История аудитов

This skill provides documentation and templates for PyTDC, a legitimate drug discovery dataset library. All 427 static findings are false positives caused by markdown code blocks containing Python examples (detected as shell backticks), scientific terminology (DRD2, GSK3B detected as C2 keywords), and molecular/cryptographic naming overlaps. No actual security risks present.

This skill provides documentation and templates for PyTDC, a legitimate drug discovery dataset library. All 427 static findings are false positives caused by markdown code blocks containing Python examples (detected as shell backticks), scientific terminology (DRD2, GSK3B detected as C2 keywords), and molecular/cryptographic naming overlaps. No actual security risks present.

This is PyTDC (Therapeutics Data Commons), a legitimate open-source scientific library for drug discovery ML. All 401 static findings are false positives: markdown backticks flagged as shell commands, protein target names (GSK3B, DRD2) flagged as C2 keywords, ML random seeds flagged as weak crypto, and dictionary keys flagged as certificate files. The skill accesses curated pharmaceutical datasets and provides benchmarks - no malicious behavior present.

No credential access, environment harvesting, or network exfiltration patterns found. Scripts are local examples for dataset loading, evaluation, and oracle usage.