The AI vulnerability race has begun, and the timeline is alarmingly short. Advanced AI models can already identify security flaws seven times faster than human teams. Cybersecurity firms estimate that organizations have only three to five months before attackers gain widespread access to similar AI-powered exploit capabilities.

A key threshold in AI-driven hacking has been crossed. Models can now autonomously chain multiple, distinct vulnerabilities together to execute complex, multi-step attacks—a capability they lacked just months ago. This significantly increases their potential as offensive cyber weapons.

The true cybersecurity risk isn't one company having a model like Mythos, but when several do. This creates a game-theoretic dilemma where exploiting vulnerabilities offers a greater first-mover advantage than patching them, incentivizing an offensive arms race between AI labs and the nations they reside in.

AI tools aren't just lowering the bar for novice hackers; they are making experts more effective, enabling attacks at a greater scale across all stages of the "cyber kill chain." AI is a universal force multiplier for offense, making even powerful reverse engineers shockingly more effective.

The Chinese government may be more willing to release powerful open-weight AI models because it already operates in an environment of "cyber exploit abundance." Having long managed a system of acquiring and using zero-day vulnerabilities, the state may not perceive the same level of novel threat from democratized cyber capabilities as Western governments do.

For decades, software has contained vulnerabilities manageable only due to a limited number of human attackers. AI allows any individual to spin up hundreds of qualified "attackers" instantly, creating a massive force that will systematically exploit this historical security debt, leading to widespread chaos.

While focus is often on an AI's ability to find single vulnerabilities ("short-horizon" tasks), the real danger is its capacity for "long-horizon" planning. This involves autonomously chaining exploits and devising complex strategies to achieve a high-level goal, akin to an NSA red team manager.

An AI model capable of executing complex cyberattacks is equally capable of identifying and fixing those same vulnerabilities. A government like China's will likely first deploy the model for defense—patching critical systems—before any public or commercial release, thus mitigating risk.

AI models are better at finding bad code than writing good code. This capability will rapidly uncover vulnerabilities in open-source, custom, and vendor software that would have otherwise taken 10 years to find. This creates an urgent, large-scale need for patching across all industries.