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a/pyproject.toml b/pyproject.toml index 8b8ab3e2..70a6d966 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -30,8 +30,9 @@ bandit = { version = "1.7.5", extras = ["toml"] } mypy = "^1.4.1" aiohttp = "^3.8.5" dill = "^0.3.7" -pandas = "^2.0.3" requests = "^2.31.0" +torch = "^1.14.0" +transformers = "^4.31.0" [tool.poetry.group.dev.dependencies] dunamai = "^1.18.0" diff --git a/tests/test_modelscan.py b/tests/test_modelscan.py index d6395226..91aae496 100644 --- a/tests/test_modelscan.py +++ b/tests/test_modelscan.py @@ -14,7 +14,9 @@ import tensorflow as tf from tensorflow import keras from typing import Any, List, Set -from test_utils import generate_dill_unsafe_file +from test_utils import generate_dill_unsafe_file, PickleInject, get_pickle_payload +import torch +from transformers import GPT2LMHeadModel import zipfile from modelscan.modelscan import Modelscan @@ -208,6 +210,33 @@ def keras_file_path(tmp_path_factory: Any) -> Any: return tmp +# @pytest.fixture(scope="session") +# def pytorch_file_path(tmp_path_factory: Any) -> Any: +# tmp = tmp_path_factory.mktemp("pytorch") + +# # Load a PyTorch model from huggingface and import relevant libaries +# name_of_model_repo_on_huggingface = "gpt2" + +# safe_model = GPT2LMHeadModel.from_pretrained(name_of_model_repo_on_huggingface) +# safe_model_path = f"{tmp}/safe.pt" +# unsafe_model_path = f"{tmp}/unsafe.pt" + +# torch.save(safe_model, safe_model_path) + +# # Inject malicious code using command +# command = "exec" +# malicious_code = 'print("Malicious Code!")' + +# payload = get_pickle_payload(command, malicious_code) +# torch.save( +# torch.load(safe_model_path), +# f=unsafe_model_path, +# pickle_module=PickleInject([payload]), +# ) + +# return tmp + + def compare_results(resultList: List[Issue], expectedSet: Set[Issue]) -> None: for result in resultList: assert result in expectedSet @@ -702,7 +731,142 @@ def test_scan_huggingface_model() -> None: assert ms.issues.all_issues == expected -# def test_scan_tf() -> None: +# def test_scan_pytorch(pytorch_file_path: Any) -> None: +# safe_ms = Modelscan() +# safe_ms.scan_path(Path(f"{pytorch_file_path}/safe.pt")) +# # assert safe_ms.issues.all_issues == [] + +# expected = { +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "transformers.models.gpt2.modeling_gpt2", +# "GPT2LMHeadModel", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "torch.nn.modules.normalization", +# "LayerNorm", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "transformers.models.gpt2.modeling_gpt2", +# "GPT2MLP", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "transformers.activations", +# "NewGELUActivation", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "transformers.models.gpt2.configuration_gpt2", +# "GPT2Config", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "torch.nn.modules.dropout", +# "Dropout", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "torch.nn.modules.container", +# "ModuleList", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "transformers.pytorch_utils", +# "Conv1D", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.CRITICAL, +# OperatorIssueDetails( +# "__builtin__", +# "exec", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "transformers.models.gpt2.modeling_gpt2", +# "GPT2Model", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "torch.nn.modules.sparse", +# "Embedding", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "torch.nn.modules.linear", +# "Linear", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "transformers.models.gpt2.modeling_gpt2", +# "GPT2Attention", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# Issue( +# IssueCode.UNSAFE_OPERATOR, +# IssueSeverity.MEDIUM, +# OperatorIssueDetails( +# "transformers.models.gpt2.modeling_gpt2", +# "GPT2Block", +# f"{pytorch_file_path}/unsafe.pt:unsafe/data.pkl", +# ), +# ), +# } +# unsafe_ms = Modelscan() +# unsafe_ms.scan_path(Path(f"{pytorch_file_path}/unsafe.pt")) +# compare_results(unsafe_ms.issues.all_issues, expected) def test_scan_keras(keras_file_path: Any) -> None: