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FlowiseAI Flowise

Flowise through 3.1.4 exposes GET /api/v1/upsert-history/:id and PATCH /api/v1/upsert-history without route-level permission checks, and the backing service performs no workspace or ownership validation. getAllUpsertHistory() returns UpsertHistory rows selected solely by an attacker-supplied chatflowid, and patchDeleteUpsertHistory() deletes rows by an attacker-supplied array of record UUIDs. As a result, any authenticated low-privilege user or valid API key can read or delete document-store upsert history belonging to other users and other workspaces whenever the target chatflowId (which is exposed publicly in /chatbot/<chatflowId> share links) or row ids are known. The retrievable flowData and result fields contain embedding, record-manager and vector-store node configuration, including per-node paramValues. No patched version is available.

FlowiseAI Flowise

Flowise through 3.1.4 does not enforce authorization on the BullMQ admin dashboard. When the server runs in queue mode with the dashboard enabled and not in cloud mode (MODE=queue, ENABLE_BULLMQ_DASHBOARD=true, and !isCloud()), the /admin/queues mount is protected only by the verifyTokenForBullMQDashboard middleware, which validates the JWT but performs no role, permission, or workspace/organization scoping check; the mount also lies outside /api/v1/* so the global API gate does not apply. As a result, any authenticated user — including the lowest-privileged member of any tenant — can reach the full Bull-Board UI and view all queues and job payloads across the entire instance, including chat inputs and overrideConfig (which may carry credentials and prompts), chatflow.flowData graph definitions with custom function source code, credential IDs and system prompts, chatIds, files, and the originating orgId/workspaceId. The dashboard's write actions (retry, remove, promote, clean) are likewise usable across tenants. No patched version is available as of the advisory.

FlowiseAI Flowise

Flowise through 3.1.4 resolves SSO and local-password users solely by email without storing provider or subject identifier bindings, allowing attackers to authenticate as any existing user by claiming their email at any configured SSO provider. Attackers can gain complete account access including chatflows, credentials, and API keys by authenticating through a different SSO provider or local password than the victim's original registration method.

FlowiseAI Flowise

Flowise through 3.1.4 (Enterprise/platform mode with SSO enabled) contains an authentication bypass in the SSO login path. When an SSO callback arrives with an email matching a user whose status is INVITED, verifyAndLogin (SSOBase.ts:80-94) copies the user record from the database — including the server-stored single-use invitation tempToken — into the data passed to AccountService.register(). The register handler's token lookup, email match, and expiry checks therefore pass trivially against the server's own token instead of a caller-supplied one, and the account and its organization membership are flipped to ACTIVE. As a result, anyone able to authenticate at any configured SSO provider using a pending invitee's email address as the email claim can take over that invitation and obtain the invited user's access to the organization without ever possessing the emailed invitation token, for as long as the invitation is valid (24 hours by default). At the time of the advisory no patched version was available.

FlowiseAI Flowise

Flowise through 3.1.4 contains missing route-level RBAC checks on chat message endpoints that allow low-privileged API keys to read and delete chat history. Attackers with valid but low-privileged API keys can access GET and DELETE chat message routes without required flow permissions to read chat histories, prompts, model responses, and delete messages.

FlowiseAI Flowise

Flowise versions before 3.1.4 contain a server-side request forgery vulnerability in Cheerio, Playwright, and Puppeteer document loader nodes that bypass SSRF protection. Attackers can provide arbitrary URLs to fetch cloud metadata, internal services, and private network resources with response content returned as document text.

FlowiseAI Flowise

Flowise before 3.1.4 fails to sanitize the overrideConfig.sessionId parameter before using it in MongoDB queries within the MongoDBMemory node. Unauthenticated attackers can submit MongoDB operator objects through the prediction API to read chat history records belonging to other users from the shared collection.

FlowiseAI Flowise

Flowise before 3.1.4 fails to validate baseURL parameters in chat-model nodes, allowing authenticated users to redirect requests to arbitrary hosts. Attackers with chatflows:create or chatflows:update permissions can exfiltrate LLM provider API keys by redirecting requests to cloud metadata services or internal hosts.

