Gorka Irazoqui

S

The cloud computing infrastructure relies on virtualized servers that provide isolation across guest OSs through sand boxing. This isolation was demonstrated to be imperfect in past work which exploited hardware level information leakages to gain access to sensitive information across co-located virtual machines (VMs). In response virtualization companies and cloud services providers have disabled features such as deduplication to prevent such attacks. In this work, we introduce a fine-grain cross-core cache attack that exploits access time variations on the last level cache. The attack exploits huge pages to work across VM boundaries without requiring deduplication. No configuration changes on the victim OS are needed, making the attack quite viable. Furthermore, only machine co-location is required, while the target and victim OS can still reside on different cores of the machine. Our new attack is a variation of the prime and probe cache attack whose applicability at the time is limited to L1 cache. In contrast, our attack works in the spirit of the flush and reload attack targeting the shared L3 cache instead. Indeed, by adjusting the huge page size our attack can be customized to work virtually at any cache level/size. We demonstrate the viability of the attack by targeting an Open SSL1.0.1f implementation of AES. The attack recovers AES keys in the cross-VM setting on Xen 4.1 with deduplication disabled, being only slightly less efficient than the flush and reload attack. Given that huge pages are a standard feature enabled in the memory management unit of OSs and that besides co-location no additional assumptions are needed, the attack we present poses a significant risk to existing cloud servers.

A: A Shared Cache Attack That Works across Cores and Defies VM Sandboxing -- and Its Application to AES

In this work we show how the Lucky 13 attack can be resurrected in the cloud by gaining access to a virtual machine co-located with the target. Our version of the attack exploits distinguishable cache access times enabled by VM deduplication to detect dummy function calls that only happen in case of an incorrectly CBC-padded TLS packet. Thereby, we gain back a new covert channel not considered in the original paper that enables the Lucky 13 attack. In fact, the new side channel is significantly more accurate, thus yielding a much more effective attack. We briefly survey prominent cryptographic libraries for this vulnerability. The attack currently succeeds to compromise PolarSSL, GnuTLS and CyaSSL on deduplication enabled platforms while the Lucky 13 patches in OpenSSL, Mozilla NSS and MatrixSSL are immune to this vulnerability. We conclude that, any program that follows secret data dependent execution flow is exploitable by side-channel attacks as shown in (but not limited to) our version of the Lucky 13 attack.

Lucky 13 Strikes Back

Cloud services keep gaining popularity despite the security concerns. While non-sensitive data is easily trusted to cloud, security critical data and applications are not. The main concern with the cloud is the shared resources like the CPU, memory and even the network adapter that provide subtle side-channels to malicious parties. We argue that these side-channels indeed leak fine grained, sensitive information and enable key recovery attacks on the cloud. Even further, as a quick scan in one of the Amazon EC2 regions shows, high percentage – 55 % – of users run outdated, leakage prone libraries leaving them vulnerable to mass surveillance.

Cache Attacks Enable Bulk Key Recovery on the Cloud

Multi-processor systems are becoming the de-facto standard across different computing domains, ranging from high-end multi-tenant cloud servers to low-power mobile platforms. The denser integration of CPUs creates an opportunity for great economic savings achieved by packing processes of multiple tenants or by bundling all kinds of tasks at various privilege levels to share the same platform. This level of sharing carries with it a serious risk of leaking sensitive information through the shared microarchitectural components. Microarchitectural attacks initially only exploited core-private resources, but were quickly generalized to resources shared within the CPU. We present the first fine grain side channel attack that works across processors. The attack does not require CPU co-location of the attacker and the victim. The novelty of the proposed work is that, for the first time the directory protocol of high efficiency CPU interconnects is targeted. The directory protocol is common to all modern multi-CPU systems. Examples include AMDs HyperTransport, Intels Quickpath, and ARMs AMBA Coherent Interconnect. The proposed attack does not rely on any specific characteristic of the cache hierarchy, e.g. inclusiveness. Note that inclusiveness was assumed in all earlier works. Furthermore, the viability of the proposed covert channel is demonstrated with two new attacks: by recovering a full AES key in OpenSSL, and a full ElGamal key in libgcrypt within the range of seconds on a shared AMD Opteron server.

Cross Processor Cache Attacks

Abstract Software updates and security patches have become a standard method to fix known and recently discovered security vulnerabilities in deployed software. In server applications, outdated cryptographic libraries allow adversaries to exploit weaknesses and launch attacks with significant security results. The proposed technique exploits leakages at the hardware level to first, determine if a specific cryptographic library is running inside (or not) a co-located virtual machine (VM) and second to discover the IP of the co-located target. To this end, we use a Flush+Reload cache side-channel technique to measure the time it takes to call (load) a cryptographic library function. Shorter loading times are indicative of the library already residing in memory and shared by the VM manager through deduplication. We demonstrate the viability of the proposed technique by detecting and distinguishing various cryptographic libraries, including MatrixSSL, PolarSSL, GnuTLS, OpenSSL and CyaSSL along with the IP of the VM running these libraries. In addition, we show how to differentiate between various versions of libraries to better select an attack target as well as the applicable exploit. Our experiments show a complete attack setup scenario with single-trial success rates of up to 90% under light load and up to 50% under heavy load for libraries running in KVM.

