This research demonstrates an automated pipeline for bug bounty programs, addressing vulnerabilities through multi-specialist models, indicating enhanced security measures.
The modern bug bounty landscape presents a dual challenge: the volume of attack surface across large programs is vast and continuously evolving, while the depth of expertise required to identify sophisticated vulnerabilities demands specialized knowledge across multiple security domains. Traditional approaches — manual penetration testing, monolithic vulnerability scanners, and single-model machine learning systems — struggle to simultaneously achieve breadth of coverage and depth of analysis.
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Yahya Saqban (2026) studied this question.
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