Our paper ReasoningBomb has been accepted to ACM CCS 2026! We propose an RL-based framework that crafts short, natural-language prompts to trap LRMs into pathologically long reasoning, with a constant-time surrogate reward enabling 4.39×10⁵× training speedup. Just 10% malicious traffic cuts benign throughput by 49.8% and monopolizes 64.3% of compute. Check out our paper, website, code, and dataset.