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Flowiseai

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Products
2
CVEs
45
Across products
45
Status
Private

Products

2

Recent CVEs

45
CVESevRiskCVSSEPSSKEVPublishedDescription
CVE-2026-41274Cri0.649.80.00Apr 23, 2026Flowise 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.
CVE-2026-41276Cri0.649.80.00Apr 23, 2026Flowise 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.
CVE-2026-41268Cri0.649.80.01Apr 23, 2026Flowise 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.
CVE-2026-41265Cri0.649.80.00Apr 23, 2026Flowise 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.
CVE-2026-41264Cri0.649.80.00Apr 23, 2026Flowise 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.
CVE-2026-40933Cri0.649.90.00Apr 21, 2026Flowise 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.
CVE-2026-41277Hig0.578.80.00Apr 23, 2026Flowise 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.
CVE-2026-41138Hig0.578.80.01Apr 23, 2026Flowise 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.
CVE-2026-41137Hig0.578.80.00Apr 23, 2026Flowise 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.
CVE-2026-41271Hig0.548.30.00Apr 23, 2026Flowise 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.
CVE-2026-41273Hig0.538.20.00Apr 23, 2026Flowise 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.
CVE-2026-41267Hig0.538.10.00Apr 23, 2026Flowise 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.
CVE-2026-41279Hig0.497.50.00Apr 23, 2026Flowise 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.
CVE-2026-41278Hig0.497.50.00Apr 23, 2026Flowise 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.
CVE-2026-41275Hig0.497.50.00Apr 23, 2026Flowise 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.
CVE-2026-41266Hig0.497.50.00Apr 23, 2026Flowise 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.
CVE-2026-41272Hig0.467.10.00Apr 23, 2026Flowise 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.
CVE-2026-41270Hig0.467.10.00Apr 23, 2026Flowise 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.
CVE-2026-41269Hig0.467.10.00Apr 23, 2026Flowise 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.
CVE-2026-46441hig0.45——May 14, 2026### Summary 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. ### Details The endpoint responsible for updating assistants: **PUT /api/v1/assistants/{assistantId}** accepts a JSON request body containing assistant metadata. However, the server does not restrict which properties may be modified by the client. As a result, user-controlled request bodies can include additional fields that should normally be controlled only by the backend. Server-controlled fields that can be manipulated include: 1. workspaceId 2. createdDate 3. updatedDate These fields appear to be directly mapped to the underlying database entity without strict DTO whitelisting or authorization checks. For example, the following request body was accepted: ```json { "details": "", "credential": "11ca7fef-c9b1-4c87-aa54-e547aed8a249", "iconSrc": null, "type": "CUSTOM", "createdDate": "2026-03-06T17:31:04.000Z", "updatedDate": "2026-03-06T17:31:55.000Z", "workspaceId": "11111111-2222-3333-4444-555555555555" } ``` This indicates that internal, server-controlled properties can be modified by an authenticated user. ### PoC 1. Authenticate to the Flowise interface. 2. Capture the request used to update an assistant: ```http PUT /api/v1/assistants/<ASSISTANT_ID> Content-Type: application/json Modify the request body by injecting server-controlled fields: { "details": "", "credential": "11ca7fef-c9b1-4c87-aa54-e547aed8a249", "iconSrc": null, "type": "CUSTOM", "createdDate": "2026-03-06T17:31:04.000Z", "updatedDate": "2026-03-06T17:31:55.000Z", "workspaceId": "11111111-2222-3333-4444-555555555555" } ``` 3.Send the request. Observe that the response accepts and persists the attacker-controlled workspaceId and metadata fields. ### Impact This vulnerability allows authenticated users to manipulate internal attributes of assistant resources. Confirmed impacts include: - Cross-workspace reassignment of assistants (workspaceId) - Unauthorized modification of metadata (createdDate, updatedDate) In multi-tenant deployments, this may allow an attacker to move assistants between workspaces without authorization, breaking tenant isolation boundaries.