arXiv subjects

Guy Farrelly

Publications and source records attributed to Guy Farrelly.

6 recordsLinked to original sources

arXiv2026

InSPECtor: Improving SLEIGH Processor Specification Veracity via Proxy

Processor specifications underpin critical security and program- analysis tools such as disassemblers, decompilers, and emulators, yet, their correctness is rarely examined. Errors in specifications distort program behaviour, obscure vulnerabilities, and enable analysis-evasion techniques. Validating processor specifications is a non-trivial task. Our study is a significant undertaking to enable, for the first time, the systematic validation of open-source SLEIGH language specifications, predominantly used by Ghidra. We design and implement a testing framework based on an automated oracle validation strategy by proxy. Our approach leverages the structure encoded in a specification itself to enumerate decodable instruction forms and generate targeted initial states. Then differentially test the successful decoding and emulation of those instructions by comparing emulators exercising the processor specification against hardware references. Applying InSPECtor across diverse, open-source specifications---x86-64, AArch64, ARM/Thumb, RISC-V, MSP430---embedding differences in specification styles, author preferences, and instruction set architecture designs, we uncovered over 38,920 discrepancies that led to 125 unique bugs with proposed fixes, identifying decoding and semantic defects as well as cross-vendor inconsistencies. We distill our findings into 8 concrete recommendations to drive future improvements. Our work underscores the importance of specification correctness and provides a practical tool to substantially improve the fidelity of SLEIGH processor specifications, strengthening the reliability of downstream security and analysis tools.

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arXiv2026

DyMA-Fuzz: Dynamic Direct Memory Access Abstraction for Re-hosted Monolithic Firmware Fuzzing

The rise of smart devices in critical domains--including automotive, medical, industrial--demands robust firmware testing. Fuzzing firmware in re-hosted environments is a promising method for automated testing at scale, but remains difficult due to the tight coupling of code with a microcontroller's peripherals. Existing fuzzing frameworks primarily address input challenges in providing inputs for Memory-Mapped I/O or interrupts, but largely overlook Direct Memory Access (DMA), a key high-throughput interface used that bypasses the CPU. We introduce DyMA-Fuzz to extend recent advances in stream-based fuzz input injection to DMA-driven interfaces in re-hosted environments. It tackles key challenges--vendor-specific descriptors, heterogeneous DMA designs, and varying descriptor locations--using runtime analysis techniques to infer DMA memory access patterns and automatically inject fuzzing data into target buffers, without manual configuration or datasheets. Evaluated on 94 firmware samples and 8 DMA-guarded CVE benchmarks, DyMA-Fuzz reveals vulnerabilities and execution paths missed by state-of-the-art tools and achieves up to 122% higher code coverage. These results highlight DyMA-Fuzz as a practical and effective advancement in automated firmware testing and a scalable solution for fuzzing complex embedded systems.

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arXiv2026

FirmReBugger: A Benchmark Framework for Monolithic Firmware Fuzzers

Monolithic Firmware is widespread. Unsurprisingly, fuzz testing firmware is an active research field with new advances addressing the unique challenges in the domain. However, understanding and evaluating improvements by deriving metrics such as code coverage and unique crashes are problematic, leading to a desire for a reliable bug-based benchmark. To address the need, we design and build FirmReBugger, a holistic framework for fairly assessing monolithic firmware fuzzers with a realistic, diverse, bug-based benchmark. FirmReBugger proposes using bug oracles--C syntax expressions of bug descriptors--with an interpreter to automate analysis and accurately report on bugs discovered, discriminating between states of detected, triggered, reached and not reached. Importantly, our idea of benchmarking does not modify the target binary and simply replays fuzzing seeds to isolate the benchmark implementation from the fuzzer while providing a simple means to extend with new bug oracles. Further, analyzing fuzzing roadblocks, we created FirmBench, a set of diverse, real-world binary targets with 313 software bug oracles. Incorporating our analysis of roadblocks challenging monolithic firmware fuzzing, the bench provides for rapid evaluation of future advances. We implement FirmReBugger in a FuzzBench-for-Firmware type service and use FirmBench to evaluate 9 state-of-the art monolithic firmware fuzzers in the style of a reproducibility study, using a 10 CPU-year effort, to report our findings.

