Cloud applications are appealing targets to attackers, yet current cloud infrastructures have few ways of helping defend their customers from attacks. However, the use of virtual machines, and the economy of scale found in cloud platforms, provides an opportunity to oer strong security guarantees to tenants at low cost to the cloud provider. We present CRIMES, an evidence based, modular security framework for cloud platforms that uses speculative execution coupled with memory introspection tools to detect malicious behavior in real time. By buering VM outputs (i.e., outgoing network packets and disk writes) until a scan has been completed, CRIMES gives strong guarantees about the amount of damage an attack can do, while minimizing overheads. When an attack is detected, CRIMES rolls back to a recent checkpoint and performs automated forensic analysis to help pinpoint the source of an attack. Our evaluation demonstrates that CRIMES incurs less overhead compared to memory protection tools such as AddressSanitizer, while oering valuable forensic analysis for buer overow attacks and malware detection across multiple applications and the OS. CCS CONCEPTS • Security and privacy → Virtualization and security; Distributed systems security;