Author: Gonzalo Emir Durante DOI: 10.5281/zenodo.19052627/19702379Registry: EX-2026-18792778 (TAD, Argentina) License: Durante Invariance License v1.0 (GPL-3.0 with mandatory attribution)Paper-Hash 979865522957907b8e0f27ec56e318b476284ef4a3274878caeda423cd434069 --- We present SAS (Symbiotic Autoprotection System), an open, precision-oriented framework for detecting structural semantic rupture in human-AI interaction. The core metric, the Invariance Stability Index (ISI), compares prompt-response pairs by computing persistent homology over sentence embeddings and quantifying topological deformation via Wasserstein distances. The central coherence threshold, κD = 0.56, is introduced as a coherence threshold with empirical stability, not as a proven universal constant but as a reproducible, mathematically motivated boundary between coherent semantic preservation and structural hallucination. SAS is validated on the HALOGEN corpus (156,215 pairs), achieving 97.63% precision and 61.81% recall, prioritizing forensic reliability over broad recall. The framework distinguishes structural hallucination (e.g., negation reversal, reference fabrication, arithmetic inconsistency, topological drift) from factual inaccuracies that require external knowledge. This work establishes a timestamped, open, and replicable standard for AI coherence auditing, with full reproducibility metadata including TAD registry EX-2026-18792778, Zenodo DOI 10.5281/zenodo.19543972, GNU GPLv3 license, and Bitcoin-anchored OpenTimestamps. SAS is designed for high-stakes audit contexts where false accusations must be minimized.