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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Speeding-up fuzzing through directional seeds

Abstract Fuzzing is an automated process for discovering inputs in a program that may trigger unexpected behavior. Today, fuzzing has become a standard practice for the discovery of bugs and security vulnerabilities. However, the main issue with such practices is that the exploration of the input space of programs can often be prohibitively expensive. Therefore, several alternative fuzzing strategies have been introduced during the last few years. Some fuzzing techniques rely on human expertise to provide a plausible set of initial input examples, namely, seeds. However, the process of handcrafting seeds for fuzzing purposes often becomes strenuous for humans as it requires a deeper understanding of the Program-Under-Test (PUT). Also, the use of known inputs to programs often does not trigger vulnerable program behavior or may not reach potentially vulnerable code locations. To address those issues, we propose a seed generation framework that enables Human-In-The-Loop (HITL) directed fuzzing where the human assumes a more active role in the creation of seeds that can penetrate and assess desired locations of the PUT. Our proposed framework uses Symbolic Execution (SE) to generate seeds that exercise paths to target program locations. Moreover, our framework enables the visualization of the explored execution paths in the binary of the PUT for the generated seeds. We evaluated our approach on a set of 12 carefully designed C programs with diverse characteristics that mimic real-world programs. The experimental results show the effectiveness of the proposed approach in improving the performance of standard fuzzing tools such as the American Fuzzy Lop ("Image missing" <#comment/> ). Specifically, our solution can generate seeds that substantially enhance the performance of the fuzzer, achieving speedups ranging from $$1.46\times $$ 1.46 × to $$68.53\times $$ 68.53 × for branch conditions, $$1.39\times $$ 1.39 × to $$254.62\times $$ 254.62 × for branch depths, $$14,879.59\times $$ 14 , 879.59 × to $$30,295.88\times $$ 30 , 295.88 × for branch widths over traditional seeds. Additionally, the speedup increases with the number of target function ranging from $$12,260\times $$ 12 , 260 × to $$22,856.07\times $$ 22 , 856.07 × over traditional seeds while only requiring less than 15 seconds on average for the seed generation step.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

IoT Firmware Emulation and Its Security Application in Fuzzing: A Critical Revisit

As IoT devices with microcontroller (MCU)-based firmware become more common in our lives, memory corruption vulnerabilities in their firmware are increasingly targeted by adversaries. Fuzzing is a powerful method for detecting these vulnerabilities, but it poses unique challenges when applied to IoT devices. Direct fuzzing on these devices is inefficient, and recent efforts have shifted towards creating emulation environments for dynamic firmware testing. However, unlike traditional software, firmware interactions with peripherals that are significantly more diverse presents new challenges for achieving scalable full-system emulation and effective fuzzing. This paper reviews 27 state-of-the-art works in MCU-based firmware emulation and its applications in fuzzing. Instead of classifying existing techniques based on their capabilities and features, we first identify the fundamental challenges faced by firmware emulation and fuzzing. We then revisit recent studies, organizing them according to the specific challenges they address, and discussing how each specific challenge is addressed. We compare the emulation fidelity and bug detection capabilities of various techniques to clearly demonstrate their strengths and weaknesses, aiding users in selecting or combining tools to meet their needs. Finally, we highlight the remaining technical gaps and point out important future research directions in firmware emulation and fuzzing.

Zhou, Wei (ORCID:0000000178340839)↗

DOE OSTI2026

Retention and surface morphology evaluation of fine-grain dispersion-strengthened tungsten for plasma-facing component applications

This study exposed novel fine-grain dispersion-strengthened tungsten (W) to high fluence, low energy deuterium (D) and helium (He) plasmas to evaluate how material microstructure and composition affect hydrogen retention and surface morphology. Tested materials included fine-grain dispersion-strengthened tungsten (DSW) with 3 wt% zirconium carbide (ZrC) dispersoids, fine-grain dense W without any dispersoids (FGW), and coarse-grained polycrystalline ‘ITER-grade’ W. Samples were exposed to D 2 + and He + plasmas at fusion-relevant fluences (∼10 25 m -2 ) and ion energies (75 eV) over a range of temperatures (200 °C, 300 °C, 450 °C for D, 850 °C for He). Helium ion microscopy was performed on the exposed samples to evaluate surface morphology changes and material integrity. After D plasma exposure, the ZrC dispersoids showed near-surface degradation at exposure temperatures above 300 °C, but no detrimental morphology changes were observed for the adjacent W grains. After He plasma-exposure, nano-structured fuzz formation was observed in the tungsten matrix of all samples. The ZrC dispersoids maintained their integrity despite the surrounding fuzz growth, with clear delineation between the W fuzz and dispersoid regions. Thermal desorption spectroscopy showed that ZrC DSW consistently retained more D than the FGW by about a factor of 2 across all temperatures. At 200 °C and 300 °C, the ITER-W displayed lower D retention than both the DSW and FGW, however at 450 °C ITER-W showed the highest retention, about 50% more than DSW. He retention was comparable across all samples, with the highest retention observed in the fine-grain W, only 26% higher than in ITER-W. These insights on retention behavior will inform further optimization of these novel fine-grained tungsten materials with and without dispersoid additives.

