### 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.
### 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.
Update langflow to 1.10.0 if you use the affected versions. Test the change in a non-production environment first.
Local check
hol-guard supply-chain scanLangflow: Unauthenticated Shareable Playground arbitrary local or S3 file read affects langflow (pip). Severity is medium. ### 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.
AI coding agents often install or upgrade packages automatically in pip. A medium vulnerability in a dependency can be pulled into a project through a normal install or update without a human reviewing the change, expanding the blast radius from a single package to every agent workspace that depends on it.
| Package | Affected range | Fixed version |
|---|---|---|
| langflowpip | <1.10.0 | 1.10.0 |
Fixed versions are reported by the source feed; confirm compatibility before updating.
Reported by GitHub Security Advisories (ghsa).
HOL Guard can help your team review package activity against supported protection paths.
Explore HOL GuardUpdate langflow to 1.10.0 if you use the affected versions. Test the change in a non-production environment first.
Local check
hol-guard supply-chain scanLangflow: Unauthenticated Shareable Playground arbitrary local or S3 file read affects langflow (pip). Severity is medium. ### 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.
AI coding agents often install or upgrade packages automatically in pip. A medium vulnerability in a dependency can be pulled into a project through a normal install or update without a human reviewing the change, expanding the blast radius from a single package to every agent workspace that depends on it.
| Package | Affected range | Fixed version |
|---|---|---|
| langflowpip | <1.10.0 | 1.10.0 |
Fixed versions are reported by the source feed; confirm compatibility before updating.
Reported by GitHub Security Advisories (ghsa).
HOL Guard can help your team review package activity against supported protection paths.
Explore HOL Guard