Parameterized FTQC Attack Cost Estimation via Surface Code Resource Modeling for 28 Cryptographic Algorithms

Estimating the physical quantum resources required to break cryptographic algorithms is essential for planning post-quantum migration timelines. Existing estimates are either algorithm-specific academic results or high-level qualitative assessments that lack configurable parameters. We present a parameterized FTQC attack cost estimation engine that computes physical qubit requirements, execution times, and feasibility timelines for 28 cryptographic algorithms using surface code error correction with 15-to-1 magic state distillation. The engine accepts configurable quantum error rates and target logical error rates, enabling organizations to model scenarios ranging from near-term noisy devices to projected fault-tolerant hardware. We validate our estimates against published results from Gidney & Ekera (2021), Haner et al. (2020), and Lee et al. (ETRI 2025), and provide batch comparison and head-to-head algorithm analysis modes for practical decision-making.