The primary cyber threat from AI is not new attack vectors, but the speed at which models can discover existing vulnerabilities. The only effective defense is to use AI to find, prioritize, and patch these flaws faster than adversaries can exploit them.

Unlike human attackers, AI can ingest a company's entire API surface to find and exploit combinations of access patterns that individual, siloed development teams would never notice. This makes it a powerful tool for discovering hidden security holes that arise from a lack of cross-team coordination.

AI has armed cyber attackers with a new weapon: swarms of coding agents. Unlike human attackers, these agents can exhaustively and rapidly review an entire codebase to find vulnerabilities, dramatically increasing the speed and scale of cyber threats. This necessitates a boom in AI-powered defensive tools.

Don't expect compute costs to limit AI-powered cybercrime. Models are becoming so efficient they can run on a laptop. The reason we haven't seen a massive AI-driven surge in attacks yet is likely due to organizational dynamics; criminal enterprises face the same slow adoption curves for new technology as any legitimate business.

AI tools drastically accelerate an attacker's ability to find weaknesses, breach systems, and steal data. The attack window has shrunk from days to as little as 23 minutes, making traditional, human-led response times obsolete and demanding automated, near-instantaneous defense.

The fear that models like Mythos can 'hack the NSA' is misplaced. The real threat is that if an attacker gains initial access, these models dramatically speed up exploit design, reducing the time security teams have to detect and contain the intrusion.

Powerful AI models haven't created fundamentally new ways to hack. Instead, their danger lies in their ability to find more vulnerabilities faster and link existing attack chains with greater success. They are a force multiplier for existing techniques, not inventors of new ones.

AI agents are not inventing new categories of cyberattacks. Instead, they automate and accelerate traditional methods—like vulnerability discovery and exploit chaining—at a speed and scale far surpassing human capabilities. This dramatically shortens the timeline for organizations to adapt their defenses.

Previously, attackers spent weeks inside a system before striking. AI agents can now find and exploit vulnerabilities at machine speed, rendering traditional detection insufficient. The focus must now be on immediate recovery and resilience, assuming a breach has already occurred.