feat(models): fail closed on denied provider runtime

src/lfx/src/lfx/base/models/unified_models/instantiation.py

@@ -90,33 +90,32 @@ def get_llm(
     overrides: dict[str, Any] | None = None,
     provider_policy: ModelProviderPolicySnapshot | None = None,
 ) -> Any:
-    # Resolve helpers via package namespace so tests patching
-    # lfx.base.models.unified_models.<name> keep working.
-    from lfx.base.models import unified_models as unified_models_module
-
     # Coerce provider-specific string params (Message/Data may leak through StrInput)
     ollama_base_url = _to_str(ollama_base_url)
     watsonx_url = _to_str(watsonx_url)
     watsonx_project_id = _to_str(watsonx_project_id)
 
-    # Check if model is already a BaseLanguageModel instance (from a connection)
-    try:
-        from langchain_core.language_models import BaseLanguageModel
-
-        if isinstance(model, BaseLanguageModel):
-            # Model is already instantiated, return it directly
-            return model
-    except ImportError:
-        pass
+    # List-shaped selections carry the provider identity needed for policy
+    # enforcement. Gate that common runtime path before importing even the
+    # LangChain base class, provider SDKs, or credential-resolution helpers.
+    if isinstance(model, list):
+        if not model:
+            msg = "A model selection is required"
+            raise ValueError(msg)
+        model = model[0]
+    else:
+        # Preserve the existing connection-object passthrough. Only this
+        # identity-free path needs the LangChain base-class import up front.
+        try:
+            from langchain_core.language_models import BaseLanguageModel
 
-    # Safely extract model configuration
-    if not model or not isinstance(model, list) or len(model) == 0:
+            if isinstance(model, BaseLanguageModel):
+                return model
+        except ImportError:
+            pass
         msg = "A model selection is required"
         raise ValueError(msg)
 
-    # Extract the first model (only one expected)
-    model = model[0]
-
     # Extract model configuration from metadata
     model_name = model.get("name")
     provider = model.get("provider")
@@ -129,17 +128,21 @@ def get_llm(
         )
         raise ValueError(msg)
     if provider_policy is None:
+        from lfx.base.models.provider_registry import get_registry_snapshot
         from lfx.services.model_provider_policy import ModelProviderPolicyPurpose, resolve_model_provider_policy
 
-        from .provider_queries import get_model_providers
-
         provider_policy = resolve_model_provider_policy(
             user_id=user_id,
-            providers=(*get_model_providers(), provider),
+            providers=(*get_registry_snapshot().provider_ids, provider),
             purpose=ModelProviderPolicyPurpose.USE,
         )
     provider_policy.require(provider)
 
+    # Resolve helpers through the package namespace only after policy passes so
+    # tests can patch lfx.base.models.unified_models.<name> and denied requests
+    # cannot trigger runtime integration imports.
+    from lfx.base.models import unified_models as unified_models_module
+
     # Policy is evaluated against the submitted identity, then all runtime
     # wiring for a known provider is resolved from its canonical registry
     # entry. Stored flow metadata is not authoritative for class or parameter
@@ -864,30 +867,30 @@ def get_embeddings(
     wrapper containing the primary instance for the selected model and an
     ``available_models`` map of enabled embedding models from every configured provider.
     """
-    # Resolve helpers via package namespace so tests patching
-    # lfx.base.models.unified_models.<name> keep working.
-    from lfx.base.models import unified_models as unified_models_module
-
     # Coerce provider-specific string params
     ollama_base_url = _to_str(ollama_base_url)
     watsonx_url = _to_str(watsonx_url)
     watsonx_project_id = _to_str(watsonx_project_id)
 
-    # Passthrough: already-instantiated Embeddings object from a connection
-    try:
-        from langchain_core.embeddings import Embeddings as BaseEmbeddings
-
-        if isinstance(model, BaseEmbeddings):
-            return model
-    except ImportError:
-        pass
+    # Gate list-shaped selections before importing a LangChain base class,
+    # provider SDK, or credential-resolution helper.
+    if isinstance(model, list):
+        if not model:
+            msg = "An embedding model selection is required"
+            raise ValueError(msg)
+        model_dict = model[0]
+    else:
+        # Preserve passthrough for already-instantiated connection objects.
+        try:
+            from langchain_core.embeddings import Embeddings as BaseEmbeddings
 
-    # Validate input
-    if not model or not isinstance(model, list) or len(model) == 0:
+            if isinstance(model, BaseEmbeddings):
+                return model
+        except ImportError:
+            pass
         msg = "An embedding model selection is required"
         raise ValueError(msg)
 
-    model_dict = model[0]
     model_name = model_dict.get("name")
     provider = model_dict.get("provider")
     metadata = model_dict.get("metadata", {})
@@ -896,17 +899,19 @@ def get_embeddings(
         msg = "The selected embedding model is missing a provider"
         raise ValueError(msg)
     if provider_policy is None:
+        from lfx.base.models.provider_registry import get_registry_snapshot
         from lfx.services.model_provider_policy import ModelProviderPolicyPurpose, resolve_model_provider_policy
 
-        from .provider_queries import get_model_providers
-
         provider_policy = resolve_model_provider_policy(
             user_id=user_id,
-            providers=(*get_model_providers(), provider),
+            providers=(*get_registry_snapshot().provider_ids, provider),
             purpose=ModelProviderPolicyPurpose.USE,
         )
     provider_policy.require(provider)
 
