CVE-2026-48520

Ein entfernter, anonymer Angreifer kann eine Schwachstelle in Langflow ausnutzen, um Informationen offenzulegen.

### 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.

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.10.0, 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 This vulnerability is fixed in 1.10.0.