VirtSC: Combining Virtualization Obfuscation with Self-Checksumming

Self-checksumming (SC) is a tamper-proofing technique that ensures certain program segments (code) in memory hash to known values at runtime. SC has few restrictions on application and hence can protect a vast majority of programs. The code verification in SC requires computation of the expected hashes after compilation, as the machine-code is not known before. This means the expected hash values need to be adjusted in the binary executable, hence combining SC with other protections is limited due to this adjustment step. However, obfuscation protections are often necessary, as SC protections can be otherwise easily detected and disabled via pattern matching. In this paper, we present a layered protection using virtualization obfuscation, yielding an architecture-agnostic SC protection that requires no post-compilation adjustment. We evaluate the performance of our scheme using a dataset of 25 real-world programs (MiBench and 3 CLI games). Our results show that the SC scheme induces an average overhead of 43% for a complete protection (100% coverage). The overhead is tolerable for less CPU-intensive programs (e.g. games) and when only parts of programs (e.g. license checking) are protected. However, large overheads stemming from the virtualization obfuscation were encountered

Leveraging WebAssembly for Numerical JavaScript Code Virtualization

Code obfuscation built upon code virtualization technology is one of the viable means for protecting sensitive algorithms and data against code reverse engineering attacks. Code virtualization has been successfully applied to programming languages like C, C++, and Java. However, it remains an outstanding challenge to apply this promising technique to JavaScript, a popular web programming language. This is primarily due to the open visibility of JavaScript code and the expensive runtime overhead associated with code virtualization. This paper presents JSPro , a novel code virtualization system for JavaScript. JSPro is the first JavaScript code obfuscation tool that builds upon the emerging WebAssembly language standard. It is designed to provide more secure code protection but without incurring a significant runtime penalty, explicitly targeting numerical JavaScript kernels. We achieve this by first automatically translating the target JavaScript code into WebAssembly and then performing code obfuscation on the compiled WebAssembly binary. Our design has two advantages over existing solutions: (1) it increases the code reverse entering complexity by implementing code obfuscation at a lower binary level and (2) it significantly reduces the performance impact of code virtualization over the native JavaScript code by using the performance-tuned WebAssembly language. We evaluate JSPro on a set of numerical JavaScript algorithms widely used in many applications. To test the performance, we apply JSPro to four mainstream web browsers running on three distinct mobile devices. Compared to state-of-the-art JavaScript obfuscation tools, JSPro not only provides stronger protection but also reduces the runtime overhead by at least 15% (up to 38.2%) and the code size by 28.2% on average

Code obfuscation against abstraction refinement attacks

Code protection technologies require anti reverse engineering transformations to obfuscate programs in such a way that tools and methods for program analysis become ineffective. We introduce the concept of model deformation inducing an effective code obfuscation against attacks performed by abstract model checking. This means complicating the model in such a way a high number of spurious traces are generated in any formal verification of the property to disclose about the system under attack.We transform the program model in order to make the removal of spurious counterexamples by abstraction refinement maximally inefficient. Because our approach is intended to defeat the fundamental abstraction refinement strategy, we are independent from the specific attack carried out by abstract model checking. A measure of the quality of the obfuscation obtained by model deformation is given together with a corresponding best obfuscation strategy for abstract model checking based on partition refinement

Protecting Software through Obfuscation:Can It Keep Pace with Progress in Code Analysis?

Software obfuscation has always been a controversially discussed research area. While theoretical results indicate that provably secure obfuscation in general is impossible, its widespread application in malware and commercial software shows that it is nevertheless popular in practice. Still, it remains largely unexplored to what extent today’s software obfuscations keep up with state-of-the-art code analysis and where we stand in the arms race between software developers and code analysts. The main goal of this survey is to analyze the effectiveness of different classes of software obfuscation against the continuously improving deobfuscation techniques and off-the-shelf code analysis tools. The answer very much depends on the goals of the analyst and the available resources. On the one hand, many forms of lightweight static analysis have difficulties with even basic obfuscation schemes, which explains the unbroken popularity of obfuscation among malware writers. On the other hand, more expensive analysis techniques, in particular when used interactively by a human analyst, can easily defeat many obfuscations. As a result, software obfuscation for the purpose of intellectual property protection remains highly challenging.</jats:p

The Effect of Code Obfuscation on Authorship Attribution of Binary Computer Files

In many forensic investigations, questions linger regarding the identity of the authors of the software specimen. Research has identified methods for the attribution of binary files that have not been obfuscated, but a significant percentage of malicious software has been obfuscated in an effort to hide both the details of its origin and its true intent. Little research has been done around analyzing obfuscated code for attribution. In part, the reason for this gap in the research is that deobfuscation of an unknown program is a challenging task. Further, the additional transformation of the executable file introduced by the obfuscator modifies or removes features from the original executable that would have been used in the author attribution process. Existing research has demonstrated good success in attributing the authorship of an executable file of unknown provenance using methods based on static analysis of the specimen file. With the addition of file obfuscation, static analysis of files becomes difficult, time consuming, and in some cases, may lead to inaccurate findings. This paper presents a novel process for authorship attribution using dynamic analysis methods. A software emulated system was fully instrumented to become a test harness for a specimen of unknown provenance, allowing for supervised control, monitoring, and trace data collection during execution. This trace data was used as input into a supervised machine learning algorithm trained to identify stylometric differences in the specimen under test and provide predictions on who wrote the specimen. The specimen files were also analyzed for authorship using static analysis methods to compare prediction accuracies with prediction accuracies gathered from this new, dynamic analysis based method. Experiments indicate that this new method can provide better accuracy of author attribution for files of unknown provenance, especially in the case where the specimen file has been obfuscated

Evaluation Methodologies in Software Protection Research

Man-at-the-end (MATE) attackers have full control over the system on which the attacked software runs, and try to break the confidentiality or integrity of assets embedded in the software. Both companies and malware authors want to prevent such attacks. This has driven an arms race between attackers and defenders, resulting in a plethora of different protection and analysis methods. However, it remains difficult to measure the strength of protections because MATE attackers can reach their goals in many different ways and a universally accepted evaluation methodology does not exist. This survey systematically reviews the evaluation methodologies of papers on obfuscation, a major class of protections against MATE attacks. For 572 papers, we collected 113 aspects of their evaluation methodologies, ranging from sample set types and sizes, over sample treatment, to performed measurements. We provide detailed insights into how the academic state of the art evaluates both the protections and analyses thereon. In summary, there is a clear need for better evaluation methodologies. We identify nine challenges for software protection evaluations, which represent threats to the validity, reproducibility, and interpretation of research results in the context of MATE attacks

Towards Static Analysis of Virtualization-Obfuscated Binaries

Virtualization-obfuscation protects a program from manual or automated analysis by compiling it into bytecode for a randomized virtual architecture and attaching a corresponding interpreter. Static analysis appears to be helpless on such programs, where only the code of the interpreter is directly visible. In this paper, we explain the particular challenges for statically analyzing the combination of interpreter and bytecode. Static analysis for computing possible variable values is commonly precise only to the program location. In the interpreter loop, however, this combines unrelated data flow information from different locations of the bytecode program. To avoid this loss of information, we show how to lift an existing static analysis to an additional dimension of location, to become sensitive to the value of the virtual program counter. Thus, the static analysis merges data flow from equal bytecode locations only. We lift an existing analysis implemented in the JAKSTAB static analyzer and present preliminary results for processing a virtualization-obfuscated binary. 1