Veritas Protocol v1.2.0: The Functional Substrate for Logic Authenticity Auditing

This update (v1.2.0) marks a significant transition of the Veritas Protocol from a conceptual framework to a functional, deployable toolkit. While the previous version established the ethical and theoretical groundwork for AI responsibility and informational integrity, version 1.2.0 provides the operational infrastructure required to perform real-time audits.

Key Updates in this version:

• Operational LAC (Logic Authenticity Check): Implementation of algorithmic filters that detect systemic fragmentation and emotional manipulation in information streams.

• Entropy Stability Index (ESI) Engine: Tools for quantifying informational noise, allowing for the mathematical distinction between signal and disinformation.

• Minimalist CLI Interface: Added interface.py and verify_news.py, enabling users to run integrity monitors locally.

• Audit Logging System: Automated recording of verification results into structured datasets for long-term analytical review.

• The Slashing Mechanism: Further refinement of the economic model designed to penalize high-entropy (manipulative) actors within the informational ecosystem.

Technical Changes:

• Full Python 3.10+ compatibility.

• Introduction of automated unit tests (sim_test.py) for logic validation.

• Dependency management via requirements.txt.

Context: This protocol continues to treat all information sources (human or AI) as agents subject to the same laws of logical integrity and entropy. It remains the only framework providing a "missing frame" for AI subjecthood through the lens of verifiable responsibility.