Current testing methods for frontier AI models are becoming obsolete as the models' hacking capabilities rapidly outpace existing benchmarks. As AI models like GPT-5.5 demonstrate advanced reasoning and agentic behaviors, static tests focusing on isolated tasks fail to capture their true potential in realistic environments. Consequently, policymakers and security teams lack clear metrics to predict deployment safety. In response, industry leaders like Anthropic are collaborating with partners like Google and Microsoft to develop standardized benchmarks focused on the actual impact of jailbreaks. Meanwhile, testing labs like Irregular are creating new metrics to measure offensive tasks such as remote code execution and privilege escalation. The shift highlights a critical need for evaluations that simulate real-world production systems to determine how effectively AI can bypass security controls or move laterally through networks.