AI Attack Velocity and Infrastructure Spend Share the Same Supply-Chain Bottleneck

The PHP2Shell pre-patch probes via commercial anonymization networks, Storm-0940’s ARTEX-driven 2900-attempts-per-minute ConnectWise compromise, and LiteLLM’s stolen-GitHub-OAuth PyPI poisoning are not isolated security incidents. They sit on the same timeline as Meta’s explicit warning that rising AI serving costs are now the dominant margin pressure after its $64.6 B revenue beat. In each case the constraint is identical: the speed at which AI can iterate new attack or inference workloads exceeds the rate at which either patching pipelines or data-center capacity can absorb them. The older headlines on GitLab backports and Canarytokens deployment after Meta’s regulatory hit simply extend the same loop—offense scales first, defense and cost accounting follow. What remains uncovered is that the commercial anonymization networks selling the PHP2Shell traffic are themselves likely running on the same GPU fleets whose utilization rates Meta must now defend.