A Python framework for combining static analysis with LLM-based bug verification
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Updated
Jun 1, 2026 - Python
A Python framework for combining static analysis with LLM-based bug verification
Stage338: Behavior Decision Engine for expected-vs-actual behavior verification.
This project, developed with Python and PyQt6, involves creating an .exe application to verify and change vulnerability statuses, visualize results, and export new vulnerabilities.
AI vulnerability verification demo using the Stage299 QSP/VEP Gate engine.
Safe Reproduction Template Library for AI vulnerability verification. Defines safe reproduction templates, expected behavior, pass/fail conditions, and safety boundaries without attack code.
REMEDA Stage327: structured reproduction evidence schema for AI vulnerability verification, target matching, SHA256 integrity binding, and third-party audit verification.
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