Recently, the use of well-defined, security-relevant pieces of runtime information, a.k.a., attributes, has emerged as a convenient paradigm for writing, enforcing, and maintaining authorization policies, allowing for extended flexibility and convenience. However, attackers may try to bypass such policies, along with their enforcement mechanisms, by maliciously forging the attributes listed on them, e.g., by compromising the attribute sources : operative systems, software modules, remote services, etc., thus gaining unintended access to protected resources as a result. In such a context, performing a proper risk assessment of authorization policies, taking into account their inner structure: rules, attributes, combining algorithms, etc., along with their corresponding sources, becomes highly convenient to overcome \emphzero-day vulnerabilities, before they can be later exploited by attackers. With this in mind, we introduce \toolname, an automated risk assessment framework for authorization policies, which, besides being inspired by well-established techniques for vulnerability analysis such as symbolic execution, also introduces the very first approach for proactively assessing risks in the context of a series of attacks based on unintended attribute manipulation via forgery. We validate our approach by resorting to a set of case studies we performed on both real-life policies originally written in the English language, as well as a set of policies obtained from the literature, which show not only the convenience of our approach for risk assessment, but also reveal that some of those policies are vulnerable to attribute-forgery attacks by just compromising one or two of their attributes.