Dairo de Ruck, Jef Jacobs, Jorn Lapon, Vincent Naessens (DistriNet, KU Leuven, 3001 Leuven, Belgium)

Debugging is a fundamental testing technique that directly interacts with the functionality and current state of a running program. It enables the debugger to step through a program and meanwhile inspect registers and memory as part of the program state. When debugging, variables and parameters are assigned concrete values resulting in a specific program path to be explored. This makes software testing time-consuming and at the same time requiring substantial expertise. On the other hand, symbolic debugging can explore multiple paths by replacing concrete input values by symbolic ones and choose the paths to be explored.
angr is a dynamic symbolic execution (DSE) platform that can be programmed to symbolically execute a binary program with selected, possibly symbolic inputs. The binary is lifted to an intermediate, architecture independent representation, preparatory to the symbolic execution. This paper presents dAngr a tool that builds upon angr, a symbolic execution platform, enabling the user to debug binaries by means of GDB-like commands, and enhances this experience by means of symbolic execution and binary analysis capabilities. We also abstract the angr framework and symbolic execution by utilizing these commands. The power of dAngr is demonstrated on multiple examples including capture-the-flag challenges with different levels of complexity.

View More Papers

Automated Expansion of Privacy Data Taxonomy for Compliant Data...

Yue Qin (Indiana University Bloomington & Central University of Finance and Economics), Yue Xiao (Indiana University Bloomington & IBM Research), Xiaojing Liao (Indiana University Bloomington)

Read More

I Know What You Asked: Prompt Leakage via KV-Cache...

Guanlong Wu (Southern University of Science and Technology), Zheng Zhang (ByteDance Inc.), Yao Zhang (ByteDance Inc.), Weili Wang (Southern University of Science and Technolog), Jianyu Niu (Southern University of Science and Technolog), Ye Wu (ByteDance Inc.), Yinqian Zhang (Southern University of Science and Technology (SUSTech))

Read More

Vision: Retiring Scenarios — Enabling Ecologically Valid Measurement in...

Oliver D. Reithmaier (Leibniz University Hannover), Thorsten Thiel (Atmina Solutions), Anne Vonderheide (Leibniz University Hannover), Markus Dürmuth (Leibniz University Hannover)

Read More

TrajDeleter: Enabling Trajectory Forgetting in Offline Reinforcement Learning Agents

Chen Gong (University of Vriginia), Kecen Li (Chinese Academy of Sciences), Jin Yao (University of Virginia), Tianhao Wang (University of Virginia)

Read More