arXiv subjects

Hulin Wang

Publications and source records attributed to Hulin Wang.

13 recordsLinked to original sources

arXiv2026

No-Box Vulnerability Analysis: Description-only Detection of Indirect Prompt Injection Vulnerabilities in MCP Servers

Conventional vulnerability analysis relies on either system access or dynamic interaction, all of which may be unavailable to third-party analysts auditing closed-source, remotely hosted, critical in situ systems, or commercially gated software. Therefore, we propose a new paradigm of no-box vulnerability analysis in which neither access nor runtime interaction is available, and only functionality metadata is available. Such metadata defines the intended behavior of the system, including its inputs, outputs, and side effects, while constraining the space of implementations consistent with that behavior. We propose hypothesizing about vulnerabilities that exist across all possible implementations of a given system metadata, without observing or interacting with the target system. An analyst can later validate these hypotheses when additional access is available. We showcase the feasibility of no-box vulnerability analysis through implementing a prototype called MCPSEC, which audits Model Context Protocol (MCP) servers for indirect prompt injection vulnerabilities using only the tool metadata exposed at server registration time. We evaluate MCPSEC on 20 widely deployed MCP servers comprising 177 tools, among which human evaluators confirm 95 vulnerable tools. MCPSEC identified 143 tools as vulnerable, and for each vulnerable tool, it produced a hypothesized vulnerability along with exploitation technique. Using metadata alone, MCPSEC predicted 94 (98.9% recall) real verified vulnerabilities, compared against an LLM baseline with 80 (84.2% recall). Overall, our results introduce no-box vulnerability analysis as a new analysis paradigm and demonstrate its practical feasibility in realistic systems.

cs.CR↗

arXiv2026

Low-energy Muon-Nucleon scattering experiment: LUNE (White Paper)

The HIAF will provide high-intensity, high-quality muon beams with momenta from 0.5 to 7.5 GeV/c. This energy range is uniquely suited for precision muon scattering, bridging the gap between low-energy electron facilities and future high-energy lepton-ion colliders. In particular, HIAF will enable precision measurements with both positive and negative muon beams over a broad kinematic range, complementing existing electron-scattering facilities such as JLab, EicC and EIC. Based on HIAF muon source, the LUNE Collaboration has been established to address several fundamental questions in nuclear and particle physics, including the proton charge radius puzzle, nucleon electromagnetic structure, and the dynamics of quantum electrodynamics and hadronic interactions. The program proceeds in two phases, from elastic scattering to nucleon structure and beyond-Standard-Model searches. The experiment is expected to determine the proton charge radius with a precision of approximately 1.0\% using elastic muon-proton scattering. It will also perform systematic measurements of the proton electromagnetic form factors with both $\mu^+$ and $\mu^-$ beams, enabling precise studies of two-photon exchange effects and stringent tests of quantum electrodynamics. Beyond elastic scattering, LUNE will investigate TMD, gravitational form factors, and nuclear charge radii, providing new insights into the 3D structure of nucleons and nuclei. The experiment will further address important topics including Coulomb-distortion corrections, nuclear medium effects, and possible signatures of physics beyond the Standard Model. This white paper presents the scientific motivation, detector concept, expected performance, and long-term strategy of LUNE.

hep-ex↗

arXiv2026

SeedSmith: LLM-Driven Seed Synthesis for Directed Fuzzing

Directed fuzzing steers fuzzers toward user-defined sink functions to identify vulnerabilities, but it frequently fails to trigger crashes even after long campaigns. We identify two challenges that prevent directed fuzzers from exposing crashes: incomplete static analysis of indirect calls, which leaves reachable paths invisible to distance-based guidance, and lack of semantic guidance for crash preconditions, which blind mutation cannot satisfy within practical time budgets. A natural intervention point is the initial seed corpus: seeds that encode the right control-flow path and satisfy key crash preconditions shift fuzzing from blind exploration to local refinement. Existing seed generation approaches address neither: grammar-based and format-driven methods produce structurally valid inputs with no sink awareness, while LLM-based methods either lack sink targeting or inherit static analysis limitations through one-shot prompting. We present SeedSmith, an agentic LLM pipeline that replicates a security analyst's workflow: starting from a sink, it iteratively explores the codebase, resolves indirect calls, identifies crash preconditions, and synthesizes concrete inputs that satisfy them. Because SeedSmith operates as a seed generation front-end, its seeds are fuzzer-agnostic and improve any downstream mutation-based fuzzer without modification. On Magma, fuzzers using SeedSmith seeds achieve geometric mean crash-time speedups of 11.51 times (AFL++) to 14.66 times (AFLGo) over default seeds. On ARVO, SeedSmith enables fuzzers to trigger 16 previously unreachable bugs spanning 10 projects with diverse input formats.