FlowiseAI Flowise

Flowise versions before 3.1.4 fail to validate file paths in the SQL Database Chain node when connecting to SQLite databases, allowing authenticated attackers to write arbitrary files. Attackers can write malicious SQLite databases to system directories or inject files into the web root to execute commands or perform stored XSS attacks.

FlowiseAI Flowise

Flowise before 3.1.4 fails to enforce workspace-level authorization checks in openai-realtime endpoints, allowing authenticated users to access tools from ChatFlows in other workspaces by supplying an unscoped chatflowid. Attackers can invoke GET and POST requests to retrieve tool definitions and execute tools from victim workspaces, triggering external side effects and accessing sensitive tool outputs.

FlowiseAI Flowise

Flowise before 3.1.4 contains a validation bypass vulnerability in MCP server configuration allowing authenticated attackers remote code execution through an unvalidated cwd parameter. Attackers can bypass path validation using clean filenames in the args array while controlling the working directory to execute malicious code.

FlowiseAI Flowise

Flowise before 3.1.4 contains a remote code execution vulnerability in the Custom MCP node that allows authenticated attackers to execute arbitrary code by supplying npx package names in the mcpServerConfig parameter. Attackers can invoke npx with attacker-controlled npm packages to execute code on the Flowise server.

FlowiseAI Flowise

Flowise before 3.1.4 fails to scope enterprise organization and workspace membership APIs to the caller's tenant, allowing authenticated users to supply arbitrary organization IDs. Attackers can add themselves as organization owners, create workspaces, and gain administrative access to victim organizations by exploiting insufficient tenant isolation in the organizationuser and workspace endpoints.

FlowiseAI Flowise

Flowise versions before 3.1.4 contain cross-tenant authorization gaps in Enterprise endpoints that fail to verify resource ownership before operations. Attackers with Enterprise access can delete arbitrary workspaces, invite themselves into other organizations, modify cross-org roles, and abuse stored SSO secrets.

FlowiseAI Flowise

Flowise versions before 3.1.4 contain an unauthenticated denial of service vulnerability in the /api/v1/text-to-speech/abort endpoint that accepts user-supplied chatflowId and chatId without ownership verification. Attackers can terminate active chatflow predictions for any user by submitting requests with known chatflow and chat identifiers, causing targeted service disruption.

FlowiseAI Flowise

Flowise versions before 3.1.3 contain a remote code execution vulnerability in the Custom MCP node when CUSTOM_MCP_PROTOCOL is set to stdio, allowing authenticated users to execute arbitrary commands by manipulating environment variables and command arguments. Attackers can abuse PYTHONWARNINGS and BROWSER environment variables with python3, or leverage the root working directory with node to bypass validation and execute system commands.

FlowiseAI Flowise

Flowise before 3.1.3 contains a code injection vulnerability in the CSV Agent node's customReadCSV parameter that allows authenticated attackers to execute arbitrary Python code. The validator uses a static regex blocklist that can be bypassed through obfuscation techniques, enabling attackers to execute code in the unsandboxed pyodide environment with full system access.

FlowiseAI Flowise

Flowise before 3.1.3 contains a code injection vulnerability in the Airtable Agent node that allows unauthenticated attackers to execute arbitrary Python code by bypassing the pythonCodeValidator blocklist through obfuscation techniques. Attackers can send crafted prompts to a chatflow using the Airtable Agent node to inject malicious Python code that executes in an unsandboxed pyodide environment with full access to the host operating system.

FlowiseAI Flowise

Flowise before 3.1.3 contains a sandbox escape vulnerability in pythonCodeValidator.ts that fails to block native Pandas DataFrame methods like to_csv, to_json, pipe, and query. Authenticated attackers can exploit this to exfiltrate uploaded CSV data or write arbitrary files to the server filesystem.

