GHSA-rcjh-r59h-gq37

Summary

The "Shareable Playground" (or "Public Flows" in code) contains a potential arbitrary file-read vulnerability, depending on the exact flow configuration used.

By making a flow public, public execution of the flow is allowed. The execution request can contain a list of files that gets read by Langflow and fed into the LLM. The files path can be any path supported by the storage - it can be either a local file or S3 path if supported by the local configuration

Details

Shareable Playground feature works by enabling the execution of workflows by unauthenticated users, by accessing a link. Specifically, it enables the route /api/v1/build_public_tmp to execute any public flow, given a public flow ID. This request contains a files field that can contain a list of files. The files get read in LCModelComponent._get_chat_result in a call to to_lc_message. A detailed stacktrace:

...
  File "/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/build.py", line 466, in build_vertices
    vertex_build_response: VertexBuildResponse = await _build_vertex(vertex_id, graph, event_manager)
  File "/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/build.py", line 324, in _build_vertex
    vertex_build_result = await graph.build_vertex(
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/graph/base.py", line 1563, in build_vertex
    await vertex.build(
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py", line 770, in build
    await step(user_id=user_id, event_manager=event_manager, **kwargs)
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/events/observability/lifecycle_events.py", line 95, in wrapper
    result = await observed_method(self, *args, **kwargs)
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py", line 411, in _build
    await self._build_results(
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py", line 640, in _build_results
    result = await initialize.loading.get_instance_results(
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/interface/initialize/loading.py", line 76, in get_instance_results
    return await build_component(params=custom_params, custom_component=custom_component)
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/interface/initialize/loading.py", line 299, in build_component
    build_results, artifacts = await custom_component.build_results()
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py", line 1136, in build_results
    return await self._build_with_tracing()
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py", line 1118, in _build_with_tracing
    results, artifacts = await self._build_results()
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py", line 1163, in _build_results
    result = await self._get_output_result(output)
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/custom/custom_component/component.py", line 1238, in _get_output_result
    result = await method() if inspect.iscoroutinefunction(method) else await asyncio.to_thread(method)
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/base/models/model.py", line 88, in text_response
    result = await self.get_chat_result(
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/base/models/model.py", line 180, in get_chat_result
    return await self._get_chat_result(
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/base/models/model.py", line 232, in _get_chat_result
    messages.append(input_value.to_lc_message(self.name))
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/schema/message.py", line 184, in to_lc_message
    file_contents = self.get_file_content_dicts(model_name)
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/schema/message.py", line 256, in get_file_content_dicts
    content_dicts.append(create_image_content_dict(file, None, model_name))
  File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/utils/image.py", line 96, in create_image_content_dict
    ...

This triggers Langflow to feed the file into the LLM as an Image. Reading the files back depends on the specific LLM configuration.

PoC

Reproduction: 1. Create a new flow and add a Chat Input node to it 2. Share the flow ("Shareable Playground") 3. Access the public link with the browser developers tools open and execute the flow. 4. Find the /api/v1/build_public_tmp route and copy as cURL 5. Edit the files JSON field to point to any file.

Impact

Potential file read (local or S3) if shareable playground feature is used.

Ori Lahav Security Researcher @ Rubrik Inc.