Customers with security-critical data processing needs are beginning to push back strongly against using cloud computing. Cloud vendors run their computations upon cloud provided VM systems, but customers are worried such host systems may not be able to protect themselves from attack, ensure isolation of customer processing, or load customer processing correctly. To provide assurance of data processing protection in clouds to customers, we advocate methods to improve cloud transparency using hardware-based attestation mechanisms. We find that the centralized management of cloud data centers is ideal for attestation frameworks, enabling the development of a practical approach for customers to trust in the cloud platform. Specifically, we propose a cloud verifier service that generates integrity proofs for customers to verify the integrity and access control enforcement abilities of the cloud platform that protect the integrity of customer's application VMs in IaaS clouds. While a cloud-wide verifier service could present a significant system bottleneck, we demonstrate that aggregating proofs enables significant overhead reductions. As a result, transparency of data security protection can be verified at cloud-scale.

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Coverage-guided fuzz testing has gained prominence as a highly effective method of finding security vulnerabilities such as buffer overflows in programs that parse binary data. Recently, researchers have introduced various specializations to the coverage-guided fuzzing algorithm for different domain-specific testing goals, such as finding performance bottlenecks, generating valid inputs, handling magic-byte comparisons, etc. Each such solution can require non-trivial implementation effort and produces a distinct variant of a fuzzing tool. We observe that many of these domain-specific solutions follow a common solution pattern. In this paper, we present FuzzFactory, a framework for developing domain-specific fuzzing applications without requiring changes to mutation and search heuristics. FuzzFactory allows users to specify the collection of dynamic domain-specific feedback during test execution, as well as how such feedback should be aggregated. FuzzFactory uses this information to selectively save intermediate inputs, called waypoints, to augment coverage-guided fuzzing. Such waypoints always make progress towards domain-specific multi-dimensional objectives. We instantiate six domain-specific fuzzing applications using FuzzFactory: three re-implementations of prior work and three novel solutions, and evaluate their effectiveness on benchmarks from Google's fuzzer test suite. We also show how multiple domains can be composed to perform better than the sum of their parts. For example, we combine domain-specific feedback about strict equality comparisons and dynamic memory allocations, to enable the automatic generation of LZ4 bombs and PNG bombs. CCS Concepts: • Software and its engineering → Software testing and debugging.

Abstract-Cloud computing has commoditized compute, storage, and networking resources creating an on-demand utility. Despite the attractiveness of this new paradigm, its adoption has been stymied by cloud platform's lack of transparency, which leaves customers unsure if their sensitive data and computation can be entrusted to the cloud. While techniques like encryption can protect customers' data at rest, clouds still lack mechanisms for customers to verify that their computations are being executed as expected, a guarantee one could obtain if they were running the computation in their own data center.In this paper, we present the cloud verifier (CV), a flexible framework that cloud vendors can configure to provide cloud monitoring services for customers to validate that their computations are configured and being run as expected in Infrastructure as a Service (IaaS) clouds. The CV builds a chain of trust from the customer to their hosted virtual machine (VM) instances through the cloud platform, enabling it to check customer-specified requirements against a comprehensive view of both the VM's load-time and run-time properties. In addition, the CV enables cloud vendors to provide more responsive remediation techniques than traditional attestation mechanisms. We built a proof of concept CV for the OpenStack cloud platform whose evaluation demonstrates that a single CV enables over 20,000 simultaneous customers to verify numerous properties with little impact on cloud application performance. As a result, the CV gives cloud customers a low-overhead method for assuring that their instances are running according to their requirements.

Abstract. Users are increasingly turning to online services, but are concerned for the safety of their personal data and critical business tasks. While secure communication protocols like TLS authenticate and protect connections to these services, they cannot guarantee the correctness of the endpoint system. Users would like assurance that all the remote data they receive is from systems that satisfy the users' integrity requirements. Hardware-based integrity measurement (IM) protocols have long promised such guarantees, but have failed to deliver them in practice. Their reliance on non-performant devices to generate timely attestations and ad hoc measurement frameworks limits the efficiency and completeness of remote integrity verification. In this paper, we introduce the integrity verification proxy (IVP), a service that enforces integrity requirements over connections to remote systems. The IVP monitors changes to the unmodified system and immediately terminates connections to clients whose specific integrity requirements are not satisfied while eliminating the attestation reporting bottleneck imposed by current IM protocols. We implemented a proof-of-concept IVP that detects several classes of integrity violations on a Linux KVM system, while imposing less than 1.5% overhead on two application benchmarks and no more than 8% on I/O-bound micro-benchmarks.

Modern distributed systems are composed from several offthe-shelf components, including operating systems, virtualization infrastructure, and application packages, upon which some custom application software (e.g., web application) is often deployed. While several commodity systems now include mandatory access control (MAC) enforcement to protect the individual components, the complexity of such MAC policies and the myriad of possible interactions among individual hosts in distributed systems makes it difficult to identify the attack paths available to adversaries. As a result, security practitioners react to vulnerabilities as adversaries uncover them, rather than proactively protecting the system's data integrity. In this paper, we develop a mostly-automated method to transform a set of commodity MAC policies into a system-wide policy that proactively protects system integrity, approximating the Clark-Wilson integrity model. The method uses the insights from the Clark-Wilson model, which requires integrity verification of security-critical data and mediation at program entrypoints, to extend existing MAC policies with the proactive mediation necessary to protect system integrity. We demonstrate the practicality of producing Clark-Wilson policies for distributed systems on a web application running on virtualized Ubuntu SELinux hosts, where our method finds: (1) that only 27 additional entrypoint mediators are sufficient to mediate the threats of remote adversaries over the entire distributed system and (2) and only 20 additional local threats require mediation to approximate Clark-Wilson integrity comprehensively. As a result, available security policies can be used as a foundation for proactive integrity protection from both local and remote threats.

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