Universal Fair Bounty Framework (UFBF): A Contribution-Aware Full-Lifecycle Model for Bug Bounty Programs in AI-Augmented Environments

This work introduces the Universal Fair Bounty Framework (UFBF), a novel full-lifecycle model designed to address structural inefficiencies in modern bug bounty programs. With the rise of AI-generated vulnerability reports, traditional first-to-report reward systems have become increasingly unfair and inefficient. UFBF proposes a mathematically grounded, contribution-aware approach that evaluates reports based on technical value rather than submission timing. The framework integrates: - Contribution-based scoring models - Graph-based vulnerability representation - Proportional reward distribution - AI-resistance mechanisms - Reputation-based triage optimization This document aims to redefine bug bounty ecosystems as collaborative security economies rather than competitive races.