FlowiseAI Flowise

Flowise (packages flowise and flowise-components) in versions <= 3.1.2 contain a sandbox escape in the vm2/@flowiseai/nodevm JavaScript sandbox. An authenticated user with access to the /api/v1/node-custom-function endpoint can escape the sandbox by supplying attacker-controlled executablePath and args parameters to puppeteer.launch(), which internally invokes child_process.spawn() outside the sandbox boundary. This allows execution of arbitrary OS commands as the Flowise process user (root in the official Docker image) and arbitrary host file disclosure via Chromium's file:// URL handling. In versions 3.0.8–3.1.2 exploitation requires ALLOW_BUILTIN_DEP=true; earlier versions are exploitable by default. Fixed in 3.1.3.

FlowiseAI Flowise

Flowise versions 2.2.4 through 3.1.4 contain a missing authorization vulnerability in the POST /api/v1/openai-assistants-file/download endpoint that allows unauthenticated attackers to access private files by exploiting the endpoint's inclusion in the global authentication whitelist, which bypasses all session and API key verification. Attackers can supply valid chatflowId, chatId, and fileName identifiers to retrieve files from any chatflow on the instance, including private chatflows belonging to other workspaces or organizations.

FlowiseAI Flowise

Flowise through 3.1.4 contains a server-side request forgery vulnerability in the SSRF guard implemented in httpSecurity.ts, where the DEFAULT_DENY_LIST omits the Oracle Cloud Infrastructure metadata endpoint 192.0.0.192 and the Alibaba Cloud metadata endpoint 100.100.100.200, allowing authenticated attackers to force the server to issue arbitrary GET requests to cloud instance metadata services. Attackers can send requests to the fetch-links API endpoint with a crafted URL parameter, bypassing deny-list validation including redirect-based bypasses, to reach instance metadata services and expose instance identity data and role credentials on Oracle Cloud Infrastructure or Alibaba Cloud deployments, with unauthenticated access possible when URL-fetching nodes exist in public chatflows.

FlowiseAI Flowise

Flowise through 3.1.4 contains an authentication bypass vulnerability that allows unauthenticated attackers to access the OAuth2 credential refresh endpoint by exploiting prefix-based whitelist matching in the authentication middleware defined in packages/server/src/utils/constants.ts. Attackers can send a POST request to the oauth2-credential refresh route with a trailing credential identifier to bypass all authentication and authorization checks, triggering unauthorized OAuth token rotation against credentials belonging to any workspace and potentially disrupting dependent OAuth integrations. This is a bypass of CVE-2026-41273.

FlowiseAI Flowise

Flowise through 3.1.4 contains a missing authorization vulnerability that allows authenticated workspace members to perform unauthorized document store operations by accessing unprotected mutation endpoints. Attackers holding only view-level permissions can send direct HTTP requests to the upsert and refresh document store routes to trigger document ingestion, refresh vector database contents, consume embedding API credits, and modify knowledge bases used by downstream chatflows.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, several organization billing endpoints in packages/server/src/enterprise/routes/organization.route.ts and packages/server/src/enterprise/controllers/organization.controller.ts accept attacker-controlled Stripe subscriptionId values without verifying that the identifier belongs to the authenticated user's organization. An authenticated attacker can perform unauthorized Stripe subscription operations on other tenants, including changing subscription plans or modifying seat quantities, resulting in financial impact and service disruption. This issue is fixed in 3.1.3.

