CISA added a LiteLLM vulnerability, CVE-2026-42271, to its Known Exploited Vulnerabilities catalog in June after attackers abused it in the wild. The bug executed commands on the host through the gateway itself and required no credentials when chained with a second flaw. It was one of seven CVEs disclosed in that single AI gateway within a month. This is the layer most enterprises reach for first when securing AI agents. That is the wrong starting point.
The article's core argument is a six-gate dependency chain: agent inventory, distinct agent identity with delegation context, task-scoped short-lived credentials, attributable telemetry, runtime action enforcement, and behavioral baselines with a cross-system kill path. Gateways are gate five. Running them at gate one means enforcing policy without knowing which agent is acting, who delegated it, or what task it was assigned. A 2026 Teleport study of 205 security leaders puts numbers on the cost of skipping the early gates: organizations with over-privileged AI reported a 76% incident rate versus 17% for those running least-privilege access. The gap between those two numbers is not a gateway problem. It is an identity and credential-scoping problem.
What makes this worth reading in full is not the conclusion but the sequencing logic. The author frames this as a brownfield problem, specifically how to layer controls against an IAM system that already exists, not a greenfield architecture. The monotonic delegation principle, every transfer of authority must preserve or reduce scope, never expand it, is a concrete rule teams can apply immediately. The dependency-gated deployment model also defines operational proof of completion for each gate, not just descriptions of what the control does. If your team is debating where to start on agent security, this article provides the argument for why the answer is almost certainly not where you are starting.
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