Use correct dataset folder in dataset nodes

comfy_extras/nodes_dataset.py

@@ -42,6 +42,62 @@ def load_and_process_images(image_files, input_dir):
     return output_images
 
 
+def secure_subfolder_path(base_dir, folder_name):
+    """Resolve folder_name inside base_dir, rejecting anything that escapes it.
+
+    Blocks '..', absolute paths, drive letters and symlink escapes using the
+    same realpath containment check as the core file endpoints.
+    """
+    target = os.path.abspath(os.path.join(base_dir, folder_name))
+    if not folder_paths.is_within_directory(base_dir, target):
+        raise ValueError(f"Invalid folder name {folder_name!r}: resolves outside of {base_dir}")
+    return target
+
+
+def list_dataset_folders():
+    """Relative paths of dataset folders found under all dataset roots.
+
+    Any subfolder containing a metadata.json or *.safetensors shard counts as
+    a dataset; the walk doesn't descend into matched folders.
+    """
+    found = set()
+    for root in folder_paths.get_folder_paths("datasets"):
+        if not os.path.isdir(root):
+            continue
+        for dirpath, subdirs, filenames in os.walk(root, followlinks=True):
+            if dirpath != root and (
+                "metadata.json" in filenames
+                or any(f.endswith(".safetensors") for f in filenames)
+            ):
+                found.add(os.path.relpath(dirpath, root).replace(os.sep, "/"))
+                subdirs[:] = []
+    return sorted(found)
+
+
+def get_dataset_save_dir(folder_name):
+    """Resolve the folder to save a new dataset into, inside the default root.
+
+    The folder is not created here; callers makedirs after validation.
+    """
+    root = folder_paths.get_folder_paths("datasets")[0]
+    target = secure_subfolder_path(root, folder_name)
+    if os.path.realpath(target) == os.path.realpath(root):
+        raise ValueError("folder_name must name a subfolder of the datasets directory, e.g. 'my_dataset'.")
+    return target
+
+
+def get_dataset_dir(folder_name):
+    """Find an existing dataset folder by relative name across all dataset roots."""
+    roots = folder_paths.get_folder_paths("datasets")
+    for root in roots:
+        target = secure_subfolder_path(root, folder_name)
+        if os.path.realpath(target) == os.path.realpath(root):
+            raise ValueError("folder_name must name a subfolder of the datasets directory, e.g. 'my_dataset'.")
+        if os.path.isdir(target):
+            return target
+    raise ValueError(f"Dataset folder {folder_name!r} not found in: {', '.join(roots)}")
+
+
 class LoadImageDataSetFromFolderNode(io.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -252,7 +308,7 @@ class SaveImageDataSetToFolderNode(io.ComfyNode):
         filename_prefix = filename_prefix[0]
         mode = mode[0]
 
-        output_dir = os.path.join(folder_paths.get_output_directory(), folder_name)
+        output_dir = secure_subfolder_path(folder_paths.get_output_directory(), folder_name)
         saved_files = save_images_to_folder(images, output_dir, filename_prefix, mode=='overwrite')
 
         logging.info(f"Saved {len(saved_files)} images to {output_dir}.")
@@ -306,7 +362,7 @@ class SaveImageTextDataSetToFolderNode(io.ComfyNode):
         filename_prefix = filename_prefix[0]
         mode = mode[0]
 
-        output_dir = os.path.join(folder_paths.get_output_directory(), folder_name)
+        output_dir = secure_subfolder_path(folder_paths.get_output_directory(), folder_name)
         saved_files = save_images_to_folder(images, output_dir, filename_prefix, mode=='overwrite')
 
         # Save captions
@@ -1443,7 +1499,7 @@ class SaveTrainingDataset(io.ComfyNode):
                 io.String.Input(
                     "folder_name",
                     default="training_dataset",
-                    tooltip="Name of folder to save dataset (inside output directory).",
+                    tooltip="Name of folder to save the dataset into, inside the datasets directory. Subfolders like 'project/run1' are allowed.",
                 ),
                 io.Int.Input(
                     "shard_size",
@@ -1473,8 +1529,8 @@ class SaveTrainingDataset(io.ComfyNode):
                 f"Something went wrong in dataset preparation."
             )
 
-        # Create output directory
+        # Create output directory (inside the datasets root, traversal-safe)
-        output_dir = os.path.join(folder_paths.get_output_directory(), folder_name)
+        output_dir = get_dataset_save_dir(folder_name)
         os.makedirs(output_dir, exist_ok=True)
 
         # Prepare data pairs
@@ -1533,10 +1589,10 @@ class LoadTrainingDataset(io.ComfyNode):
             description="Load encoded training dataset (latents + conditioning) from disk for use in training.",
             is_experimental=True,
             inputs=[
-                io.String.Input(
+                io.Combo.Input(
                     "folder_name",
-                    default="training_dataset",
+                    options=list_dataset_folders(),
-                    tooltip="Name of folder containing the saved dataset (inside output directory).",
+                    tooltip="Saved dataset to load, from the datasets directory.",
                 ),
             ],
             outputs=[
@@ -1555,11 +1611,8 @@ class LoadTrainingDataset(io.ComfyNode):
 
     @classmethod
     def execute(cls, folder_name):
-        # Get dataset directory
+        # Get dataset directory (searched across all dataset roots, traversal-safe)
-        dataset_dir = os.path.join(folder_paths.get_output_directory(), folder_name)
+        dataset_dir = get_dataset_dir(folder_name)
-
-        if not os.path.exists(dataset_dir):
-            raise ValueError(f"Dataset directory not found: {dataset_dir}")
 
         # Find all shard files
         shard_files = sorted(