I’m less interested in the “ShinyHunters did X” angle. There are already enough posts on that......The timing is what bothers me....

Canvas goes down or gets compromised during finals week and suddenly it’s not just an IT ticket. It affects students submitting work, professors grading, deadline extensions, exam logistics, and university comms....

Most schools now depend on a handful of SaaS platforms for core operations. Canvas, Google Workspace, Microsoft 365, Zoom, payment portals, student systems...

That makes life easier until one of them becomes unavailable or untrusted....

The question I keep coming back to is
Are universities treating these platforms like critical infrastructure, or still treating them like normal vendor software?

Because if finals week can be disrupted by one SaaS incident, the risk model probably needs to change.

This report made me realize something.

AI inference is becoming an infrastructure problem, not just an AI problem.

A lot of companies rushed to deploy models, agents, copilots, internal AI tools etc.

But now they have:

• prompt traffic moving through APIs
• model routing layers
• inference gateways
• cached responses
• internal data flowing between tools

That creates a completely new operational surface.

Most security teams already monitor endpoints, identities, SaaS, cloud workloads.

Now they also need visibility into how AI systems are actually being used and what data is moving through them.

Otherwise “normal employee activity” becomes impossible to distinguish from risky AI usage.

https://www.helpnetsecurity.com/2026/05/07/f5-ai-inference-operations-report/