Know Thy Neighbor: Crypto Library Detection in Cloud

Clouds unrivaled cost effectiveness and on the fly operation versatility is attractive to enterprise and personal users. However, the cloud inherits a dangerous behavior from virtualization systems that poses a serious security risk: resource sharing. This work exploits a shared resource optimization technique called memory deduplication to mount a powerful known-ciphertext only cache side-channel attack on a popular OpenSSL implementation of AES. In contrast to the other cross-VM cache attacks, our attack does not require synchronization with the target server and is fully asynchronous, working in a more realistic scenario with much weaker assumption. Also, our attack succeeds in just 15 seconds working across cores in the cross-VM setting. Our results show that there is strong information leakage through cache in virtualized systems and the memory deduplication should be approached with caution.

A Faster and More Realistic Flush+Reload Attack on AES

In modern computing environments, hardware resources are commonly shared, and parallel computation is widely used. Parallel tasks can cause privacy and security problems if proper isolation is not enforced. Intel proposed SGX to create a trusted execution environment within the processor. SGX relies on the hardware, and claims runtime protection even if the OS and other software components are malicious. However, SGX disregards side-channel attacks. We introduce a powerful cache side-channel attack that provides system adversaries a high resolution channel. Our attack tool named CacheZoom is able to virtually track all memory accesses of SGX enclaves with high spatial and temporal precision. As proof of concept, we demonstrate AES key recovery attacks on commonly used implementations including those that were believed to be resistant in previous scenarios. Our results show that SGX cannot protect critical data sensitive computations, and efficient AES key recovery is possible in a practical environment. In contrast to previous works which require hundreds of measurements, this is the first cache side-channel attack on a real system that can recover AES keys with a minimal number of measurements. We can successfully recover AES keys from T-Table based implementations with as few as ten measurements.

CacheZoom: How SGX Amplifies the Power of Cache Attacks

Dividing last level caches into slices is a popular method to prevent memory accesses from becoming a bottleneck on modern multicore processors. In order to assess and understand the benefits of cache slicing in detail, a precise knowledge of implementation details such as the slice selection algorithm are of high importance. However, slice selection methods are mostly unstudied, and processor manufacturers choose not to publish their designs, nor their design rationale. In this paper, we present a tool that allows to recover the slice selection algorithm for Intel processors. The tool uses cache access information to derive equations that allow the reconstruction of the applied slice selection algorithm. Thereby, the tool enables further exploration of the behavior of modern caches. The tool is successfully applied to a range of Intel CPUs with different slices and architectures. Results show that slice selection algorithms have become more complex over time by involving an increasing number of bits of the physical address. We also demonstrate that among the most recent processors, the slice selection algorithm depends on the number of CPU cores rather than the processor model.

Systematic Reverse Engineering of Cache Slice Selection in Intel Processors

This work exposes vulnerabilities in virtualized cloud servers by mounting Cross-VM cache attacks in Xen and VMware VMs. We show for the first time that AES implementations in a number popular cryptographic libraries including Open SSL, Polar SSL and Libgcrypt have non-constant execution times and are vulnerable to Bernsteins correlation attack when run in Xen and VMware (bare metal version) VMs. We show that the vulnerability persists even if the VMs are running on different cores in the same machine. Experiments on Amazon EC2 and Google Compute Engine highlight the practical implications of the found vulnerability. The results of this study show that there remains a security risk to AES implementations of popular libraries and data encrypted under AES on popular cloud services.

Fine Grain Cross-VM Attacks on Xen and VMware

Cache based attacks can overcome software-level isolation techniques to recover cryptographic keys across VMboundaries. Therefore, cache attacks are believed to pose a serious threat to public clouds. In this work, we investigate the effectiveness of cache attacks in such scenarios. Specifically, we apply the Flush+Reload and Prime+Probe methods to mount cache side-channel attacks on a popular OpenSSL implementation of AES. The attacks work across cores in the cross-VM setting and succeeds to recover the full encryption keys in a short time-suggesting a practical threat to real-life systems. Our results show that there is strong information leakage through cache in virtualized systems and the software implementations of AES must be approached with caution. Indeed, for the first time, we demonstrate the effectiveness of the attack across co-located instances on the Amazon EC2 cloud. We argue that for secure usage of worlds most commonly used block cipher such as AES, one should rely on secure, constanttime hardware implementations offered by CPU vendors.