IBM Langflow OSS 1.0.0 through 1.10.0 could allow a remote attacker to inject arbitrary code on the system, due to the improper control of user input code.

IBM Langflow OSS 1.0.0 through 1.10.1 can allow an attacker to access another user's private vector documents by creating their own flow with matching Chroma persist_directory and collection_name values. The attacker receives exact victim content in their workflow output despite having no authorization to read the victim's flow. Additionally, the attacker can pollute the victim's collection by inserting their own documents into the shared namespace.

IBM Langflow OSS 1.0.0 through 1.10.1 contains an improper input validation vulnerability in the PythonREPL sandbox implementation.

IBM Langflow OSS 1.0.0 through 1.10.1 could allow a remote attacker to traverse directories on the system. An attacker could send a specially crafted URL request containing "dot dot " sequences ( /.. /) to view arbitrary files on the system.

IBM Langflow OSS 1.0.0 through 1.8.4 contains multiple broken access control vulnerabilities in its file handling API that allow unauthorized access to user files.The /api/v1/files/images/{flow_id}/{file_name} endpoint does not enforce authentication or authorization checks, allowing unauthenticated remote attackers to retrieve image files associated with any flow by specifying a valid flow_id and file_name.Additionally, the /api/v1/files/download/{flow_id}/{file_name} endpoint requires authentication but fails to properly validate ownership of the requested resource. As a result, an authenticated user can access files belonging to other users by supplying arbitrary identifiers, leading to an authorization bypass (IDOR).Successful exploitation may result in unauthorized disclosure of sensitive data, including files stored in private flows. This issue breaks tenant isolation in multi-user deployments.

IBM Langflow OSS 1.0.0 through 1.10.1 allows authenticated users to access and manipulate other users' build jobs through improper access control on log retrieval and unauthenticated build endpoints.

IBM Langflow OSS 1.0.0 through 1.10.1  are vulnerable to unauthenticated remote code execution via environment variable injection in the MCP (Model Context Protocol) stdio launcher. The vulnerability exists in src/lfx/src/lfx/base/mcp/util.py where the DANGEROUS_ENV_VARS blocklist fails to include SHELLOPTS , BASHOPTS , and PS4 environment variables.

IBM Langflow OSS 1.0.0 through 1.10.1 can allow an attacker to reuse another user's FAISS namespace to access owner-only vector content and influence later query results. This causes cross-user information disclosure and limited integrity impact through persistent poisoning of returned results.

IBM Langflow OSS 1.0.0 through 1.10.0 allows unauthenticated attackers to create unlimited user accounts on any Langflow instance; when NEW_USER_IS_ACTIVE=true (documented deployment option), newly created accounts are immediately active and can authenticate to reach RCE endpoints, bypassing the need for AUTO_LOGIN.

IBM Langflow OSS 1.0.0 through 1.10.0 allows unauthenticated attackers to chain /api/v1/auto_login (mints SUPERUSER tokens to any network caller) with /api/v1/validate/code (executes user code via exec()) to achieve full RCE on default Langflow deployments

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.0, Langflow is vulnerable to Path Traversal in the Knowledge Bases API (DELETE /api/v1/knowledge_bases). This occurs because user-supplied knowledge base names are concatenated directly into file paths without proper sanitization or boundary validation. An authenticated attacker can exploit this flaw to delete arbitrary directories anywhere on the server's filesystem, leading to data loss and potential service disruption. This vulnerability is fixed in 1.9.0.

IBM Langflow Desktop 1.0.0 through 1.8.4 Langflow allows an attacker to execute arbitrary commands with the privileges of the process running Langflow. This allows reading sensitive environment variables (API keys, DB credentials), modifying files, or launching further attacks on the internal network.

IBM Langflow OSS 1.0.0 through 1.8.4 could allow any user to supply a flow_id to read transaction logs and vertex build data belonging to other users, and to delete persisted vertex build data for another user's flow.

IBM Langflow Desktop <=1.8.4 Langflow could allow a remote attacker to traverse directories on the system. An attacker could send a specially crafted URL request containing "dot dot" sequences (/../) to view arbitrary files on the system.

IBM Langflow Desktop 1.0.0 through 1.8.4 Langflow could allow an unauthenticated user to view other users' images due to an indirect object reference through a user-controlled key.

IBM Langflow Desktop 1.2.0 through 1.8.4 Langflow could allow an authenticated attacker to traverse directories on the system. An attacker could send a specially crafted URL request containing "dot dot" sequences (/../) to write arbitrary files on the system.

IBM Langflow Desktop 1.6.0 through 1.8.4 Lanflow is vulnerable to stored cross-site scripting. This vulnerability allows an authenticated user to embed arbitrary JavaScript code in the Web UI thus altering the intended functionality potentially leading to credentials disclosure within a trusted session.

IBM Langflow Desktop 1.0.0 through 1.8.4 IBM Langflow is vulnerable to server-side request forgery (SSRF). This may allow an authenticated attacker to send unauthorized requests from the system, potentially leading to network enumeration or facilitating other attacks.

IBM Langflow Desktop 1.6.0 through 1.8.2 Langflow could allow an authenticated user to execute arbitrary code on the system, caused by an insecure default setting which permits the deserialization of untrusted data in the FAISS component.

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.5.1, the `_read_flow` helper in `src/backend/base/langflow/api/v1/flows.py` branched on the `AUTO_LOGIN` setting to decide whether to filter by `user_id`. When `AUTO_LOGIN` was `False` (i.e., authentication was enabled), neither branch enforced an ownership check — the query returned any flow matching the given UUID regardless of who owned it. This allowed any authenticated user to read any other user's flow, including embedded plaintext API keys; modify the logic of another user's AI agents, and/or delete flows belonging to other users. The vulnerability was introduced by the conditional logic that was meant to accommodate public/example flows (those with `user_id = NULL`) under auto-login mode, but inadvertently left the authenticated path without an ownership filter. The fix in version 1.5.1 removes the `AUTO_LOGIN` conditional entirely and unconditionally scopes the query to the requesting user.

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.9.0, the Agentic Assistant feature in Langflow executes LLM-generated Python code during its validation phase. Although this phase appears intended to validate generated component code, the implementation reaches dynamic execution sinks and instantiates the generated class server-side. In deployments where an attacker can access the Agentic Assistant feature and influence the model output, this can result in arbitrary server-side Python execution. Version 1.9.0 fixes the issue.

The '/api/v1/files/images/{flow_id}/{file_name}' endpoint serves SVG files with the 'image/svg+xml' content type without sanitizing their content. Since SVG files can contain embedded JavaScript, an attacker can upload a malicious SVG that executes arbitrary JavaScript when viewed by other users, leading to stored cross-site scripting (XSS). This allows stealing authentication tokens stored in cookies, including JWT access and refresh tokens.

The '/logs' and '/logs-stream' endpoints in the log router allow any authenticated user to read the full application log buffer. These endpoints only require basic authentication ('get_current_active_user') without any privilege checks (e.g., 'is_superuser').

The '/api/v1/files/images/{flow_id}/{file_name}' endpoint does not enforce any authentication or authorization checks, allowing any unauthenticated user to download images belonging to any flow by knowing (or guessing) the flow ID and file name.

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.7.1, in the download_profile_picture function of the /profile_pictures/{folder_name}/{file_name} endpoint, the folder_name and file_name parameters are not strictly filtered, which allows the secret_key to be read across directories. Version 1.7.1 contains a patch.