Summary
Langflow's built-in Python interpreter components — PythonREPLComponent (Python Interpreter) and the legacy PythonREPLToolComponent (Python REPL Tool) — executed arbitrary user- or model-supplied Python code inside flows without effective sandboxing. Because the code ran in-process with the privileges of the Langflow service, any authenticated user who could edit and run a flow could achieve remote code execution and, from there, escalate privileges to superuser (e.g. by opening a database session and flipping is_superuser) or compromise the host.
This issue is fixed as of 1.10.1, with additional hardening through 1.12.3. See Remediation below.
Affected
- Package:
langflow (PyPI), and the underlying lfx package that ships the component.
- Vulnerable versions:
< 1.10.1.
- Patched:
1.10.1 (core fix). Upgrade to >= 1.12.3 for the complete hardening series.
Details
The root cause is code injection (CWE-94/CWE-95): the component passed raw input to LangChain's PythonREPL, which is explicitly not a security sandbox.
Two distinct weaknesses existed before 1.10.1:
-
Unrestricted builtins (default deployments). get_globals() built the exec globals from the global_imports allow-list but never set __builtins__. CPython's exec() then auto-injected the full builtins module, leaving __import__, open, eval, exec and the whole import machinery reachable regardless of the allow-list — e.g. __import__("os").system(...) or __import__("subprocess").check_output([...]). This made the "only modules in Global Imports can be used" guarantee false, and it applied even with the default configuration (allow_custom_components=True).
-
No server-policy gate (locked-down deployments). Even a deployment hardened with allow_custom_components=False could still run interpreter code, because the components did not consult that policy before executing.
Both let an authenticated user run the reported PoC, which opens a DB session and sets is_superuser = True on their account, or writes to the filesystem / runs OS commands with the service's privileges.
PoC (as reported)
- Authenticate as a normal user.
- Create a flow with the
PythonREPLComponent.
- Execute Python that imports Langflow internals and elevates the account:
import asyncio
from sqlmodel import select
from langflow.services.database.models.user.model import User
from langflow.services.deps import session_scope
async def escalate():
async with session_scope() as session:
stmt = select(User).where(User.username == 'testuser')
user = (await session.exec(stmt)).first()
if user:
user.is_superuser = True
session.add(user)
await session.commit()
asyncio.run(escalate())
Impact
Any authenticated user could:
- Execute arbitrary Python / OS commands with the Langflow service's privileges (RCE).
- Escalate their own account to superuser via direct database access.
- Read/modify data and configuration, and potentially pivot to the underlying host.
Remediation
Upgrade to Langflow 1.10.1 or later (preferably >= 1.12.3). The interpreter components were hardened with layered, defense-in-depth controls, applied in run_python_repl() before any code is executed:
- Restricted builtins —
get_globals() injects a curated safe_builtins() mapping, removing __import__, eval, exec, compile, open, input, globals/locals/vars, getattr/setattr, etc. (#13397)
- AST validation —
validate_code_safety() rejects inline import/from ... import, dunder/escape-gadget attribute access (__class__, __subclasses__, __globals__, frame/traceback introspection) and format-string dunder traversal. (#13397)
- Server-policy gate —
ensure_code_execution_enabled() refuses to run when allow_custom_components=False or block_code_interpreter_components=True, and fails closed if the settings stack cannot be resolved. (#13700 — this advisory — and #14375)
- Allow-listed module proxies — imported modules are exposed via a proxy that blocks reaching
sys.modules["os"] through a module's transitive import graph. (#15198)
- Optional hardware isolation — configure
LANGFLOW_SANDBOX_BACKEND to run interpreter code in an isolated microVM instead of in-process. (#14400)
Upstream fix references: #13397, #13700 (carries this GHSA), #14375, #14400, #15198.
Hardening recommendations for operators
- Keep Langflow updated (>= 1.12.3).
- For locked-down deployments, set
LANGFLOW_ALLOW_CUSTOM_COMPONENTS=false (or LANGFLOW_BLOCK_CODE_INTERPRETER_COMPONENTS=true) to disable the interpreter entirely.
- For deployments that must run untrusted code, configure
LANGFLOW_SANDBOX_BACKEND for microVM isolation.
- Run the Langflow service as an unprivileged user with least-privilege database credentials.
References
Summary
Langflow's built-in Python interpreter components —
PythonREPLComponent(Python Interpreter) and the legacyPythonREPLToolComponent(Python REPL Tool) — executed arbitrary user- or model-supplied Python code inside flows without effective sandboxing. Because the code ran in-process with the privileges of the Langflow service, any authenticated user who could edit and run a flow could achieve remote code execution and, from there, escalate privileges to superuser (e.g. by opening a database session and flippingis_superuser) or compromise the host.This issue is fixed as of 1.10.1, with additional hardening through 1.12.3. See Remediation below.
Affected
langflow(PyPI), and the underlyinglfxpackage that ships the component.< 1.10.1.1.10.1(core fix). Upgrade to>= 1.12.3for the complete hardening series.Details
The root cause is code injection (CWE-94/CWE-95): the component passed raw input to LangChain's
PythonREPL, which is explicitly not a security sandbox.Two distinct weaknesses existed before 1.10.1:
Unrestricted builtins (default deployments).
get_globals()built theexecglobals from theglobal_importsallow-list but never set__builtins__. CPython'sexec()then auto-injected the fullbuiltinsmodule, leaving__import__,open,eval,execand the whole import machinery reachable regardless of the allow-list — e.g.__import__("os").system(...)or__import__("subprocess").check_output([...]). This made the "only modules in Global Imports can be used" guarantee false, and it applied even with the default configuration (allow_custom_components=True).No server-policy gate (locked-down deployments). Even a deployment hardened with
allow_custom_components=Falsecould still run interpreter code, because the components did not consult that policy before executing.Both let an authenticated user run the reported PoC, which opens a DB session and sets
is_superuser = Trueon their account, or writes to the filesystem / runs OS commands with the service's privileges.PoC (as reported)
PythonREPLComponent.Impact
Any authenticated user could:
Remediation
Upgrade to Langflow 1.10.1 or later (preferably >= 1.12.3). The interpreter components were hardened with layered, defense-in-depth controls, applied in
run_python_repl()before any code is executed:get_globals()injects a curatedsafe_builtins()mapping, removing__import__,eval,exec,compile,open,input,globals/locals/vars,getattr/setattr, etc. (#13397)validate_code_safety()rejects inlineimport/from ... import, dunder/escape-gadget attribute access (__class__,__subclasses__,__globals__, frame/traceback introspection) and format-string dunder traversal. (#13397)ensure_code_execution_enabled()refuses to run whenallow_custom_components=Falseorblock_code_interpreter_components=True, and fails closed if the settings stack cannot be resolved. (#13700 — this advisory — and #14375)sys.modules["os"]through a module's transitive import graph. (#15198)LANGFLOW_SANDBOX_BACKENDto run interpreter code in an isolated microVM instead of in-process. (#14400)Upstream fix references: #13397, #13700 (carries this GHSA), #14375, #14400, #15198.
Hardening recommendations for operators
LANGFLOW_ALLOW_CUSTOM_COMPONENTS=false(orLANGFLOW_BLOCK_CODE_INTERPRETER_COMPONENTS=true) to disable the interpreter entirely.LANGFLOW_SANDBOX_BACKENDfor microVM isolation.References