IBM Langflow OSS 1.0.0 through 1.10.3 contain an authentication bypass vulnerability in the Model Context Protocol (MCP) composer endpoint when mcp_composer_enabled=true (default) and projects are configured with auth_type=oauth .
IBM Langflow OSS 1.0.0 through 1.10.3 could allow a remote authenticated attacker to execute arbitrary commands due to improper validation of the command field in MCP server configurations.
IBM Langflow OSS 1.0.0 through 1.10.3 Langflow could allow an authenticated attacker to read, modify, or expose sensitive host files via Docker-based MCP servers due to incomplete filtering of dangerous Docker volume-mount and device-mapping arguments.
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 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 1.10.1 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 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 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.