FlowiseAI Flowise

Flowise is a drag-and-drop user interface for building customized large language model (LLM) flows. Prior to 3.1.3, Flowise has three OAuth2 credential endpoints that look up credentials by id alone with no workspaceId filter. The authorize, callback, and refresh handlers query the Credential table by id only; callback and refresh are whitelisted from authentication. This allows any authenticated user to initiate OAuth2 flows against credentials belonging to other workspaces, allows an unauthenticated attacker to forge OAuth2 callbacks to overwrite tokens in any credential, and allows an unauthenticated attacker to refresh tokens for any credential. The affected routes include /api/v1/oauth2-credential/authorize/<VICTIM_CREDENTIAL_UUID>, /api/v1/oauth2-credential/callback?code=ATTACKER_AUTH_CODE&state=<VICTIM_CREDENTIAL_UUID>, and /api/v1/oauth2-credential/refresh/<VICTIM_CREDENTIAL_UUID>. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag-and-drop user interface for building customized large language model (LLM) flows. Prior to 3.1.3, Flowise GET /api/v1/upsert-history returns the entire server-wide upsert history instead of being scoped to the requesting user, tenant, or workspace. The response can exceed 100MB and includes sensitive configuration data, including Vector Store settings such as Qdrant Server URL and collection name. The observed behavior indicates missing or insufficient authorization checks, workspace/project/tenant isolation, and pagination or limits, exposing integration parameters and infrastructure details that may enable further targeted attacks. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, Flowise openai-assistants-vector-store endpoints accept a client-controlled credential parameter and load credentials by id without checking whether that credential belongs to the caller workspace. Route permissions assistants:* only check feature access. The controller passes req.query.credential straight to the service, and the service uses findOneBy({ id: credentialId }), decrypts the credential, and calls OpenAI APIs without a workspaceId check. If an attacker knows another workspace credentialId, the attacker can use that workspace OpenAI key, read, modify, or delete victim vector stores and files, cause billing impact on the victim OpenAI account, and violate multi-tenant boundaries. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, `DELETE /api/v1/chatflows/:id` authorized requests with checkAnyPermission('chatflows:delete,agentflows:delete'), so possession of either permission was sufficient to reach the delete path. The delete logic then resolved the target record only by id and workspaceId and did not validate the target resource type, allowing a caller with only agentflows:delete to delete a CHATFLOW and a caller with only chatflows:delete to delete an AGENTFLOW in the same workspace. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the SQLite Record Manager node in packages/components/nodes/recordmanager/SQLiteRecordManager/SQLiteRecordManager.ts accepted user-controlled additionalConfig and spread it after the intended database setting, allowing additionalConfig.database to overwrite the SQLite database path. An authenticated attacker using the published Docker image, which ran as root, could write a SQLite database to paths such as /etc/chromium/exploit.conf; by controlling the table name and namespace value, the attacker could place shell syntax into the database file and trigger execution when Puppeteer launched Chromium and sourced /etc/chromium/*.conf. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, Flowise's HTTP security module httpSecurity.ts did not normalize IPv4-mapped IPv6 addresses such as ::ffff:127.0.0.1 and ::ffff:169.254.169.254 before checking them against the deny list. Because ipaddr.js reports these addresses as ipv6 while IPv4 CIDR deny-list entries are ipv4, isDeniedIP() skipped the IPv4 CIDR checks. An attacker who controls DNS resolution for a hostname used by the HTTP Node, API Chain, Document Loader, MCP tool, or other paths using secureAxiosRequest(), secureFetch(), or checkDenyList() could return a AAAA record for an IPv4-mapped target and cause requests to reach localhost, internal services, or cloud metadata endpoints. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the CSVAgent node allowed users to provide Python code that is executed through pyodide; although a denylist blocked dangerous Python constructs, pandas.read_pickle() could deserialize a pickled payload and achieve code execution without matching the denied words. The affected file is flowise-components/nodes/agents/CSVAgent/CSVAgent.ts, where user-supplied customReadCSVFunc is evaluated as pd.${customReadCSVFunc}. An authenticated user who can create or modify a chatflow can add a CSV Agent, place a malicious read_pickle payload in the Additional Parameters, save the chatflow, and trigger /api/v1/prediction/<UUID> to execute commands. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the CSVAgent in packages/components/nodes/agents/CSVAgent/CSVAgent.ts extracted attacker-controlled CSV data with file.split(',').pop() and interpolated it directly into executable Python as base64_string = "${base64String}" before calling Pyodide. The validatePythonCodeForDataFrame() denylist only checked later LLM-generated code and did not validate this initial code block. An authenticated attacker could inject a closing quote followed by Python code, use Pyodide's js bridge to load Node.js child_process, and execute arbitrary operating system commands as root in the Flowise container. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, executeJavaScriptCode() accepted caller-provided nodeVMOptions and merged them over the default NodeVM security settings in packages/components/src/utils.ts. An authenticated attacker reaching packages/server/src/routes/node-custom-functions/index.ts could run a custom function that imported flowise-components/dist/src/utils.js, called executeJavaScriptCode() again with nodeVMOptions.require.builtin set to allow all built-in modules, and then required child_process to execute arbitrary system commands as root on the Flowise server. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag-and-drop user interface for building customized large language model (LLM) flows. Prior to version 3.1.3, several custom-tool components — AgentAsTool, ChatflowTool, and ExecuteFlow — ran code in the in-process  vm2  sandbox. To build that code, they inserted a user-controlled  baseURL  value straight into the JavaScript source, for example  const url = "${baseURL}/..."; . The only check on  baseURL  was  isValidURL , but a valid-looking URL can still contain characters that break out of a code string. An authenticated user could craft a  baseURL  that passed this check, closed the surrounding string, and injected their own JavaScript into the sandboxed script (code injection, CWE-94). The  vm2  sandbox runs in the same Node.js process as Flowise and exposes risky dependencies. As a result, the injected code could escape the sandbox and run arbitrary code on the Flowise server as the Flowise process user. Exploitation only requires an authenticated session. The issue is fixed in version 3.1.3, which passes the URL to the sandbox as data instead of inserting it into code and adds stricter URL validation.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the /api/v1/files route was protected only by the feat:files feature gate and did not enforce checkPermission on GET or DELETE. A low-privileged authenticated API key with unrelated permissions could call GET /api/v1/files to list files under the organization storage root and DELETE /api/v1/files?path=... to delete files belonging to other workspaces in the same organization because getAllFiles and deleteFile used activeOrganizationId and a user-controlled path without restricting access by permissions or activeWorkspaceId. This issue is fixed in version 3.1.3.

