FlowiseAI/Flowise

Flowise through 2.2.4 contains an unauthenticated arbitrary file upload vulnerability in the /api/v1/attachments endpoint when storageType is set to local. Attackers can exploit path traversal in the chatId and chatflowId parameters to upload malicious files to arbitrary directories, potentially enabling remote code execution and server compromise.

Flowise before 3.0.6 (affected versions 2.2.7-patch.1 and earlier) contains an unsandboxed remote code execution vulnerability in the Custom MCP feature, which is designed to execute OS commands such as launching local MCP servers. Because Flowise's authentication and authorization model is minimal and lacks role-based access control, and the default installation runs without authentication unless FLOWISE_USERNAME and FLOWISE_PASSWORD are set, an attacker can send a crafted JSON payload with the header 'x-request-from: internal' to the /api/v1/node-load-method/customMCP endpoint to execute arbitrary OS commands, resulting in complete compromise of the platform container or server.

Flowise before 3.0.10 (affected versions 3.0.7 and earlier) fails to invalidate existing sessions and session tokens after a user changes their password. An attacker who already holds an active session, for example via a stolen session token or a device left logged in, remains authenticated as the legitimate user even after the user rotates their credentials, undermining the security purpose of the password change.

Flowise contains a path traversal vulnerability in the /api/v1/document-store/loader/process endpoint that allows unauthenticated attackers to write arbitrary files to the filesystem. Attackers can exploit unsanitized fileName parameters with ../ sequences to overwrite critical files like package.json and achieve remote code execution when the application restarts.

Flowise before 3.0.6 (affected versions 2.2.8 and earlier) contains an arbitrary file access vulnerability due to missing validation that the chatflowId and chatId parameters are UUIDs or numbers in file handling operations. By supplying a path-traversal value (e.g., '../../../../../tmp') as the chatflow id, an unauthenticated attacker can use the /api/v1/chatflows endpoint (via addBase64FilesToStorage) to write arbitrary files, and the /api/v1/get-upload-file and /api/v1/openai-assistants-file/download endpoints (via streamStorageFile) to read arbitrary files. Arbitrary file write may lead to remote code execution.

Flowise contains an authentication bypass vulnerability in the unprotected /api/v1/account/register endpoint that allows unauthenticated attackers to create user accounts. Remote attackers can exploit this endpoint to register arbitrary accounts and authenticate to the system, gaining full API access without credentials.

Flowise before 3.0.6 contains an arbitrary file read vulnerability in the chatId parameter of the /api/v1/get-upload-file and /api/v1/openai-assistants-file/download endpoints. The chatId value is not validated and is passed to streamStorageFile(), where a fallback file-lookup path constructed without the orgId is evaluated after the storage-directory containment check, allowing path traversal beyond the intended storage directory. Unauthenticated attackers can read sensitive files such as /root/.flowise/database.sqlite, exposing all database content in the default configuration.

Flowise before 3.0.10 contains an unverified password change vulnerability. An authenticated user can change their account password through the account settings (Security) section without supplying the current password or any additional verification, as the application does not enforce a current-password check on the credential change. This can lead to full account takeover, particularly if an attacker can hijack or coerce an authenticated session.

Flowise before 3.0.13 uses bcrypt with default salt rounds of 5, providing only 32 iterations instead of the OWASP-recommended minimum of 10 rounds. Attackers can crack password hashes approximately 30 times faster with modern GPU hardware, potentially compromising all user accounts in a database breach scenario.

Flowise before 3.1.0 (versions 3.0.13 and earlier) contains a missing authentication vulnerability in the /api/v1/loginmethod endpoint that allows unauthenticated users to retrieve an organization's complete SSO configuration, including OAuth client secrets in cleartext, by providing an organizationId parameter. Remote attackers can send a GET request to harvest sensitive API credentials for Google, Microsoft/Azure, GitHub, and Auth0 integrations. This affects FlowiseAI Cloud and self-hosted instances where the endpoint is exposed.

Flowise before 3.1.0 (npm package flowise, versions 3.0.13 and earlier) uses a weak hardcoded default value 'Secre$t' for the TOKEN_HASH_SECRET environment variable in packages/server/src/enterprise/utils/tempTokenUtils.ts when the variable is not configured. This secret derives the AES-256-CBC key used to encrypt user IDs and workspace IDs in the 'meta' field of JWT tokens. An attacker who knows the default secret can decrypt this metadata to extract internal user and workspace identifiers, and re-encrypt manipulated values such as altered user or workspace IDs. Because the JWT signature is validated separately, decrypting or tampering with this metadata does not by itself grant access, but the disclosure of internal identifiers and possible metadata manipulation could aid privilege escalation or unauthorized data access.

