Results for “metal-dollar”

Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.

Detect NTFS timestamp manipulation (MITRE T1070.006) by comparing $STANDARD_INFORMATION vs $FILE_NAME timestamps in the MFT using analyzeMFT and Python.

Executes Atomic Red Team tests for MITRE ATT&CK technique validation using the atomic-operator Python framework. Loads test definitions from YAML atomics, runs attack simulations, and validates detection coverage.