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Artifact Submission for "Dynamic Taint Analysis versus Obfuscated Self-Checking"

To set up this project, a docker image can be built with the following command: docker build -t vsc .
The built docker image includes the updated VirtSC, a dynamic taint analysis attack on the original VirtSC, as well as scripts and files that can be useful for the evaluation of VirtSC and its attack.

To create a new container using the image, use docker run -it vsc bash.

To open the container at a later point in time again, use docker start -i [container id/name].

VirtSC

The original version of VirtSC was created by Ahmadvand et al. [1]. The initially built version in this project is VirtSC after its security update.

To mark functions in the program's source code to be virtualized or additionally checked by guards, use either __attribute__((sc_virtualize)) or __attribute__((sc_sensitive)), respectively.

The main files constituting VirtSC can be found in /home/sip/sc-virt/src/lib/Transforms/ScVirt.

The following example shows how to protect and compile a C++ program using VirtSC. Here, main.cpp would contain the source code, and the resulting binary file would be main.out:

/home/sip/built-sc-virt/bin/clang++ -c -emit-llvm main.cpp -o main.bc
/home/sip/built-sc-virt/bin/opt -reg2mem < main.bc > prep.bc
/home/sip/built-sc-virt/bin/opt -load LLVMScVirt.so -scvirt -connectivity=5 < prep.bc > out.bc
/home/sip/built-sc-virt/bin/clang++ -o main.out out.bc

The connectivity parameter determines the maximum number of guards for each sensitive function. To disassemble the protected LLVM output, use the following command and open out.ll with a text editor:

/home/sip/built-sc-virt/bin/llvm-dis -o out.ll out.bc

More information can be found in VirtSC's original README.

Dynamic Taint Analysis Attack on VirtSC

This section refers to the content of the directory /home/sip/attacking_anti_tamper.

For the attack, some of the files for Guggenmos' master's thesis [2] were used. The original project can be found here.

To attack a protected binary, use run.py.

  • Example usage: ./run.py evaluation/binaries_old_tampered/sha.out -o sha_data.txt --args="/home/sip/attacking_anti_tamper/evaluation/dataset/cmdline-args/sha_input_small.asc"
  • More command line arguments are available. However, it cannot be guaranteed that they work as intended, as they have not been used after modifying Guggenmos' code.
  • The script uses code that has been compiled from the directories tracer and taint_cpp. The original attack's README contains more details on how to build and use the individual components.

Evaluation

This section refers to the content of the directory /home/sip/attacking_anti_tamper/evaluation.

Dataset

The following folders constitute the dataset:

  • VirtSC_*: The files that have to be replaced before recompiling to change the version of VirtSC.
  • dataset: The unprotected dataset of programs including any predefined input and which libraries have to be linked to.
    Side note: The current command-line input for susan is not recognized by the program. The last token would have to be changed from s to -s.
  • binaries_*: The dataset of programs protected by different versions of VirtSC, which was used for the evaluation in Valenzuela's bachelor's thesis [3].

Scripts

  • To create all binaries of the dataset using different VirtSC versions, use create_all_binaries.sh. As all options are covered here, no command-line flags are necessary. The script uses the following other scripts:
    • build_virtsc_version.sh builds a specific version of VirtSC.
    • compile_dataset.sh compiles the dataset of programs using the current version of VirtSC. It uses the script protect.sh which protects a single program of the dataset.
  • To attack an entire version of VirtSC, use attack_virtsc_version.sh.
    • Example usage: ./attack_virtsc_version.sh binaries_old_tampered
    • The script creates a directory with all attack data gathered by run.py in the directory attack_data. Already present data will not be collected again.
  • To generate graphs for the time needed and the number of skipped instructions for each attack given the set of data generated by run.py, use generate_attack_figure_time.py and generate_attack_figure_skipped.py, respectively.
    • Example usage for time needed: ./generate_attack_figure_time.py -i attack_data/old_tampered -o figures
    • Example usage for skipped instructions: ./generate_attack_figure_skipped.py -i attack_data/old_tampered -o figures
  • To generate charts comparing the execution time and file size of a set of programs protected by two versions of VirtSC, use compare_time.py and compare_size.py, respectively.
    • Before executing compare_time.py, the execution has to be timed using time_execution.py.
    • Example usage for execution time:
      ./time_execution.py --old binaries_old_dummy_check --new binaries_new_dummy_check -o execution_times.txt
      ./compare_time.py -i execution_times.txt -o figures
    • Example usage for file size: ./compare_size.py --old binaries_old_dummy_check --new binaries_new_dummy_check -o figures
  • To print a LaTeX table with an entire set of data generated by run.py, use print_latex_table.py.
    • Example usage: ./print_latex_table.py -i attack_data/old_tampered
  • To print a list of specific values that can be used to compute an average value, among others, use the other scripts with the prefix print_.
    • Example usage for attack data: ./print_value_lists.py -i attack_data/old_tampered
    • Example usage for execution time:
      ./time_execution.py --old binaries_old_dummy_check --new binaries_new_dummy_check -o execution_times.txt
      ./print_overhead_list_time.py -i execution_times.txt
    • Example usage for file size: ./print_overhead_list_size.py --old binaries_old_dummy_check --new binaries_new_dummy_check

Bibliography

[1] M. Ahmadvand, D. Below, S. Banescu, and A. Pretschner. “VirtSC: Combining Virtualization Obfuscation with Self-Checksumming”. In: Proceedings of the 3rd ACM Workshop on Software Protection. 2019, pp. 53–63.

[2] M. Guggenmos. “Software Protection and Taint-based Attacks”. MA thesis. Technical University of Munich, 2020.

[3] S. Valenzuela. “Making Self-Checksumming Combined with Virtualization Obfuscation Resistant against Attacks”. BA thesis. Technical University of Munich, 2020.

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