Flowise through 2.2.7 contains a SQL injection vulnerability in the importChatflows API. Due to insufficient validation of the chatflow.id value, an authenticated user can supply a crafted JSON import file whose id field is concatenated unsanitized into a SQL IN clause, allowing arbitrary SQL to be executed, including blind and error-based extraction of data from the credential table.

Flowise before 3.1.2 contains multiple OS command injection vulnerabilities in the Custom MCP Server feature due to incomplete command-flag validation and a regex bypass in local file access restrictions. An attacker with a Flowise account of any role, or API access with view/update permissions for chatflows, can configure a malicious MCP server to bypass the validateCommandFlags blocklist (for example, 'docker build' is not blocked, and 'npx --yes' is not blocked while only '-y' is) and the validateArgsForLocalFileAccess checks, resulting in execution of arbitrary commands on the Flowise host.

Flowise before 3.1.0 contains a server-side request forgery vulnerability in the Execute Flow node that allows attackers to bypass security validation by providing intranet addresses through the base URL field. Attackers can initiate HTTP requests to internal network addresses, access cloud metadata, and enumerate internal services by exploiting the missing secureFetch verification in httpSecurity.ts.

Flowise before 3.0.10 (affected versions 3.0.7 and earlier) contains an unverified email change vulnerability. An authenticated user can change the account email address, used as a login identifier and password-recovery channel, via the account profile endpoint without confirming the change to the original email address or re-entering the current password. By changing the recovery email, an attacker can take over the account and abuse password reset mechanisms.

Flowise before 3.1.2 contains an information disclosure vulnerability in the /api/v1/chatflows/apikey/:apikey endpoint. When the keyonly query parameter is omitted (the default), the endpoint returns not only the chatflows bound to the supplied API key but also all chatflows across every workspace that have no API key assigned, because the underlying query lacks any workspace filter. An attacker with a valid API key for one workspace can therefore retrieve the full ChatFlow configuration (including flowData with system prompts and node configurations, chatbotConfig, apiConfig, and credential IDs) of unprotected chatflows belonging to other workspaces.

Flowise before 3.0.13 contains an information exposure vulnerability in the POST /api/v1/account/forgot-password endpoint that returns full user objects including PII to unauthenticated attackers. An attacker can enumerate valid email addresses and harvest sensitive user data including user IDs, names, account status, and timestamps by sending requests with known email addresses.

Flowise before 3.0.8 contains a cross-site scripting (XSS) vulnerability caused by insufficient input filtering in chat messages and custom agent functions. An attacker can inject malicious JavaScript by sending an iframe payload (e.g., <iframe src="javascript:alert(document.cookie)">) in a chat box, or by having a custom agent function return an XSS payload from an external website. The injected script executes in the victim's browser, enabling theft of cookies and session data.

Flowise before 3.1.2 contains a mass assignment vulnerability in the PUT /api/v1/user endpoint that allows authenticated users to directly modify the credential field without validation. Attackers can bypass password change verification and session invalidation by supplying a crafted password hash, establishing persistent account access after temporary session compromise.

Flowise before 2.1.4 allows configuration to be injected into the Chainflow during execution via the overrideConfig option, supported in both the frontend web integration and the backend Prediction API. Because this feature is enabled by default with no allow-list of permitted variables and relies on vm2 for sandboxing, an attacker can abuse it to achieve remote code execution and sandbox escape, denial of service by crashing the server, server-side request forgery, prompt injection, and server variable and data exfiltration. These issues are self-targeted and do not persist to other users.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, dataset create and update mass-assignment allows cross-workspace dataset takeover. This issue has been patched in version 3.1.2.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, DatasetRow create and update mass-assignment allows cross-workspace row takeover. This issue has been patched in version 3.1.2.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, evaluation create and update mass-assignment allows cross-workspace evaluation takeover. This issue has been patched in version 3.1.2.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, evaluator create and update mass-assignment allows cross-workspace evaluator takeover. This issue has been patched in version 3.1.2.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, a mass assignment vulnerability exists in the assistant update endpoint of FlowiseAI. The endpoint allows authenticated users to modify server-controlled properties such as workspaceId, createdDate, and updatedDate when updating an assistant resource. Due to missing server-side validation and authorization checks, an attacker can manipulate the workspaceId field and reassign assistants to arbitrary workspaces. This breaks tenant isolation in multi-workspace environments. This issue has been patched in version 3.1.2.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, CustomTemplate create and update mass-assignment allows cross-workspace template takeover. This issue has been patched in version 3.1.2.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, assistant create and update mass-assignment allows cross-workspace assistant takeover. This issue has been patched in version 3.1.2.