FlowiseAI Flowise · FlowiseAI flowise-components

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, Flowise record manager and agent memory nodes allowed users to set arbitrary TypeORM DataSource options through the additionalConfig input in packages/components/nodes/recordmanager/MySQLRecordManager/MySQLrecordManager.ts, packages/components/nodes/recordmanager/PostgresRecordManager/PostgresRecordManager.ts, packages/components/nodes/recordmanager/SQLiteRecordManager/SQLiteRecordManager.ts, packages/components/nodes/memory/AgentMemory/MySQLAgentMemory/MySQLAgentMemory.ts, and packages/components/nodes/memory/AgentMemory/AgentMemory.ts. TypeORM DataSource options such as entities, subscribers, and migrations can load local JavaScript files, allowing an authenticated user to execute arbitrary code on the server by uploading a JavaScript payload and referencing it from additionalConfig.entities. This issue is fixed in version 3.1.3.

FlowiseAI Flowise

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the OAuth2 token refresh endpoint POST /api/v1/oauth2-credential/refresh/:credentialId is unauthenticated by design and performs a server-side HTTP request to the credential-controlled accessTokenUrl without SSRF protections. Runtime validation confirmed that the endpoint was reachable without authentication, triggered outbound POST requests to an attacker-controlled server, reflected the full remote response body to the caller through tokenInfo, and sent client_id, client_secret, grant_type=refresh_token, and refresh_token in the request body. This issue is fixed in version 3.1.3.

Flowise · Flowiseai flowise

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 · Flowiseai flowise

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 · Flowiseai flowise

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 · Flowiseai flowise

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 · Flowiseai flowise

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 · Flowiseai flowise

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 · Flowiseai flowise

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 · Flowiseai flowise

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.

FlowiseAI Flowise

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.

FlowiseAI Flowise

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.

FlowiseAI Flowise

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.

FlowiseAI Flowise

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.

FlowiseAI Flowise

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.

FlowiseAI Flowise

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.

FlowiseAI Flowise

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.

FlowiseAI Flowise

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.