting or file retrieval, can lead to Stored XSS, malicious file hosting, or Remote Code Execution (RCE). This issue has been patched in version 3.0.13.

Flowise 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.

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. 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 before 3.0.5 allows XSS via an IFRAME element when an admin views the chat log.

Flowise before 3.0.5 allows XSS via a FORM element and an INPUT element when an admin views the chat log.

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 <= 2.2.3 is vulnerable to SQL Injection. via tableName parameter at Postgres_VectorStores.

An Unauthenticated Denial of Service (DoS) vulnerability exists in Flowise version 1.8.2 leading to a complete crash of the instance running a vulnerable version due to improper handling of user supplied input to the “/api/v1/get-upload-file” api endpoint.

Flowise is a drag & drop user interface to build a customized large language model flow. In version 1.4.3 of Flowise, A CORS misconfiguration sets the Access-Control-Allow-Origin header to all, allowing arbitrary origins to connect to the website. In the default configuration (unauthenticated), arbitrary origins may be able to make requests to Flowise, stealing information from the user. This CORS misconfiguration may be chained with the path injection to allow an attacker attackers without access to Flowise to read arbitrary files from the Flowise server. As of time of publication, no known patches are available.

Flowise is a drag & drop user interface to build a customized large language model flow. In version 1.4.3 of Flowise, the `/api/v1/openai-assistants-file` endpoint in `index.ts` is vulnerable to arbitrary file read due to lack of sanitization of the `fileName` body parameter. No known patches for this issue are available.

An issue in FlowiseAI Inc Flowise v.1.6.2 and before allows a remote attacker to execute arbitrary code via a crafted script to the api/v1 component.