Anthropic's much-hyped Mythos Preview last month, claimed to be a frontier model posing a unique threat to cybersecurity, with limited access. However, an independent evaluation released this week by the AI Safety Institute (AISI) shows GPT-5.5's performance on the same set of cybersecurity tests is essentially on par with Mythos, with differences within statistical error margins. This result directly challenges Anthropic's core narrative. The AISI report points out that Mythos's alleged unique cybersecurity threat is likely not model-specific, but a byproduct of general improvements in long-horizon autonomy, reasoning, and coding — in other words, Anthropic packaged industry-wide progress as the unique capability of its own product. Ironically, OpenAI CEO Sam Altman recently criticized this approach directly in a podcast interview: "This is clearly a brilliant marketing strategy — we built a bomb, about to throw it at your head, you come buy a bunker, $100 million." He said more companies will market themselves as too dangerous to release in the future, while truly dangerous models will be released in different ways. From a technical perspective, this incident reveals a core question in the cybersecurity-model domain: when model capabilities generally improve, how do you define unique threats? Is benchmark design enough to distinguish real capability gaps, or just amplify vendor marketing narratives? For the industry, AISI's independent evaluation mechanism is growing more important. When vendors are both athletes and referees, the market needs third-party institutions to provide objective reference — this evaluation proved GPT-5.5 isn't inferior, but more importantly, it pulled back the curtain on an industry convention: first hype the model to the sky, then limit access on safety grounds, finally let the market verify the truth.