When Identity is the Attack Path

Consider a cached access key on a single Windows machine. It got there the way most cached credentials do - a user logged in, and the key stored itself automatically. Standard AWS behavior. No one misconfigured anything or violated a policy. Yet that single key, which was easily accessible to a minor-league attacker, could have opened a path to some 98% of entities in the company's cloud

The article describes how a single cached AWS access key on a Windows machine—left there through normal login behavior—could be harvested by an attacker and used to reach approximately 98% of entities in the company’s cloud environment. This is a classic identity and credential exposure issue, where no explicit misconfiguration is needed for a powerful lateral movement path to exist. From a CyberSE.AI perspective, the practical implication is that any AI agents or AI-integrated systems with access keys, tokens, or role credentials cached on endpoints or in application runtimes can create similarly expansive blast radii if compromised. Organizations should evaluate where AI components store and reuse credentials, enforce least-privilege and short-lived tokens, and integrate identity-aware threat modeling into AI Security Readiness Assessments and Business Logic Audits to prevent large-scale data leakage and unauthorized cloud access via a single compromised identity.