An AI cybersecurity model from Anthropic, Claude Mythos Preview, triggered industry panic after claims that it could uncover vulnerabilities at scale. The materials note the model reportedly found a patched weak spot in OpenBSD that Anthropic said went undiscovered for 27 years, along with “thousands” of additional high- and critical-severity issues. A senior security executive, David Lindner, chief information security officer at Contrast Security, argues the more important risk is not discovery but remediation. He says organizations have ongoing piles of vulnerabilities they do not fix and warns that AI-driven discovery does little to address persistent threats like social engineering. The discussion also highlights access constraints: Anthropic says Mythos will not be publicly released and is being shared with a limited group of organizations via “Project Glasswing,” including major tech and security firms and JPMorgan. For higher education and campus technology leaders, the message is governance-focused: institutions adopting AI security tools may need equal investment in patching capacity, vulnerability management workflow, and training against human-targeted attacks—areas that may not improve simply by increasing vulnerability counts.