+    # Resolve helpers through the patchable package namespace only after the
+    # provider has been authorized for runtime use.
+    from lfx.base.models import unified_models as unified_models_module
     from lfx.base.models.provider_registry import provider_name_for_id, resolve_provider_id
 
     provider_id = resolve_provider_id(provider)

src/lfx/tests/unit/services/model_provider_policy/test_policy.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import builtins
 from dataclasses import FrozenInstanceError
 from unittest.mock import AsyncMock, patch
 
@@ -16,6 +17,13 @@
     set_current_model_provider_policy_context,
 )
 
+_DENIED_RUNTIME_CATALOG_CALLS: list[None] = []
+
+
+def _denied_runtime_catalog_loader():
+    _DENIED_RUNTIME_CATALOG_CALLS.append(None)
+    return [{"name": "blocked-model", "model_type": "llm"}]
+
 
 def _restricted_snapshot(*allowed: str) -> ModelProviderPolicySnapshot:
     return ModelProviderPolicySnapshot(
@@ -514,13 +522,27 @@ def test_context_attributes_are_deeply_immutable():
 
 def test_runtime_denies_provider_before_credential_resolution(monkeypatch):
     credential_lookup_called = False
+    class_lookup_called = False
+    runtime_imports = []
+    real_import = builtins.__import__
 
     def _credential_lookup(*_args, **_kwargs):
         nonlocal credential_lookup_called
         credential_lookup_called = True
         return "secret"
 
+    def _track_import(name, *args, **kwargs):
+        runtime_imports.append(name)
+        return real_import(name, *args, **kwargs)
+
+    def _class_lookup(*_args, **_kwargs):
+        nonlocal class_lookup_called
+        class_lookup_called = True
+        return object
+
     monkeypatch.setattr("lfx.base.models.unified_models.get_api_key_for_provider", _credential_lookup)
+    monkeypatch.setattr("lfx.base.models.unified_models.get_model_class", _class_lookup)
+    monkeypatch.setattr(builtins, "__import__", _track_import)
 
     with pytest.raises(ModelProviderPolicyError) as exc_info:
         get_llm(
@@ -531,17 +553,34 @@ def _credential_lookup(*_args, **_kwargs):
 
     assert exc_info.value.code == "policy_blocked"
     assert credential_lookup_called is False
+    assert class_lookup_called is False
+    assert "langchain_core.language_models" not in runtime_imports
+    assert not any(name.startswith("langchain_anthropic") for name in runtime_imports)
 
 
 def test_embedding_runtime_denies_provider_before_credential_resolution(monkeypatch):
     credential_lookup_called = False
+    class_lookup_called = False
+    runtime_imports = []
+    real_import = builtins.__import__
 
     def _credential_lookup(*_args, **_kwargs):
         nonlocal credential_lookup_called
         credential_lookup_called = True
         return "secret"
 
+    def _track_import(name, *args, **kwargs):
+        runtime_imports.append(name)
+        return real_import(name, *args, **kwargs)
+
+    def _class_lookup(*_args, **_kwargs):
+        nonlocal class_lookup_called
+        class_lookup_called = True
+        return object
+
     monkeypatch.setattr("lfx.base.models.unified_models.get_api_key_for_provider", _credential_lookup)
+    monkeypatch.setattr("lfx.base.models.unified_models.get_embedding_class", _class_lookup)
+    monkeypatch.setattr(builtins, "__import__", _track_import)
 
     with pytest.raises(ModelProviderPolicyError):
         get_embeddings(
@@ -551,6 +590,43 @@ def _credential_lookup(*_args, **_kwargs):
         )
 
     assert credential_lookup_called is False
+    assert class_lookup_called is False
+    assert "langchain_core.embeddings" not in runtime_imports
+    assert not any(name.startswith("langchain_anthropic") for name in runtime_imports)
+
+
+@pytest.mark.parametrize("instantiate", [get_llm, get_embeddings])
+def test_denied_extension_runtime_does_not_execute_catalog_loader(monkeypatch, instantiate):
+    from lfx.base.models.provider_registry import ProviderSpec, register_provider, unregister_provider
+
+    provider = "Denied Runtime Extension"
+    register_provider(
+        ProviderSpec(
+            name=provider,
+            provider_id="denied-runtime-extension",
+            metadata={
+                "icon": "Bot",
+                "variables": [],
+                "mapping": {"model_class": "ChatOpenAI", "model_param": "model"},
+            },
+            catalog_loader=f"{__name__}:_denied_runtime_catalog_loader",
+        )
+    )
+    service = ModelProviderPolicyService()
+    service.set_approved_provider_ids({"openai"})
+    monkeypatch.setattr("lfx.services.deps.get_model_provider_policy_service", lambda: service)
+    _DENIED_RUNTIME_CATALOG_CALLS.clear()
+
+    try:
+        with pytest.raises(ModelProviderPolicyError):
+            instantiate(
+                [{"name": "blocked-model", "provider": provider, "metadata": {}}],
+                user_id="user-1",
+            )
+    finally:
+        unregister_provider(provider)
+
+    assert _DENIED_RUNTIME_CATALOG_CALLS == []
 
 
 @pytest.mark.parametrize("runtime", [get_llm, get_embeddings], ids=["llm", "embeddings"])