Get your free personalized podcast brief

We scan new podcasts and send you the top 5 insights daily.

For most organizations, defending against AI-powered attacks won't mean fighting AI with AI. The more practical strategy will be to 'quarantine' critical systems by creating partitioned networks. This suggests a future of a more fragmented internet, driven by security needs rather than geopolitics.

Related Insights

The threat of AI-driven cyberattacks that can defeat modern encryption may render current secure networks (like SIPRnet) obsolete. This could force government and military organizations to revert to expensive and inefficient physically-isolated, "air-gapped" systems for classified communications.

Despite AI supercharging offensive capabilities, the defender's ultimate advantage remains unchanged: they set the operational terrain. Basic, often-neglected measures like network air-gapping are more critical than ever, as they create structural barriers that even advanced AI struggles to overcome.

The cybersecurity landscape is now a direct competition between automated AI systems. Attackers use AI to scale personalized attacks, while defenders must deploy their own AI stacks that leverage internal data access to monitor, self-attack, and patch vulnerabilities in real-time.

Kevin Mandia predicts that within two years, all cyberattacks will be AI-driven. The sheer speed of these threats makes human-in-the-loop defense obsolete. The only viable response is a fully autonomous, AI-powered defensive system to counter AI-born threats.

Historically, many organizations only implement robust cybersecurity after being attacked, despite knowing the risks. AI-powered offense dramatically raises the stakes by increasing the speed and scale of threats, making this reactive posture untenable and potentially catastrophic.

Instead of relying on flawed AI guardrails, focus on traditional security practices. This includes strict permissioning (ensuring an AI agent can't do more than necessary) and containerizing processes (like running AI-generated code in a sandbox) to limit potential damage from a compromised AI.

The long-term trajectory for AI in cybersecurity might heavily favor defenders. If AI-powered vulnerability scanners become powerful enough to be integrated into coding environments, they could prevent insecure code from ever being deployed, creating a "defense-dominant" world.

While AI gives attackers scale, defenders possess a fundamental advantage: direct access to internal systems like AWS logs and network traffic. A defending AI stack can work with ground-truth data, whereas an attacking AI must infer a system's state from external signals, giving the defender the upper hand.

The old security adage was to be better than your neighbor. AI attackers, however, will be numerous and automated, meaning companies can't just be slightly more secure than peers; they need robust defenses against a swarm of simultaneous threats.

Adversaries are using AI to create an "asymptotic attack pressure" with novel exploits moving at machine speed. Traditional human-speed defense is insufficient. The solution is an autonomous defensive system that mirrors the attackers, creating a corresponding counter-pressure to analyze threats and respond in real-time.

AI Cyber Threats Will Force a Defensive Partitioning of the Internet | RiffOn