Flowise 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.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, when credentials are fetched with a credentialName filter parameter, the encryptedData field is not stripped from the response. The code properly omits encryptedData when no filter is used but fails to do so when a filter is used. This issue has been patched in version 3.1.2.

Flowise 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.

Flowise 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.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, a mass assignment vulnerability exists in the chatflow update endpoint of FlowiseAI. The endpoint allows clients to modify server-controlled properties such as deployed, isPublic, workspaceId, createdDate, and updatedDate when updating a chatflow object. Due to missing server-side validation and authorization checks, an authenticated user can manipulate internal attributes of a chatflow and reassign it to another workspace. This allows cross-workspace resource reassignment and unauthorized modification of deployment and visibility settings. This issue has been patched in version 3.1.2.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, a mass assignment vulnerability exists in the tool update endpoint of FlowiseAI. The endpoint allows authenticated users to modify server-controlled properties such as workspaceId, createdDate, and updatedDate when updating a tool resource. Due to missing server-side validation and authorization checks, an attacker can manipulate the workspaceId field and reassign tools to arbitrary workspaces. This breaks tenant isolation in multi-workspace environments. This issue has been patched in version 3.1.2.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to version 3.1.2, a mass assignment vulnerability exists in the variable update endpoint of FlowiseAI. The endpoint allows authenticated users to modify server-controlled properties such as workspaceId, createdDate, and updatedDate when updating a variable resource. Due to missing server-side validation and authorization checks, an attacker can manipulate the workspaceId field and reassign variables to arbitrary workspaces. This behavior may break tenant isolation in multi-workspace environments. This issue has been patched in version 3.1.2.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, multiple tool implementations directly import and invoke raw HTTP clients (node-fetch, axios) instead of using the secured wrapper. These tools include (1) OpenAPIToolkit/OpenAPIToolkit.ts, (2) WebScraperTool/WebScraperTool.ts, (3) MCP/core.ts, and (4) Arxiv/core.ts. 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 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.

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, 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, 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, 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, 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, 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, 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, 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.

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 3.1.0, 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.

Flowise 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.

Flowise 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.

Flowise 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.

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 through v3.0.4 is vulnerable to remote code execution via unsanitized evaluation of user input in the "Supabase RPC Filter" field.

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

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

Flowise 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.

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.

Flowise is a drag & drop user interface to build a customized large language model flow. In version 1.4.3 of Flowise, a reflected cross-site scripting vulnerability occurs in the `/api/v1/credentials/id` endpoint. If the default configuration is used (unauthenticated), an attacker may be able to craft a specially crafted URL that injects Javascript into the user sessions, allowing the attacker to steal information, create false popups, or even redirect the user to other websites without interaction. If the chatflow ID is not found, its value is reflected in the 404 page, which has type text/html. This allows an attacker to attach arbitrary scripts to the page, allowing an attacker to steal sensitive information. This XSS may be chained with the path injection to allow an attacker without direct 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, a reflected cross-site scripting vulnerability occurs in the `/api/v1/chatflows-streaming/id` endpoint. If the default configuration is used (unauthenticated), an attacker may be able to craft a specially crafted URL that injects Javascript into the user sessions, allowing the attacker to steal information, create false popups, or even redirect the user to other websites without interaction. If the chatflow ID is not found, its value is reflected in the 404 page, which has type text/html. This allows an attacker to attach arbitrary scripts to the page, allowing an attacker to steal sensitive information. This XSS may be chained with the path injection to allow an attacker without direct 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, a reflected cross-site scripting vulnerability occurs in the `/api/v1/public-chatflows/id` endpoint. If the default configuration is used (unauthenticated), an attacker may be able to craft a specially crafted URL that injects Javascript into the user sessions, allowing the attacker to steal information, create false popups, or even redirect the user to other websites without interaction. If the chatflow ID is not found, its value is reflected in the 404 page, which has type text/html. This allows an attacker to attach arbitrary scripts to the page, allowing an attacker to steal sensitive information. This XSS may be chained with the path injection to allow an attacker without direct 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.

Flowise is a drag & drop user interface to build a customized large language model flow. In version 1.4.3 of Flowise, a reflected cross-site scripting vulnerability occurs in the `api/v1/chatflows/id` endpoint. If the default configuration is used (unauthenticated), an attacker may be able to craft a specially crafted URL that injects Javascript into the user sessions, allowing the attacker to steal information, create false popups, or even redirect the user to other websites without interaction. If the chatflow ID is not found, its value is reflected in the 404 page, which has type text/html. This allows an attacker to attach arbitrary scripts to the page, allowing an attacker to steal sensitive information. This XSS may be chained with the path injection to allow an attacker without direct 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, 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.