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.

The only viable defense against offensive swarms of AI is to create defensive swarms of AI that are even smarter. This dynamic locks humanity into a cat-and-mouse game of escalating intelligence, a runaway train with no clear off-ramp. Each side must continuously advance its AI's capabilities simply to keep pace, increasing systemic risk.

Investigating the OpenAI cyber incident required using powerful AI models that racked up a $400,000 API bill. This signals a future where effective cyber defense against sophisticated AI attacks may be financially inaccessible for smaller companies, local governments, and critical infrastructure operators.

The rise of offensive AI agents creates an arms race where defenders must also deploy AI agents to keep up. This dynamic forces humans out of the loop in cybersecurity incident response, increasing reliance on potentially misaligned AI systems to fight other misaligned systems.

Because AI models can be easily downloaded, traditional regulation is ineffective. The logical endpoint isn't policy, but active 'algorithmic warfare' where proprietary models are used to launch offensive attacks to degrade or trick competing open-source and foreign state-sponsored models.

The perception that AI currently favors hackers over defenders is causing CISOs to increase cybersecurity budgets by 20-30%. This spending surge is a short-term reaction to catch up with new threats. Success is measured not by preventing breaches, but by a massive increase in newly discovered vulnerabilities found by defensive AI tools.

Highly capable open-source models are dual-use cyber weapons. Withholding them creates an asymmetry where attackers have an advantage. However, releasing them gives defenders necessary tools to protect themselves against bad actors who will inevitably acquire capable models, creating a difficult trade-off.

The greatest cybersecurity risk is not powerful AI, but an imbalance where attackers possess capabilities that defenders lack. Open-sourcing models ensures defensive tools can evolve alongside offensive ones, creating a more resilient ecosystem. It empowers defenders to react faster and make the entire system safer for everyone.

The core ethos of open source—unrestricted proliferation of powerful capabilities to everyone—is fundamentally incompatible with the national security state's mandate to control dangerous technologies. As AI models become more potent, this irreconcilable conflict will escalate into a major policy battle.