Arkose Labs expands Agent Trust Manager to govern agent sessions

The vast majority of AI agents traversing business systems fail to identify themselves, making traditional bot detection and access control mechanisms nearly blind to their presence. Because these agents can mimic human behavior or blend into normal traffic, organizations cannot enforce consistent policies around what agents are allowed to do, what data they can access, or when they should be blocked. This creates a significant trust gap: businesses may be granting AI agents the same access privileges as legitimate human users without realizing it. Without proper classification, monitoring, and policy enforcement specifically designed for agentic traffic, companies are exposed to data exfiltration, unauthorized actions, and compliance failures. The emergence of AI agents as a distinct traffic class demands a new layer of identity and access governance beyond what traditional tools provide.