Eric Hare b8fe970493 fix(mcp): close path traversal + cross-user disclosure (PVR0754098) (#12818)
* fix(mcp): close path traversal + cross-user disclosure in MCP endpoint (PVR0754098)

Path-containment on the storage service was only enforced in save_file;
get_file/get_file_stream/delete_file/get_file_size all resolved user-supplied
names directly, letting an authenticated user read arbitrary files via the
MCP resources/read handler. resources/list and tools/list additionally
returned every user's flows regardless of ownership.

- storage/local.py: extract path-containment into shared _validated_path()
  and call it from every read/write/delete entry point (langflow + lfx).
- mcp_utils.handle_read_resource: reject filenames containing ../, /, \ at
  the handler layer; require a current user and verify flow ownership
  (or self-owned user bucket) before dispatching to storage.
- mcp_utils.handle_read_resource: accept optional project_id so project
  servers can't read resources outside the project's flows.
- mcp_projects: pass project_id into handle_read_resource.
- mcp_utils.handle_list_resources / handle_list_tools: scope flow queries
  to the authenticated user on the global server.

Regression tests cover traversal rejection on every read path, cross-user
flow access denial, project-scope enforcement, and unauthenticated list
queries returning empty.

* fix(mcp): drop user-bucket files from project-scoped resources/list

Project-scoped handle_list_resources still appended every UserFile owned
by the caller, so a project MCP client could enumerate user-level files
unrelated to the project. User files have no project association, so
skip them entirely when project_id is set.

Adds a regression test proving that project-scoped resources/list returns
only files from flows in the project.

(cherry picked from commit f0fd436fe9)
2026-04-23 17:49:52 -07:00
2026-04-21 16:18:16 -04:00
2025-03-20 00:05:55 +00:00
2026-04-14 16:44:45 -07:00
2024-06-04 09:26:13 -03:00
2026-04-13 23:23:37 +00:00

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Langflow is a powerful platform for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool that can be integrated into applications built on any framework or stack. Langflow comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools.

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