cs.CR↗

arXiv2026

Root-Cause-Driven Automated Vulnerability Repair

Recent LLM-based systems have made automated vulnerability repair increasingly practical, but two challenges remain. First, without strong signals about where a bug originates, repair agents drift toward shallow edits that silence the observed failure while leaving the underlying defect unresolved. Second, finding the root cause for bugs is hard: even developers familiar with the codebase frequently produce fixes that address symptoms rather than the root cause, and LLM-based agents, operating with noisier context and less program understanding, are no exception. We present Kumushi, a root-cause-driven patching agent that addresses both challenges by combining diversified dynamic fault localization with evidence-weighted ranking to focus the LLM on the code most relevant to the defect. To rigorously measure whether Kumushi produces genuinely better patches, we also introduce a two-tier patch quality metric that pairs automated oracle validation with structured expert assessment of patches. Evaluated on 178 C/C++ vulnerabilities, Kumushi substantially outperforms prior specialized repair agents under automated evaluation while matching a frontier commercial coding agent. Expert assessment then reveals differences that oracles cannot: Kumushi produces more root-cause fixes and fewer superficial patches, and is preferred in the majority of decisive pairwise comparisons. Together, these results demonstrate that progress in automated vulnerability repair requires not only stronger patching systems, but also richer evaluation methods capable of distinguishing genuine fixes from oracle-passing ones.

cs.CR↗

arXiv2025

BuildBench: Benchmarking LLM Agents on Compiling Real-World Open-Source Software

Automatically compiling open-source software (OSS) projects is a vital, labor-intensive, and complex task, which makes it a good challenge for LLM Agents. Existing methods rely on manually curated rules and workflows, which cannot adapt to OSS that requires customized configuration or environment setup. Recent attempts using Large Language Models (LLMs) used selective evaluation on a subset of highly rated OSS, a practice that underestimates the realistic challenges of OSS compilation. In practice, compilation instructions are often absent, dependencies are undocumented, and successful builds may even require patching source files or modifying build scripts. We propose a more challenging and realistic benchmark, BUILD-BENCH, comprising OSS that are more diverse in quality, scale, and characteristics. Furthermore, we propose a strong baseline LLM-based agent, OSS-BUILD-AGENT, an effective system with enhanced build instruction retrieval module that achieves state-of-the-art performance on BUILD-BENCH and is adaptable to heterogeneous OSS characteristics. We also provide detailed analysis regarding different compilation method design choices and their influence to the whole task, offering insights to guide future advances. We believe performance on BUILD-BENCH can faithfully reflect an agent's ability to tackle compilation as a complex software engineering tasks, and, as such, our benchmark will spur innovation with a significant impact on downstream applications in the fields of software development and software security.

cs.SE↗

arXiv2025

Simulation of radiation environment for the beam monitor of CEE experiment

The cooling storage ring external-target experiment is a large-scale nuclear physics experiment, which aims to study the physics of heavy-ion collisions at low temperatures and high baryon densities. A beam monitor (BM) is placed in the beam line to monitor the beam status and to improve the reconstruction resolution of the primary vertices. The radiation dose and particle fluence stemming from the beam interactions with gases and detector materials affect the performance of the sensors and electronics of BM. This paper uses FLUKA Monte Carlo code to simulate the radiation environment of BM detector. Radiation quantities including the total ionizing dose, 1 MeV neutron equivalent fluence, high-energy hadron flux, thermal neutron flux, and nuclear fragment flux are presented. Results of alternative simulation setups, including adding shielding layers inside the BM, are also investigated.

physics.ins-det↗

arXiv2025

Design and performance of the prototype gaseous beam monitor with GEM and pixel sensors for the CSR external-target experiment

A gaseous beam monitor utilizing gas electron multiplier (GEM) and pixel sensors is being developed for the Cooling Storage Ring (CSR) External-target Experiment (CEE) at Heavy Ion Research Facility in Lanzhou (HIRFL). The beam monitor is mainly used to track each beam particle, providing an accurate reconstruction of the primary vertex of the collision. Two generations of the pixel sensors (named Topmetal-CEE) were produced, with the second generation's performance improving over the first one. The design and performance of the prototype are described in the paper. Characterization of the prototype with heavy-ion beams and laser beams are presented, showing a spatial resolution better than 50 $\mum$ and a time resolution better than 15 ns.

physics.ins-det↗

arXiv2025

Development of a simulation and analysis framework for N{\nu}DEx experiment

N$\nu$DEx aims to search for the neutrinoless double beta decay in $^{82}$Se using a high pressure $^{82}$SeF$_6$ gas time projection chamber (TPC). This paper presents a simulation and analysis framework developed specifically for the N$\nu$DEx experiment. Using density functional theory and two-temperature theory, the reduced mobilities of SeF$_5^-$ and SeF$_6^-$ ions in SeF$_6$ were calculated, yielding values of 0.444 and 0.430 $\mathrm{cm^2V^{-1}s^{-1}}$ respectively, with an estimated uncertainty within 3\%. The TPC geometry, featuring a cathode, focusing plane, and anode structure, was modeled in COMSOL to compute electric fields. Signal and background events were generated using BxDecay0 and Geant4, while Garfield++ was employed to simulate charge transport and signal induction. Three-dimensional tracks were reconstructed from drift-time differences between the two assumed ion species using a breadth-first search algorithm. To demonstrate the framework's analytical capability, topological variables were taken from reconstructed tracks and used to define selection criteria. A boosted decision tree was then implemented to benchmark the signal-background separation. This simulation framework successfully validates the complete experimental workflow, serving as a robust tool for detector design and future sensitivity studies in the N$\nu$DEx experiment.

physics.ins-det↗

arXiv2024

Measurement of gas properties for the ion-TPC of N$\nu$DEx experiment

In the N$\nu$DEx collaboration, a high-pressure gas TPC is being developed to search for the neutrinoless double beta decay. The use of electronegative $\mathrm{^{82}SeF_{6}}$ gas mandates an ion-TPC. The reconstruction of $z$ coordinate is to be realized exploiting the feature of multiple species of charge carriers. As the initial stage of the development, we studied the properties of the $\mathrm{SF_{6}}$ gas, which is non-toxic and has similar molecular structure to $\mathrm{SeF_{6}}$. In the paper we present the measurement of drift velocities and mobilities of the majority and minority negative charge carriers found in $\mathrm{SF_{6}}$ at a pressure of 750 Torr, slightly higher than the local atmospheric pressure. The reduced fields range between 3.0 and 5.5 Td. It was performed using a laser beam to ionize the gas inside a small TPC, with a drift length of 3.7 cm. A customized charge sensitive amplifier was developed to read out the anode signals induced by the slowly drifting ions. The reconstruction of $z$ coordinate using the difference in the velocities of the two carriers was also demonstrated.

physics.ins-det↗

arXiv2024

Performance study of the JadePix-3 telescope from a beam test

We present the results of a beam test conducted on a telescope using the JadePix-3 pixel sensor, developed with TowerJazz 180 nm CMOS imaging technology. The telescope is composed of five planes, each equipped with a JadePix-3 sensor with pitches of 26 um x 16 um and 23.11 um x 16 um. In addition, it features an FPGA-based synchronous readout system. The telescope underwent testing using an electron beam with energy ranging from 4 to 6 GeV. At an electron energy of 5.4 GeV, the telescope demonstrated superior spatial resolutions of 2.6 and 2.3 um in two dimensions. By designating the central plane as the device under test, we evaluated the JadePix-3 sensor's spatial resolutions as 5.2 and 4.6 um in two dimensions, achieving a detection efficiency of over 99%.

hep-ex↗

arXiv2022

FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks

Increasing concerns and regulations about data privacy and sparsity necessitate the study of privacy-preserving, decentralized learning methods for natural language processing (NLP) tasks. Federated learning (FL) provides promising approaches for a large number of clients (e.g., personal devices or organizations) to collaboratively learn a shared global model to benefit all clients while allowing users to keep their data locally. Despite interest in studying FL methods for NLP tasks, a systematic comparison and analysis is lacking in the literature. Herein, we present the FedNLP, a benchmarking framework for evaluating federated learning methods on four different task formulations: text classification, sequence tagging, question answering, and seq2seq. We propose a universal interface between Transformer-based language models (e.g., BERT, BART) and FL methods (e.g., FedAvg, FedOPT, etc.) under various non-IID partitioning strategies. Our extensive experiments with FedNLP provide empirical comparisons between FL methods and helps us better understand the inherent challenges of this direction. The comprehensive analysis points to intriguing and exciting future research aimed at developing FL methods for NLP tasks.

cs.CL↗

arXiv2021

The DAQ and control system for JadePix3

The silicon pixel sensor is the core component of the vertex detector for the Circular Electron Positron Collider~(CEPC). The JadePix3 is a full-function large-size CMOS chip designed for the CEPC vertex detector. To test all the functions and the performance of this chip, we designed a test system based on the IPbus framework. The test system controls the parameters and monitors the status of the pixel chip. By integrating the jumbo frame feature into the IPbus suite, the block read/write speed is further extended in order to meet the specifications of the JadePix3. The robustness, scalability, and portability of this system have been verified by pulse test, cosmic test and laser test in the laboratory. This paper summarizes the DAQ and control system of the JadePix3 and presents the first results of the tests.

physics.ins-det↗

arXiv2019

Do People Prefer "Natural" code?

Natural code is known to be very repetitive (much more so than natural language corpora); furthermore, this repetitiveness persists, even after accounting for the simpler syntax of code. However, programming languages are very expressive, allowing a great many different ways (all clear and unambiguous) to express even very simple computations. So why is natural code repetitive? We hypothesize that the reasons for this lie in fact that code is bimodal: it is executed by machines, but also read by humans. This bimodality, we argue, leads developers to write code in certain preferred ways that would be familiar to code readers. To test this theory, we 1) model familiarity using a language model estimated over a large training corpus and 2) run an experiment applying several meaning preserving transformations to Java and Python expressions in a distinct test corpus to see if forms more familiar to readers (as predicted by the language models) are in fact the ones actually written. We find that these transformations generally produce program structures that are less common in practice, supporting the theory that the high repetitiveness in code is a matter of deliberate preference. Finally, 3) we use a human subject study to show alignment between language model score and human preference for the first time in code, providing support for using this measure to improve code.

cs.CL↗