Dominik Maier, Lukas Seidel (TU Berlin)

Researchers spend hours, or even days, to understand a target well enough to harness it and get a feedback-guided fuzzer running. Once this is achieved, they rely on their fuzzer to find the right paths, maybe sampling the collected queue entries to see how well it performs. Their knowledge is of little help to the fuzzer, while the fuzzer’s behavior is largely a black box to the researcher. Enter JMPscare, providing deep insight into fuzzing queues. By highlighting unreached basic blocks across all queue items during fuzzing, JMPscare allows security researchers to understand the shortcomings of their fuzzer and helps to overcome them. JMPscare can analyze thousands of queue entries efficiently and highlight interesting roadblocks, socalled frontiers. This intel helps the human-in-the-loop to improve the fuzzer, mutator, and harness. Even complex bugs, hard to reach for a generalized fuzzer, hidden deep in the control flow of the target, can be covered in this way. Apart from a purely analytical view, its convenient built-in binary patching facilitates forced execution for subsequent fuzz runs. We demonstrate the benefit of JMPscare on the ARM-based MediaTek Baseband. With JMPscare we gain an in-depth understanding of larger parts of the firmware and find new targets in this RTOS. JMPscare simplifies further mutator, fuzzer, and instrumentation development.

View More Papers

Similarity Metric Method for Binary Basic Blocks of Cross-Instruction...

Xiaochuan Zhang (Artificial Intelligence Research Center, National Innovation Institute of Defense Technology), Wenjie Sun (State Key Laboratory of Mathematical Engineering and Advanced Computing), Jianmin Pang (State Key Laboratory of Mathematical Engineering and Advanced Computing), Fudong Liu (State Key Laboratory of Mathematical Engineering and Advanced Computing), Zhen Ma (State Key Laboratory of Mathematical Engineering and Advanced…

Read More

Trim My View: An LLM-Based Code Query System for...

Sima Arasteh (University of Southern California), Pegah Jandaghi, Nicolaas Weideman (University of Southern California/Information Sciences Institute), Dennis Perepech, Mukund Raghothaman (University of Southern California), Christophe Hauser (Dartmouth College), Luis Garcia (University of Utah Kahlert School of Computing)

Read More

What Remains Uncaught?: Characterizing Sparsely Detected Malicious URLs on...

Sayak Saha Roy, Unique Karanjit, Shirin Nilizadeh (The University of Texas at Arlington)

Read More