PatchFirst · Latest vulnerabilities
Known vulnerabilities affecting flowise 3.0.1: 93. Compare the fixes below with your installed release.
Vulnerabilities: 93
Flowise before 3.1.3 contains an incomplete credential redaction vulnerability in the GET /api/v1/credentials/:id endpoint that returns decrypted secrets in plaintext. Authenticated users with credentials:view permission can retrieve sensitive data including database connection URLs with embedded passwords, cloud service account JSON with private keys, and API keys by calling this endpoint.
Flowise before 3.1.4 fails to validate chatflow visibility in the unauthenticated text-to-speech endpoint, allowing attackers to abuse private chatflow TTS credentials. Unauthenticated attackers can generate unlimited text-to-speech audio using stored OpenAI or ElevenLabs API keys by providing a valid chatflow UUID, incurring costs on the chatflow owner's account.
Flowise versions before 3.1.3 contain an insecure direct object reference vulnerability in the GET /api/v1/organization/customer-default-source endpoint that allows authenticated attackers to access other customers' payment and profile data by manipulating the customerId parameter. Attackers can enumerate predictable customer IDs to retrieve sensitive information including email addresses, account balances, currency types, and billing configurations without authorization checks.
Flowise before 3.1.3 contains a regex-based Python code validator bypass in CSV and Airtable Agent nodes that allows unauthenticated attackers to inject malicious code via prompt injection. Attackers can exploit unblocked pandas functions like pd.read_json() to exfiltrate datasets, perform SSRF against internal services, or achieve code execution through the unauthenticated prediction API.
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_
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 fix
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. Thi
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 cred
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
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 Op
## Summary Flowise on current `main` allows an authenticated user with `documentStores:preview-process` permission to trigger the `S3 Directory` document loader with attacker-controlled S3 object keys. The loader joins each returned S3 key with a temporary directory using
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
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 N
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
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the mitigation for CVE-2025-8943 blocked -y and --yes flags on npx, but packages/components/nodes/tools/MCP/core.ts denied only PATH, LD_LIBRARY_PATH, DYLD_LIBRARY_PATH, and NODE_OPTIONS by exact environment-variable name. Because npm reads configuration from npm_config_* variables, setting npm_config_yes=true reproduced --yes behavior without using a blocked flag, causing npx to auto-install and execute the named package when a Custom MCP server launched. 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, `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.
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
Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the unauthenticated POST /api/v1/prediction/:id endpoint accepted an overrideConfig object and unconditionally spread it into internal flowConfig and flowData objects in packages/server/src/utils/buildChatflow.ts and packages/server/src/utils/index.ts without checking apiOverrideStatus. This allowed unauthenticated attackers to inject arbitrary properties into the flow execution context of any public chatflow, overwrite values such as chatId, sessionId, and chatHistory, and control values resolved through $flow.* template variables consume
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