DECAF

DECAF (short for Dynamic Executable Code Analysis Framework) is a binary analysis platform based on QEMU.

DECAF++

DECAF++, the new version of DECAF, taint analysis is around 2X faster making it the fastest, to the best of our knowledge, whole-system dynamic taint analysis framework. This results in a much better usability imposing only 4% overhead (SPEC CPU2006) when no suspicious (tainted) input exists. Even under heavy taint analysis workloads, DECAF++ has a much better performance, around 25% faster on nbench, because of its elasticity. DECAF++ elasticity makes it a very suitable case for security analysis tasks that would selectively analyze the input e.g. Intrusion Detection Systems (IDS) that can filter out benign traffic. For further technical details, see our RAID 2019 paper. To activate the optimizations, see our DECAF++ wiki page.

PUBLICATIONS

1. Ali Davanian, Zhenxiao Qi, Yu Qu, and Heng Yin, DECAF++: Elastic Whole-System Dynamic Taint Analysis, In the 22nd International Symposium on Research in Attacks, Intrusions and Defenses (RAID), September 2019. (If you wish to cite the new optimized version of DECAF, please cite this paper)

2. "Make it work, make it right, make it fast: building a platform-neutral whole-system dynamic binary analysis platform", Andrew Henderson, Aravind Prakash, Lok Kwong Yan, Xunchao Hu, Xujiewen Wang, Rundong Zhou, and Heng Yin, to appear in the International Symposium on Software Testing and Analysis (ISSTA'14), San Jose, CA, July 2014.(If you wish to cite DECAF, please cite this paper)

3. Lok Kwong Yan, Andrew Henderson, Xunchao Hu, Heng Yin, and Stephen McCamant?.On soundness and precision of dynamic taint analysis. Technical Report SYR-EECS-2014-04, Syracuse University, January 2014.

4. DroidScope: Seamlessly Reconstructing OS and Dalvik Semantic Views for Dynamic Android Malware Analysis", Lok-Kwong Yan and Heng Yin, in the 21st USENIX Security Symposium, Bellevue, WA, August 8-10, 2012.

Select Academic Systems Using DECAF

1. Luo, L., Fu, Y., Wu, D., Zhu, S., & Liu, P. (2016, June). Repackage-proofing android apps. In 2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) (pp. 550-561). IEEE.

2. Wei, J., Yan, L. K., & Hakim, M. A. (2015, December). Mose: Live migration based on-the-fly software emulation. In Proceedings of the 31st Annual Computer Security Applications Conference (ACSAC) (pp. 221-230).

3. Carmony, C., Hu, X., Yin, H., Bhaskar, A.V., & Zhang, M. (2016). Extract Me If You Can: Abusing PDF Parsers in Malware Detectors. In Proceedings of 2016 Network and Distributed System Security Symposium (NDSS).

4. Feng, Q., Prakash, A., Yin, H., & Lin, Z. (2014, December). Mace: High-coverage and robust memory analysis for commodity operating systems. In Proceedings of the 30th annual computer security applications conference (pp. 196-205)

5. Alwabel, A., Shi, H., Bartlett, G., & Mirkovic, J. (2014). Safe and automated live malware experimentation on public testbeds. In 7th Workshop on Cyber Security Experimentation and Test (CSET'14).

Introduction

DECAF (Dynamic Executable Code Analysis Framework) is the successor to the binary analysis techniques developed for TEMU (dynamic analysis component of BitBlaze ) as part of Heng Yin's work on BitBlaze project headed up by Dawn Song. DECAF builds upon TEMU. We appreciate all that worked with us on that project.

Fig 1 the overall architecture of DECAF

Fig 1 illustrates the overall architecture of DECAF. DECAF is a platform-agnostic whole-system dynamic binary analysis framework. It provides the following key features.

Right-on-Time Virtual Machine Introspection

Different with TEMU, DECAF doesn’t use guest driver to retrieve os-level semantics. The VMI component of DECAF is able to reconstruct a fresh OS-level view of the virtual machine, including processes, threads, code modules, and symbols to support binary analysis. Further, in order to support multiple architectures and operating systems, it follows as a platform-agnostic design. The workflow for extracting OS-level semantic information is common across multiple architectures and operating systems. The only platform- specific handling lies in what kernel data structures and what fields to extract information from.

Support for Multiple Platforms

Ideally, we would like to have the same analysis code (with minimum platform-specific code) to work for different CPU architectures (e.g, x86 and ARM) and different operating systems (e.g., Windows and Linux). It requires that the analysis framework hide the architecture and operating system specific details from the analysis plugins. Further, to make the analysis framework itself maintainable and extensible to new architectures and operat-ing systems, the platform-specific code within the framework should also be minimized. DECAF can provide support for both multiple architectures and multiple operating systems. Currently, DECAF supports 32 bit Windows xp/Windows 7/linux and X86/arm.

Precise and Lossless Tainting

DECAF ensures precise tainting by maintaining bit-level precision for CPU registers and memory, and inlining precise tainting rules in the translated code blocks. Thus, the taint status for each CPU register and memory location is processed and updated synchronously during the code execution of the virtual machine. The propagation of taint labels is done in an asynchronous manner . By implementing such a tainting logic mainly in the intermediate representation level (more concretely, TCG IR level), it becomes easy to extend tainting support to a new CPU architecture.

Event-driven programming interfaces

DECAF provides an event-driven programming interface. It means that the paradigm of ”instrument” in the translation phase and then analyze in the execution phase” is invisible to the analysis plugins. The analysis plugins only need to register for interested events and implement corresponding event handling functions. The details of code instrumentation are taken care of by the framework.

Dynamic instrumentation management

To reduce runtime overhead, the instrumentation code is inserted into the translated code only when necessary. For example, when a plugin registers a function hook at a function’s entry point, the instrumentation code for this hook is only placed at the function entry point. When the plugin unregisters this function hook, the instrumentation code will also be removed from the translated code accordingly. To ease the development of plugins, the management of dynamic code instrumentation is completely taken care of in the framework, and thus invisible to the plugins.

Help Documents

Please refer to our wiki page for help documents.