discovered 19 Aug 2026
PhantomTap
→ View on GitHubPhantomTap is a machine learning-enhanced tool for the Flipper Zero, specifically designed for RFID/NFC fuzzing and access-control auditing. It utilizes active learning to intelligently generate test credentials, significantly reducing the number of reader queries required for effective security assessments, and produces an explainable audit report for identifying vulnerabilities in badge systems. Notably, it features efficient characterization, Bayesian population sizing, and integrates detection mechanisms to monitor real-time security threats.