Histórico de Auditoria

This is a legitimate scientific computing skill for DeepChem molecular machine learning. All 237 static findings are false positives. The findings originate from markdown documentation code examples being incorrectly flagged as executable Ruby/shell commands. Common English words in chemistry documentation are matching C2 security patterns. The Python scripts use argparse for safe argument handling with no hardcoded secrets or dangerous operations.

This is a legitimate scientific computing skill for DeepChem molecular machine learning. All 237 static findings are false positives. The findings originate from markdown documentation code examples being incorrectly flagged as executable Ruby/shell commands. Common English words in chemistry documentation are matching C2 security patterns. The Python scripts use argparse for safe argument handling with no hardcoded secrets or dangerous operations.

This is a legitimate scientific computing skill for molecular machine learning. All static analysis findings are false positives resulting from pattern matching without context understanding. The skill provides safe molecular property prediction capabilities using the DeepChem library.

Contains executable Python scripts for molecular ML training. Scripts access local data files and download public datasets and pretrained models through DeepChem. No credential harvesting, obfuscation, or suspicious network behavior detected.