The Doppelgänger Framework describes a new attack class where credentials are valid and actions are permitted, making intrusions indistinguishable from normal operations. This isn't living off the land; it's living inside the workflow. Attackers like those behind the 2022 Uber breach observe behavior, learn access patterns, and inherit trust through valid sessions, leaving no traditional malware signatures.

Traditional security tools fail because they measure isolated events, not malicious intent. Defenders see permitted actions, while attackers substitute malicious goals into legitimate sequences. This gap between what a system allows and what a human intends is the core vulnerability. The framework argues that intent is the only anomaly, making it invisible to machines focused on compliance and anomalies.

To combat this, the guide proposes sequence-aware analytics and trust-graph traversal over static indicators. Key controls include Just-In-Time privilege elevation and identity-centric baselines that track per-user behavior. Small businesses are especially vulnerable due to overlapping roles and shared credentials, where predictable gaps are plentiful. The challenge is shifting from monitoring events to understanding operational narratives.