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arXiv2025

An Automated Blackbox Noncompliance Checker for QUIC Server Implementations

We develop QUICtester, an automated approach for uncovering non-compliant behaviors in the ratified QUIC protocol implementations (RFC 9000/9001). QUICtester leverages active automata learning to abstract the behavior of a QUIC implementation into a finite state machine (FSM) representation. Unlike prior noncompliance checking methods, to help uncover state dependencies on event timing, QUICtester introduces the idea of state learning with event timing variations, adopting both valid and invalid input configurations, and combinations of security and transport layer parameters during learning. We use pairwise differential analysis of learned behaviour models of tested QUIC implementations to identify non-compliance instances as behaviour deviations in a property-agnostic way. This exploits the existence of the many different QUIC implementations, removing the need for validated, formal models. The diverse implementations act as cross-checking test oracles to discover non-compliance. We used QUICtester to analyze analyze 186 learned models from 19 QUIC implementations under the five security settings and discovered 55 implementation errors. Significantly, the tool uncovered a QUIC specification ambiguity resulting in an easily exploitable DoS vulnerability, led to 5 CVE assignments from developers, and two bug bounties thus far.

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arXiv2023

SplITS: Split Input-to-State Mapping for Effective Firmware Fuzzing

Ability to test firmware on embedded devices is critical to discovering vulnerabilities prior to their adversarial exploitation. State-of-the-art automated testing methods rehost firmware in emulators and attempt to facilitate inputs from a diversity of methods (interrupt driven, status polling) and a plethora of devices (such as modems and GPS units). Despite recent progress to tackle peripheral input generation challenges in rehosting, a firmware's expectation of multi-byte magic values supplied from peripheral inputs for string operations still pose a significant roadblock. We solve the impediment posed by multi-byte magic strings in monolithic firmware. We propose feedback mechanisms for input-to-state mapping and retaining seeds for targeted replacement mutations with an efficient method to solve multi-byte comparisons. The feedback allows an efficient search over a combinatorial solution-space. We evaluate our prototype implementation, SplITS, with a diverse set of 21 real-world monolithic firmware binaries used in prior works, and 3 new binaries from popular open source projects. SplITS automatically solves 497% more multi-byte magic strings guarding further execution to uncover new code and bugs compared to state-of-the-art. In 11 of the 12 real-world firmware binaries with string comparisons, including those extensively analyzed by prior works, SplITS outperformed, statistically significantly. We observed up to 161% increase in blocks covered and discovered 6 new bugs that remained guarded by string comparisons. Significantly, deep and difficult to reproduce bugs guarded by comparisons, identified in prior work, were found consistently. To facilitate future research in the field, we release SplITS, the new firmware data sets, and bug analysis at https://github.com/SplITS-Fuzzer

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arXiv2023

Ember-IO: Effective Firmware Fuzzing with Model-Free Memory Mapped IO

Exponential growth in embedded systems is driving the research imperative to develop fuzzers to automate firmware testing to uncover software bugs and security vulnerabilities. But, employing fuzzing techniques in this context present a uniquely challenging proposition; a key problem is the need to deal with the diverse and large number of peripheral communications in an automated testing framework. Recent fuzzing approaches: i) employ re-hosting methods by executing code in an emulator because fuzzing on resource limited embedded systems is slow and unscalable; and ii) integrate models of hardware behaviour to overcome the challenges faced by the massive input-space to be explored created by peripheral devices and to generate inputs that are effective in aiding a fuzzer to make progress. Our efforts expounds upon program execution behaviours unique to firmware to address the resulting input-space search problem. The techniques we propose improve the fuzzer's ability to generate values likely to progress execution and avoids time consumed on mutating inputs that are functionally equivalent to other test cases. We demonstrate the methods are highly efficient and effective at overcoming the input-space search problem. Our emulation-based implementation, Ember-IO, when compared to the existing state-of-the-art fuzzing framework across 21 firmware binaries, demonstrates up to 255% improvement in blocks covered. Further Ember-IO discovered 6 new bugs in the real-world firmware, previously not identified by state-of-the-art fuzzing frameworks. Importantly, Ember-IO integrated with the state-of-the-art fuzzer, Fuzzware, demonstrates similar or improved coverage across all firmware binaries whilst reproducing 3 of the 6 new bugs discovered by Ember-IO.

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