AITBM – AI Trust Benchmarking and Maturity Framework

AITBM is a bias-resistant framework for quantifying AI security risk without subjective guesswork. It uses a three-layer architecture: Intrinsic Vulnerability Profile (21 sub-metrics across 5 security axes), Operational Risk Posture (deployment context), and Assurance Confidence Index (evidence freshness). It produces a mathematically grounded composite score (ERS) that preserves multi-dimensional signal.

Key features: deterministic rubrics (0–4 scoring), agentic-native threat modeling, tiered assessment pathways, and alignment with 16 external frameworks (OWASP, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, EU AI Act). Includes specification, worked examples, website with calculator, and Docker deployment. 

https://github.com/ninedter/AITBM

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