"I think what you're seeing now is the adversaries, the bad guys, they're basically focused on, 'look where's the weakest link, where is the place where we've spent the least?' And infrastructure people are about throughput and speed and access, and security is about protection. And if you have a domain that is split between those two, you're going to find weaknesses."
"Identity really is sort of the tip of the spear of watching for breaches, because there will be failures probing an identity that will give you indicators that something bad is going to happen before it happens. Once they have the authenticated identity, then it's really damaging. But if you can see the leading indicators, you can get in front of it, and I think this is where AI is going to really help."
Identity management remains challenging and AI agents increase complexity by creating thousands of additional identities across MCP and API endpoints. Cybersecurity teams must manage human, machine, and AI agent identities concurrently to prevent exploitation. Attackers focus on the weakest links where infrastructure emphasizes throughput and security emphasizes protection, producing split domains with exploitable gaps. A structural imbalance often advantages adversaries. Probing failures against identities generate early indicators of compromise that can reveal attacks before authentication succeeds. Detecting those leading indicators enables preemptive response. AI can enhance detection of anomalous identity behavior and help intercept identity-based attacks earlier.
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