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feat(app): better errors when scanning models with picklescan #7803

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Merged
merged 1 commit into from
Mar 18, 2025
Merged

feat(app): better errors when scanning models with picklescan #7803

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7 changes: 5 additions & 2 deletions invokeai/app/services/model_load/model_load_default.py
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Original file line number Diff line number Diff line change
Expand Up @@ -85,8 +85,11 @@ def load_model_from_path(

def torch_load_file(checkpoint: Path) -> AnyModel:
scan_result = scan_file_path(checkpoint)
if scan_result.infected_files != 0 or scan_result.scan_err:
raise Exception("The model at {checkpoint} is potentially infected by malware. Aborting load.")
if scan_result.infected_files != 0:
raise Exception(f"The model at {checkpoint} is potentially infected by malware. Aborting load.")
if scan_result.scan_err:
raise Exception(f"Error scanning model at {checkpoint} for malware. Aborting load.")

result = torch_load(checkpoint, map_location="cpu")
return result

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6 changes: 4 additions & 2 deletions invokeai/backend/model_manager/legacy_probe.py
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Expand Up @@ -484,8 +484,10 @@ def _scan_model(cls, model_name: str, checkpoint: Path) -> None:
"""
# scan model
scan_result = scan_file_path(checkpoint)
if scan_result.infected_files != 0 or scan_result.scan_err:
raise Exception("The model {model_name} is potentially infected by malware. Aborting import.")
if scan_result.infected_files != 0:
raise Exception(f"The model {model_name} is potentially infected by malware. Aborting import.")
if scan_result.scan_err:
raise Exception(f"Error scanning model {model_name} for malware. Aborting import.")


# Probing utilities
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7 changes: 5 additions & 2 deletions invokeai/backend/model_manager/util/model_util.py
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Expand Up @@ -58,8 +58,11 @@ def read_checkpoint_meta(path: Union[str, Path], scan: bool = True) -> Dict[str,
else:
if scan:
scan_result = scan_file_path(path)
if scan_result.infected_files != 0 or scan_result.scan_err:
raise Exception(f'The model file "{path}" is potentially infected by malware. Aborting import.')
if scan_result.infected_files != 0:
raise Exception(f"The model at {path} is potentially infected by malware. Aborting import.")
if scan_result.scan_err:
raise Exception(f"Error scanning model at {path} for malware. Aborting import.")

checkpoint = torch.load(path, map_location=torch.device("meta"))
return checkpoint

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