Initial commit: hardened DeerFlow factory

Vendored deer-flow upstream (bytedance/deer-flow) plus prompt-injection
hardening:

- New deerflow.security package: content_delimiter, html_cleaner,
  sanitizer (8 layers — invisible chars, control chars, symbols, NFC,
  PUA, tag chars, horizontal whitespace collapse with newline/tab
  preservation, length cap)
- New deerflow.community.searx package: web_search, web_fetch,
  image_search backed by a private SearX instance, every external
  string sanitized and wrapped in <<<EXTERNAL_UNTRUSTED_CONTENT>>>
  delimiters
- All native community web providers (ddg_search, tavily, exa,
  firecrawl, jina_ai, infoquest, image_search) replaced with hard-fail
  stubs that raise NativeWebToolDisabledError at import time, so a
  misconfigured tool.use path fails loud rather than silently falling
  back to unsanitized output
- Native client back-doors (jina_client.py, infoquest_client.py)
  stubbed too
- Native-tool tests quarantined under tests/_disabled_native/
  (collect_ignore_glob via local conftest.py)
- Sanitizer Layer 7 fix: only collapse horizontal whitespace, preserve
  newlines and tabs so list/table structure survives
- Hardened runtime config.yaml references only the searx-backed tools
- Factory overlay (backend/) kept in sync with deer-flow tree as a
  reference / source

See HARDENING.md for the full audit trail and verification steps.

deer-flow/backend/packages/harness/deerflow/reflection/__init__.py

@@ -0,0 +1,3 @@
+from .resolvers import resolve_class, resolve_variable
+
+__all__ = ["resolve_class", "resolve_variable"]

deer-flow/backend/packages/harness/deerflow/reflection/resolvers.py

@@ -0,0 +1,95 @@
+from importlib import import_module
+
+MODULE_TO_PACKAGE_HINTS = {
+    "langchain_google_genai": "langchain-google-genai",
+    "langchain_anthropic": "langchain-anthropic",
+    "langchain_openai": "langchain-openai",
+    "langchain_deepseek": "langchain-deepseek",
+}
+
+
+def _build_missing_dependency_hint(module_path: str, err: ImportError) -> str:
+    """Build an actionable hint when module import fails."""
+    module_root = module_path.split(".", 1)[0]
+    missing_module = getattr(err, "name", None) or module_root
+
+    # Prefer provider package hints for known integrations, even when the import
+    # error is triggered by a transitive dependency (e.g. `google`).
+    package_name = MODULE_TO_PACKAGE_HINTS.get(module_root)
+    if package_name is None:
+        package_name = MODULE_TO_PACKAGE_HINTS.get(missing_module, missing_module.replace("_", "-"))
+
+    return f"Missing dependency '{missing_module}'. Install it with `uv add {package_name}` (or `pip install {package_name}`), then restart DeerFlow."
+
+
+def resolve_variable[T](
+    variable_path: str,
+    expected_type: type[T] | tuple[type, ...] | None = None,
+) -> T:
+    """Resolve a variable from a path.
+
+    Args:
+        variable_path: The path to the variable (e.g. "parent_package_name.sub_package_name.module_name:variable_name").
+        expected_type: Optional type or tuple of types to validate the resolved variable against.
+            If provided, uses isinstance() to check if the variable is an instance of the expected type(s).
+
+    Returns:
+        The resolved variable.
+
+    Raises:
+        ImportError: If the module path is invalid or the attribute doesn't exist.
+        ValueError: If the resolved variable doesn't pass the validation checks.
+    """
+    try:
+        module_path, variable_name = variable_path.rsplit(":", 1)
+    except ValueError as err:
+        raise ImportError(f"{variable_path} doesn't look like a variable path. Example: parent_package_name.sub_package_name.module_name:variable_name") from err
+
+    try:
+        module = import_module(module_path)
+    except ImportError as err:
+        module_root = module_path.split(".", 1)[0]
+        err_name = getattr(err, "name", None)
+        if isinstance(err, ModuleNotFoundError) or err_name == module_root:
+            hint = _build_missing_dependency_hint(module_path, err)
+            raise ImportError(f"Could not import module {module_path}. {hint}") from err
+        # Preserve the original ImportError message for non-missing-module failures.
+        raise ImportError(f"Error importing module {module_path}: {err}") from err
+
+    try:
+        variable = getattr(module, variable_name)
+    except AttributeError as err:
+        raise ImportError(f"Module {module_path} does not define a {variable_name} attribute/class") from err
+
+    # Type validation
+    if expected_type is not None:
+        if not isinstance(variable, expected_type):
+            type_name = expected_type.__name__ if isinstance(expected_type, type) else " or ".join(t.__name__ for t in expected_type)
+            raise ValueError(f"{variable_path} is not an instance of {type_name}, got {type(variable).__name__}")
+
+    return variable
+
+
+def resolve_class[T](class_path: str, base_class: type[T] | None = None) -> type[T]:
+    """Resolve a class from a module path and class name.
+
+    Args:
+        class_path: The path to the class (e.g. "langchain_openai:ChatOpenAI").
+        base_class: The base class to check if the resolved class is a subclass of.
+
+    Returns:
+        The resolved class.
+
+    Raises:
+        ImportError: If the module path is invalid or the attribute doesn't exist.
+        ValueError: If the resolved object is not a class or not a subclass of base_class.
+    """
+    model_class = resolve_variable(class_path, expected_type=type)
+
+    if not isinstance(model_class, type):
+        raise ValueError(f"{class_path} is not a valid class")
+
+    if base_class is not None and not issubclass(model_class, base_class):
+        raise ValueError(f"{class_path} is not a subclass of {base_class.__name__}")
+
+    return model_class