On July 2, Anthropic, together with Glasswing partners including Amazon, Microsoft, and Google, officially launched the "Cyber Jailbreak Severity" (CJS) scoring framework — the industry's first unified standard for quantifying LLM jailbreak attacks into five severity levels. CJS splits jailbreak into four scoring dimensions: capability gain (whether the capabilities the attacker obtains from the model exceed existing tools), capability breadth (whether the same technique can be reused across multiple attack tasks), weaponization difficulty (how much human effort is needed to turn the technique into a usable attack), and discoverability (how easy it is for threat actors to obtain the technique). The four-axis scores sum into five tiers from CJS-0 (informational) to CJS-4 (critical), with exponential relationships between tiers — each step up multiplies the risk by several times. The framework's biggest highlight is aligning jailbreak governance with the CVSS approach that the software security industry is accustomed to. Today, when LLM security research has long lacked unified terminology, different vendors can only qualitatively describe "some jailbreak" when reporting it, making it hard for regulators and enterprises to judge priorities. CJS maps each finding to a comparable number, and Anthropic has published grading examples for historical cases including Log4Shell, Bypass jailbreak, and task decomposition. As a companion action, Anthropic has launched a HackerOne public bug bounty program, and set up a 24/7 monitoring team to track jailbreak submission channels. The classifier deployed for Fable 5 is recalibrated under the new framework, with the goal of compressing the "safety margin" to just barely blocking real threats of CJS-2 and above. On the opinion side, this is a key step in LLM security moving from "each defending itself" to "industry co-judging". But whether CJS becomes the de facto standard depends on whether OpenAI, Google DeepMind, and Meta adopt it — if only Anthropic uses it, this scoring can only constrain Anthropic's own model release rhythm.