AI workflows may be creating a dangerous new authorization blind spot
Noma Labs researchers describe 'workflow identity hijacking,' letting unauthenticated users trigger privileged AI workflows that execute actions with high-privilege service accounts.
Noma Labs lead researcher Sasi Levi detailed 'workflow identity hijacking,' where benign unauthenticated inputs via support inboxes, GitHub issues, or web forms trigger enterprise AI pipelines that execute privileged actions. The workflow runs using high-privilege service accounts or developer API keys, decoupled from the requester's identity, effectively creating a confused-deputy condition. Unlike prompt injection, the model behaves correctly; the failure lies in authorization enforcement at the workflow layer, and activity blends into routine automation. Mitigations include identity-aware access at execution points and user-context propagation between AI outputs and downstream operations.