Hybrid Emulation and Hardware Fuzzing for Embedded Systems
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Solution Overview
Problem
In embedded systems, static instrumentation for fuzzing is challenging due to limited access and memory constraints, and hardware-based approaches are slow and inefficient, leading to bottlenecks in testing complex systems with closed-source components and multiple peripherals.
Innovation Solution
A hybrid fuzzing method combining emulation-based and hardware-based fuzzers, where both types of fuzzers synchronize and translate corpus files to efficiently test embedded systems, allowing real hardware operation and emulation, thereby ensuring reliable and safe operation by minimizing fuzz data and optimizing peripheral modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If static instrumentation is used for fuzzing in embedded systems, then code coverage feedback can be obtained, but it increases code size and cannot be applied to closed-source binary components
Solution Approach 1:
The patent uses QEMU emulator to create a virtual copy of the embedded system's hardware architecture, allowing software instrumentation to be applied to the emulated environment rather than the actual hardware or closed-source binaries. This copying approach enables coverage feedback without modifying the original system's code or increasing its size.
Solution Approach 2:
The QEMU emulator acts as an intermediary layer between the fuzzer and the embedded system under test. It provides a transparent emulation environment where software instrumentation can be applied to obtain coverage information, while the original closed-source binaries remain unchanged and their size is not increased.
2Reliability
If hardware-based fuzzing approaches are used, then real hardware operation can be tested, but they are slow and create bottlenecks in testing
Solution Approach 1:
The patent segments the fuzzing process into two independent parts: an emulation-based fuzzer that handles the bulk of testing work at high speed, and a hardware-based fuzzer that validates critical paths. This segmentation allows each component to operate at its optimal speed without bottlenecking the entire system.
Solution Approach 2:
The patent merges emulation-based fuzzing and hardware-based fuzzing into a unified testing framework where both approaches work together. The emulation fuzzer provides fast coverage-guided testing while the hardware fuzzer validates real hardware behavior, combining their advantages to achieve both speed and reliability.
3Measurement precision
If multiple fuzzers are used to test embedded systems, then coverage can be improved, but synchronization and corpus translation between different fuzzer types becomes complex
Solution Approach 1:
The patent designs a universal corpus format that can be understood by both emulation-based and hardware-based fuzzers. This multi-functional corpus structure allows different fuzzer types to share and synchronize test data without requiring complex translation layers, simplifying the synchronization process while maintaining comprehensive coverage.
Data Source
AI summary
A method for the automated performance of software tests for a program to be tested in an embedded system. The method includes: ascertaining, using an emulation-based fuzzer, a program behavior of the program to be tested, wherein at least one emulation-based result is derived on this basis; ascertaining, using a hardware-based fuzzer, the program behavior of the program to be tested, wherein at least one hardware-based result is derived on this basis; providing, using a monitoring component, the derived results, wherein the emulation-based result is provided to the hardware-based fuzzer, and/or the hardware-based result is provided to the emulation-based fuzzer.