The Post-Mythos Security Model: Vulnerability Management in the AI Age
Learn why AI-driven vulnerability discovery breaks the patching paradigm and what organizations must do now.
Download the White Paper
In the white paper you will learn:
- The implications of AI accelerating vulnerability discovery and exploit creation
- Why patch-first security strategies will not be able to keep up with the volume and pace of vulnerability discovery
- Three perspectives on the issues AI introduces and next steps for organizations addressing the risk
- How RunSafe Security reduces AI exploitability, protecting software from AI-driven attacks even before patches are available
When Patching Isn’t Enough: AI Vulnerability Management
The idea of patch-centric security—that defenders can roughly keep pace with attacker discovery—is being invalidated by the ability of Mythos AI and other models to quickly find and exploit vulnerabilities at scale.
AI-assisted vulnerability discovery and exploit development will strain most organizations’ patching models beyond their load-bearing capacity. The response cannot be a faster version of the same model. It requires security programs that protect systems while vulnerabilities exist, not only after they are remediated.
Deploy RunSafe’s Patented Code Protection
RunSafe Security has spent years focused on exactly this problem: protecting software against exploitation while vulnerabilities are present, not only after they are patched.
Learn how our patented Load-time Function Randomization (LFR) technique makes exploitation structurally harder so that, even when a vulnerability exists and an adversary has the tools to find and weaponize it, the determinism required to build a reliable attack is absent.