Post by Shailej Iskande

Anthropic’s “Claude Mythos” narrative points to a future where vulnerabilities can be identified at scale—but the more immediate reality is already here. As highlighted by Nicholas Carlini from Anthropic: LLMs are no longer just productivity tools—they are capable of discovering zero-days and enabling real-world attacks. This fundamentally changes the equation. What was once rare and expertise-driven is now becoming: 👉 Scalable, repeatable, and increasingly automated What this means for enterprises Zero-day risk is no longer an edge case—it’s a continuous condition. Two paths are emerging: 1. Augmented Defenders AI-enabled SDLC (SAST/DAST/fuzzing at scale) Automated remediation pipelines Focus on exploitability, not just severity 👉 Assume: if it exists, it’s already known 2. Blind Spots Periodic scanning Manual remediation Fragmented visibility 👉 Result: Exposure compounds faster than it can be reduced The shift required Move from vulnerability management → exposure management Prioritize speed of remediation over volume of findings Design for blast radius reduction (identity, segmentation, least privilege) The future may reduce vulnerabilities. But right now, AI is doing the opposite: 👉 Increasing discovery 👉 Compressing timelines 👉 Amplifying asymmetry Security is no longer about finding vulnerabilities first— It’s about responding before they are exploited. #CyberSecurity #AI #DevSecOps #ZeroTrust #ExposureManagement