No abstract

This paper presents SgxPectre Attacks that exploit the recently disclosed CPU bugs to subvert the confidentiality and integrity of SGX enclaves. Particularly, we show that when branch prediction of the enclave code can be influenced by programs outside the enclave, the control flow of the enclave program can be temporarily altered to execute instructions that lead to observable cache-state changes. An adversary observing such changes can learn secrets inside the enclave memory or its internal registers, thus completely defeating the confidentiality guarantee offered by SGX. To demonstrate the practicality of our SgxPectre Attacks, we have systematically explored the possible attack vectors of branch target injection, approaches to win the race condition during enclave's speculative execution, and techniques to automatically search for code patterns required for launching the attacks. Our study suggests that any enclave program could be vulnerable to SgxPectre Attacks since the desired code patterns are available in most SGX runtimes (e.g., Intel SGX SDK, Rust-SGX, and Graphene-SGX). Most importantly, we have applied SgxPectre Attacks to steal seal keys and attestation keys from Intel signed quoting enclaves. The seal key can be used to decrypt sealed storage outside the enclaves and forge valid sealed data; the attestation key can be used to forge attestation signatures. For these reasons, SgxPectre Attacks practically defeat SGX's security protection. This paper also systematically evaluates Intel's existing countermeasures against SgxPectre Attacks and discusses the security implications.

We present a new attack framework for conducting cachebased side-channel attacks and demonstrate this framework in attacks between tenants on commercial Platform-as-aService (PaaS) clouds. Our framework uses the FlushReload attack of Gullasch et al. as a primitive, and extends this work by leveraging it within an automaton-driven strategy for tracing a victim's execution. We leverage our framework first to confirm co-location of tenants and then to extract secrets across tenant boundaries. We specifically demonstrate attacks to collect potentially sensitive application data (e.g., the number of items in a shopping cart), to hijack user accounts, and to break SAML single sign-on. To the best of our knowledge, our attacks are the first granular, cross-tenant, side-channel attacks successfully demonstrated on state-of-the-art commercial clouds, PaaS or otherwise.

No abstract

Security is a major barrier to enterprise adoption of cloud computing. Physical co-residency with other tenants poses a particular risk, due to pervasive virtualization in the cloud. Recent research has shown how side channels in shared hardware may enable attackers to exfiltrate sensitive data across virtual machines (VMs). In view of such risks, cloud providers may promise physically isolated resources to select tenants, but a challenge remains: Tenants still need to be able to verify physical isolation of their VMs.We introduce HomeAlone, a system that lets a tenant verify its VMs' exclusive use of a physical machine. The key idea in HomeAlone is to invert the usual application of side channels. Rather than exploiting a side channel as a vector of attack, HomeAlone uses a side-channel (in the L2 memory cache) as a novel, defensive detection tool. By analyzing cache usage during periods in which "friendly" VMs coordinate to avoid portions of the cache, a tenant using HomeAlone can detect the activity of a co-resident "foe" VM. Key technical contributions of HomeAlone include classification techniques to analyze cache usage and guest operating system kernel modifications that minimize the performance impact of friendly VMs sidestepping monitored cache portions. HomeAlone requires no modification of existing hypervisors and no special action or cooperation by the cloud provider.