Fuzzing, an automated software testing technique, has achieved remarkable success in recent years, aiding developers in identifying vulnerabilities. However, fuzzing can also be exploited by attackers to discover zero-day vulnerabilities. To counter this threat, researchers have proposed anti-fuzzing techniques, which aim to impede the fuzzing process by slowing the program down, providing misleading coverage feedback, and complicating data flow, etc. Unfortunately, current anti-fuzzing approaches primarily focus on enhancing defensive capabilities while underestimating the associated overhead and manual efforts required. In our paper, we present No-Fuzz, an efficient and practical anti-fuzzing technique. No-Fuzz stands out in binary-only fuzzing by accurately determining running environments, effectively reducing unnecessary fake block overhead, and replacing resource-intensive functions with lightweight arithmetic operations in anti-hybrid techniques. We have implemented a prototype of No-Fuzz and conducted evaluations to compare its performance against existing approaches. Our evaluations demonstrate that No-Fuzz introduces minimal performance overhead, accounting for less than 10% of the storage cost for a single fake block. Moreover, it achieves a significant 92.2% reduction in total storage costs compared to prior works for an equivalent number of branch reductions. By emphasizing practicality, our study sheds light on improving anti-fuzzing techniques for real-world deployment.