| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| 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. |
| 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. |
| 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. |
| 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 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. |
| 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 = "${baseURL}/..."; . The only check on baseURL was isValidURL , but a valid-looking URL can still contain characters that break out of a code string. An authenticated user could craft a baseURL that passed this check, closed the surrounding string, and injected their own JavaScript into the sandboxed script (code injection, CWE-94). The vm2 sandbox runs in the same Node.js process as Flowise and exposes risky dependencies. As a result, the injected code could escape the sandbox and run arbitrary code on the Flowise server as the Flowise process user. Exploitation only requires an authenticated session. The issue is fixed in version 3.1.3, which passes the URL to the sandbox as data instead of inserting it into code and adds stricter URL validation. |
| Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, executeJavaScriptCode() accepted caller-provided nodeVMOptions and merged them over the default NodeVM security settings in packages/components/src/utils.ts. An authenticated attacker reaching packages/server/src/routes/node-custom-functions/index.ts could run a custom function that imported flowise-components/dist/src/utils.js, called executeJavaScriptCode() again with nodeVMOptions.require.builtin set to allow all built-in modules, and then required child_process to execute arbitrary system commands as root on the Flowise server. This issue is fixed in version 3.1.3. |
| Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the CSVAgent in packages/components/nodes/agents/CSVAgent/CSVAgent.ts extracted attacker-controlled CSV data with file.split(',').pop() and interpolated it directly into executable Python as base64_string = "${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. |
| 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. |
| 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. |
| 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 consumed by flow nodes. 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 file and trigger execution when Puppeteer launched Chromium and sourced /etc/chromium/*.conf. 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 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. |
| 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. |
| 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. |
| 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 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 & 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. |
