Anthropic’s Project Glasswing has exposed more than 10,000 high-severity flaws in critical open-source components in under a month, with 1,094 confirmed high- or critical-risk issues already driving 97 upstream patches. This volume is not incremental; it marks a phase shift where autonomous model-based discovery outpaces human triage and vendor remediation cycles by orders of magnitude. The WolfSSL certificate forgery case (CVE-2026-5194) is illustrative: Mythos identified an attack path that traditional static analysis and manual review had missed for years. Microsoft’s parallel observation that monthly patch volumes will “continue trending larger” confirms the pressure is already materializing across the ecosystem. Mainstream coverage has framed this as an Anthropic milestone; it is instead an industry-wide forcing function that compresses the entire vulnerability lifecycle. Prior AI tools (e.g., XBOW’s offensive platform) improved candidate generation but still required heavy human filtering. Mythos’s reported ability to chain findings into end-to-end exploits removes that bottleneck. The result is an asymmetric advantage for the 50 Glasswing partners—mostly large banks and infrastructure operators—while the broader open-source commons and smaller vendors face an unmanageable backlog. Historical parallels exist in the post-Heartbleed and post-Log4Shell eras, yet neither produced sustained monthly patch-rate increases of this scale. The absence of adequate safeguards for public release of comparable models (noted in both Anthropic’s and OpenAI’s restricted programs) creates a narrow window before equivalent capabilities diffuse to adversaries. Network defenders must therefore treat accelerated patching, default hardening, and MFA enforcement not as best practices but as survival thresholds. Failure to compress remediation timelines will translate directly into measurable increases in successful exploitation across supply-chain targets.