Vendor: langflow
IBM Langflow OSS 1.0.0 through 1.9.1 could allow an authenticated user to read or modify sensitive information by bypassing authentication using insecure direct object references.
IBM Langflow OSS 1.0.0 through 1.9.0 could allow a denial of service due to uncontrolled resource consumption.
IBM Langflow OSS 1.0.0 through 1.9.1 could allow remote code execution due to improper validation of symbolic links during archive extraction.
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 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 1.6.0 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').