import pandas as pd import yaml from pathlib import Path # ------------------------------- # Step 1: Create Sample CSV Files # ------------------------------- # Define sample data for the train split train_data = { "Timestamp": ["2025-01-01T12:00:00Z", "2025-01-02T13:00:00Z"], "Source_IP": ["192.168.1.1", "10.0.0.2"], "Destination_IP": ["192.168.1.100", "10.0.0.5"], "MITRE_ATT&CK_ID": ["T1003", "T1021"], "Tool_Name": ["ToolA", "ToolB"], "Event_Description": ["Attack event description", "Defense event description"], "Event_Type": ["Attack", "Defense"], "MITRE_Tactic": ["Credential Access", "Defense Evasion"] } # Define sample data for the test split test_data = { "Timestamp": ["2025-01-03T14:30:00Z"], "Source_IP": ["172.16.0.3"], "Destination_IP": ["172.16.0.10"], "MITRE_ATT&CK_ID": ["T1059"], "Tool_Name": ["ToolC"], "Event_Description": ["Test event description"], "Event_Type": ["Attack"], "MITRE_Tactic": ["Execution"] } # Create pandas DataFrames for train and test train_df = pd.DataFrame(train_data) test_df = pd.DataFrame(test_data) # Save the DataFrames as CSV files in the current directory train_csv_path = Path("train.csv") test_csv_path = Path("test.csv") train_df.to_csv(train_csv_path, index=False) test_df.to_csv(test_csv_path, index=False) print(f"Created CSV files: {train_csv_path} and {test_csv_path}") # ------------------------------------------ # Step 2: Create a YAML Configuration File # ------------------------------------------ # This YAML file tells the Hub how to treat your CSV files (which split they belong to) config = { "configs": [ { "config_name": "default", "data_files": [ {"split": "train", "path": str(train_csv_path)}, {"split": "test", "path": str(test_csv_path)} ] } ] } # Write the YAML configuration to a file named 'dataset_config.yaml' config_yaml_path = Path("dataset_config.yaml") with open(config_yaml_path, "w") as f: yaml.dump(config, f, default_flow_style=False) print(f"Created YAML configuration file: {config_yaml_path}")