Threat Intelligence Database

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the POST /api/v1/oauth2-credential/refresh/:credentialId endpoint is included in WHITELIST_URLS and requires no authentication. The endpoint decrypts the stored credential, sends a refresh request to the configured OAuth provider with the client secret and refresh token, and returns the refreshed access_token in the response body. An attacker with a credential ID can use the token to access the victim's connected service and can also exhaust refresh-token quota. This issue is fixed in 3.1.3.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, a prompt injection sent to a chatflow using a CSV Agent node can cause the LLM to respond with a malicious Python script that bypasses the blocklist validator and executes in an unsandboxed Pyodide environment. The specific flaw exists within the run method of the CSV_Agents class, where untrusted data is used to construct an LLM prompt and the resulting pythonCode is validated by validatePythonCodeForDataFrame before execution. An attacker can leverage this to execute arbitrary code in the context of the service account. This issue is fixed in 3.1.3.

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.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the PUT /api/v1/executions/:id endpoint in packages/server/src/routes/executions/index.ts lacks the checkAnyPermission() middleware that protects other execution endpoints. Any authenticated user, regardless of assigned permissions, can modify execution state, data, and metadata of any execution in their workspace, enabling privilege escalation and manipulation of workflow execution results. This issue is fixed in 3.1.3.

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.

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.

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.

Flowise is a drag-and-drop user interface for building customized large language model (LLM) flows. Prior to 3.1.3, Flowise injects $vars into the code execution sandbox without requiring variables:view, bypassing the permission-protected Variables API. Variables for the active workspace are fetched at packages/components/src/utils.ts and runtime variables are resolved from server environment variables, while the official variables route enforces variables:view. A user or API key that is denied variables:view can call /api/v1/node-custom-function and receive $vars pre-populated with all variables for the workspace, including Variable.name to Variable.value static variables and Variable.name to process.env[Variable.name] runtime variables. This can expose secrets such as database passwords, JWT secrets, SMTP passwords, and cloud keys, depending on the workspace Variables configuration. This issue is fixed in version 3.1.3.

Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, Flowise validatePythonCodeForDataFrame in packages/components/src/pythonCodeValidator.ts can be bypassed with Unicode homoglyph identifiers, allowing arbitrary Python execution inside Pyodide and full OS command execution on the Flowise host via Pyodide js module interop. The validator gates pyodide.runPythonAsync in packages/components/nodes/agents/CSVAgent/CSVAgent.ts and packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts with an ASCII word-boundary blacklist. JavaScript regex word boundaries are ASCII-only, while Python 3 NFKC-normalizes identifiers at parse time, so homoglyph forms such as __cl𝐚ss__, __subcl𝐚sses__, __b𝐚se__, and __b𝐮iltins__ bypass the blacklist and are parsed as their ASCII equivalents. This issue is fixed in version 3.1.3.

Prior to 3.1.3, Flowise CSVAgent interpolates an attacker-controlled segment of the csvFile data URI directly into a Python source-code template that is then executed by Pyodide. Because Pyodide is loaded with the default js bridge to globalThis, which on Node.js exposes eval and dynamic import, the attacker can break out of the Python string literal, hand a JavaScript string to js.eval, dynamically import Node built-in modules such as fs and child_process, and execute arbitrary file I/O or OS commands as the Flowise process. The two validator paths around this code, validatePythonCodeForDataFrame and validateCustomReadCSVFunction, are never applied to the bootstrap template. A workspace user with chatflows:create or agentflows/chatflows update permission can plant a CSV Agent node with a crafted csvFile; once the chatflow is exposed via POST /api/v1/prediction/:id, any unauthenticated request triggers host remote code execution. This issue is fixed in version 3.1.3.