Recently, both academia and industry have recognized the need for leveraging real-time information for the purposes of specifying, enforcing and maintaining rich and flexible authorization policies. In such a context, security-related properties, a.k.a., attributes, have been recognized as a convenient abstraction for providing a welldefined representation of such information, allowing for them to be created and exchanged by different independently-run organizational domains for authorization purposes. However, attackers may attempt to compromise the way attributes are generated and communicated by recurring to hacking techniques, e.g., forgery, in an effort to bypass authorization policies and their corresponding enforcement mechanisms and gain unintended access to sensitive resources as a result. In this paper,we propose a novel technique that allows for enterprises to pro-actively collect attributes fromthe different entities involved in the access request process, e.g., users, subjects, protected resources, and running environments. After the collection, we aim to carefully select the attributes that uniquely identify the aforementioned entities, and randomly mutate the original access policies over time by adding additional policy rules constructed from the newly-identified attributes. This way, even when attackers are able to compromise the original attributes, our mutated policies may offer an additional layer of protection to deter ongoing and future attacks. We present the rationale and experimental results supporting our proposal, which provide evidence of its suitability for being deployed in practice.