Detecting Multi-Step IAM Attacks in AWS Environments via Model Checking

Cloud services enjoy a surging popularity among IT professionals, owing to their rapid provision of virtual infrastructure on demand. Hand-in-hand with the growing usage, there is also a growing concern about potential security vulnerabilities arising from misconfigurations, exposing resources or allowing malicious actors to escalate privileges. Model checking is a known method for verifying that a finite-state Boolean model of a system satisfies certain properties, where the model and the properties are described in formal logic. In case it doesn’t, a finite trace leading to a violating state can be generated.

In this paper, we present an approach to construct a finite-state Boolean model from the Identity and Access Management (IAM) component of Amazon Web Services (AWS), and a property from an attack target, e.g., read a classified S3 bucket object. We run a model checker that detects whether some initial setup allows an attacker to escalate privileges and reach the target in one or more steps by applying IAM manipulating actions. We show that our approach can discover existing misconfigurations in real AWS environments, and that it can detect multi-step attacks in setups containing tens of AWS accounts with hundreds of resources in under a minute.