Dispersion-strengthened tungsten↗

DOE OSTI2025

Accelerating plasma and radiation surface science using transient grating spectroscopy

A facility for the investigation of in situ radiation-materials and plasma-materials interaction is demonstrated with tungsten, using transient grating spectroscopy as a probe of thermal diffusivity and surface acoustic wave speed. Helium plasma exposure at 645 °C to 1.18 × 10 18 cm −2 helium, until the growth of tungsten fuzz, showed an increase in surface acoustic wave speed at the near-surface from 2542 ± 1 m s −1 up to 2565 ± 1 m s −1 , followed by a greater drop to 2499 ± 7 m s −1 . No observable change in thermal diffusivity was present for plasma exposure alone. A separate 10.26 MeV self-ion-irradiation of tungsten to a dose of 7.92 dpa showed a reduction in both thermal diffusivity from 61.4 ± 1.4 mm 2 s −1 to 36.0 ± 0.7 mm 2 s −1 , following trends seen in existing studies, and surface acoustic wave speed from 2647.8 ± 0.6 m s −1 to 2640.0 ± 0.4 m s −1 . Facilities like these are poised to rapidly close critical knowledge gaps regarding the coupled effects of plasma and radiation damage for materials in fusion systems.

Accelerated plasmas↗

DOE OSTI2025

Secondary electron emission for reticulated carbon foam surfaces using direct measurements and spectroscopic analysis

This study investigates secondary electron emission (SEE) characteristics of reticulated foams using direct measurements and analytical modeling. Total SEE was quantified, revealing suppression of up to 44% in carbon foam structures compared to planar graphite surfaces. An optimal geometric configuration was identified and supported by analytical models. SEE angular dependence experiments showed diverse behaviors: fiber-like behavior and directional dependence for pore and ligaments on the mm scale, with fuzz-like characteristics when the foam features are between 10–100 µm. Electron energy analyzer measurements showed that carbon foams preferentially suppress inelastic backscattered electrons (BSEs) more so than true secondary electrons (SEs). The analysis indicated a larger fraction of low-energy SE generation in foams compared to flat surfaces due to increased emission from curved fiber ligaments and tertiary SEs from high-energy BSEs. These findings have implications for design and optimization of materials with tailored electron emission properties for applications like plasma-facing components, spacecraft materials, and accelerator surfaces.

Auger↗

DOE OSTI2025

Enhancing Automotive Intrusion Detection Through Multi-Modal Fusion: A CAN FD-LiDAR Approach

As vehicles become smarter and more autonomous, they increasingly depend on advanced sensors and communication technologies to operate securely. However, such growing dependence on technology—whether it’s CAN (Controller Area Network) for internal communication or LiDAR (Light Detection and Ranging) for sensing the world around them—also expands the attack surface for the types of cyber attacks. Traditional intrusion detection systems (IDS) typically monitor these systems in isolation, limiting their ability to detect sophisticated, crosssystem attacks. To address this, we propose a multi-modal fusion approach that combines real-world CAN FD signals (from the HCRL dataset) with LiDAR features (from the nuScenes dataset) to enhance attack detection. Our method employs a twostage ensemble approach. Calibrated XGBoost and LightGBM models initially process CAN FD (Fuzzing Data) and LiDAR data independently, detecting timing anomalies and space abnormalities. They are subsequently logarithmically combined with a logistic regression meta-model along with 17 engineered features capturing cross-modal behavior, prediction conflicts, and nonlinear interactions. This approach achieves an AUC of 0.87 and an F1-score of 0.82, surpassing single-modality baselines and early fusion methods, at merely 2 ms inference latency. Compared with deep learning competitors, it is 3 times more efficient, providing a lightweight, interpretable, and real time solution to automotive cybersecurity.

97 MATHEMATICS AND COMPUTING↗