Token Security Warns SOC 2 Controls May Fail to Distinguish AI Agent Activity from Human Actions

As AI agents become more prevalent in enterprise workflows, they are increasingly granted access through human credentials to perform tasks ranging from data retrieval to system configuration. Token Security's analysis suggests that current SOC 2 control sets may not be designed to distinguish these agent-driven actions from those of actual users. Because SOC 2 relies heavily on logging access and reviewing user behavior, the indistinguishable nature of agent activity poses a risk: auditors and automated tools may misclassify malicious or erroneous agent actions as normal human activity. This misclassification undermines the integrity of access governance mechanisms and creates blind spots in anomaly detection systems. The advisory does not describe a new vulnerability or active exploit but rather a design and compliance gap. Token Security recommends that organizations using AI agents implement agent identity governance, segregate credentials where possible, and deploy behavior-based anomaly detection to differentiate agent traffic from human traffic. The firm also suggests that SOC 2 auditors and framework administrators consider updating control criteria to account for non-human identities. As of the article's publication date, no standardized SOC 2 modifications addressing AI agent identities have been adopted industry-wide.