arXiv subjects

Ningyu He

Publications and source records attributed to Ningyu He.

At least 19 recordsLinked to original sources

arXiv2026

NotDec: WebAssembly Decompilation With Inter-Procedural Type Recovery

With WebAssembly widely supported in browsers, containers, IoT devices, and serverless platforms and increasingly adopted as a universal low-level bytecode standard, auditing its hidden vulnerabilities and malicious intentions has become critical. Decompiling existing WebAssembly modules can help security researchers and end users understand binary behavior, but current tools suffer from verbose result, poor readability, and limited type recovery. We present NotDec, an advanced WebAssembly decompilation framework. NotDec extends the WebAssembly type checking algorithm to lift bytecode into an SSA-based IR, applies the inter-procedural type recovery algorithm Retypd with pointer and numeric value differentiation methods to recover complex data structures, and leverages Memory SSA alongside semantics-preserving structured control-flow analysis to emit readable, semantically consistent C code. NotDec achieves 100% recompilation success rate on all 5,241 Juliet samples and all Howard dataset programs, significantly outperforming baselines including Ghidra (45.95% success rate). On type recovery accuracy, NotDec recovers 85.33% of struct member accesses in real-world programs, vastly exceeding Ghidra's 9.24%. While the full inter-procedural version faces scalability challenges on large binaries, the intra-procedural variant NotDec_F demonstrates superior efficiency, consuming less than half of Ghidra's memory and up to 97% less execution time on unoptimized binaries.

cs.SE↗

arXiv2026

CLIR: Liveness-Driven and Structure-Aware Fuzzing for the Cranelift Compiler

Modern compilers are complex software systems that must correctly translate high-level programming languages into machine code across multiple architectures. Cranelift, a fast and modern compiler backend originally developed for WebAssembly and recently adopted as an experimental backend for Rust, has gained increasing importance due to its superior compilation speed compared to LLVM and comprehensive multi-architecture support, including x86-64, AArch64, s390x, and RISCV64. However, despite decades of development in compiler testing, testing Cranelift still presents unique challenges, including (1) constructing valid IR under the strict enforcement of SSA form, (2) generating sequences with sufficient computational density to stress backend components, and (3) balancing broad backend coverage with efficient root cause analysis across heterogeneous architectures. To address these challenges, we propose CLIR, a differential testing framework that integrates a syntax-preserving hierarchical generation strategy to guarantee SSA validity, a liveness-guided instruction refinement mechanism to maximize computational density, and a diagnosis-guided cross-architecture adaptation scheme to facilitate efficient root cause analysis across heterogeneous backends. Our comprehensive evaluation demonstrates that CLIR significantly outperforms existing state-of-the-art baselines, detecting 8x, 24x, and 8x more unique bugs than cranelift-fuzzgen, wasm-smith, and WASMaker, respectively, while RustSmith uncovered no bugs. Consequently, within 72 hours of testing, CLIR discovered 24 bugs spanning all target architectures, with 21 confirmed and 9 fixed.

cs.SE↗

arXiv2026

When Specifications Meet Reality: Uncovering API Inconsistencies in Ethereum Infrastructure

The Ethereum ecosystem, which secures over $381 billion in assets, fundamentally relies on client APIs as the sole interface between users and the blockchain. However, these critical APIs suffer from widespread implementation inconsistencies, which can lead to financial discrepancies, degraded user experiences, and threats to network reliability. Despite this criticality, existing testing approaches remain manual and incomplete: they require extensive domain expertise, struggle to keep pace with Ethereum's rapid evolution, and fail to distinguish genuine bugs from acceptable implementation variations. We present APIDiffer, the first specification-guided differential testing framework designed to automatically detect API inconsistencies across Ethereum's diverse client ecosystem. APIDiffer transforms API specifications into comprehensive test suites through two key innovations: (1) specification-guided test input generation that creates both syntactically valid and invalid requests enriched with real-time blockchain data, and (2) specification-aware false positive filtering that leverages large language models to distinguish genuine bugs from acceptable variations. Our evaluation across all 11 major Ethereum clients reveals the pervasiveness of API bugs in production systems. APIDiffer uncovered 72 bugs, with 90.28% already confirmed or fixed by developers. Beyond these raw numbers, APIDiffer achieves up to 89.67% higher code coverage than existing tools and reduces false positive rates by 37.38%. The Ethereum community's response validates our impact: developers have integrated our test cases, expressed interest in adopting our methodology, and escalated one bug to the official Ethereum Project Management meeting.

cs.SE↗

arXiv2026

An Effective and Cost-Efficient Agentic Framework for Ethereum Smart Contract Auditing

Smart contract security is paramount, but identifying intricate business logic vulnerabilities remains a persistent challenge because existing solutions consistently fall short: manual auditing is unscalable, static analysis tools are plagued by false positives, and fuzzers struggle to navigate deep logic states within complex systems. Even emerging AI-based methods suffer from hallucinations, context constraints, and a heavy reliance on expensive, proprietary Large Language Models. In this paper, we introduce Heimdallr, an automated auditing agent designed to overcome these hurdles through four core innovations. By reorganizing code at the function level, Heimdallr minimizes context overhead while preserving essential business logic. It then employs heuristic reasoning to detect complex vulnerabilities and automatically chain functional exploits. Finally, a cascaded verification layer validates these findings to eliminate false positives. Notably, this approach achieves high performance on lightweight, open-source models like GPToss-120B without relying on proprietary systems. Our evaluations demonstrate exceptional performance, as Heimdallr successfully reconstructed 17 out of 20 real-world attacks post June 2025, resulting in total losses of $384M, and uncovered 4 confirmed zero-day vulnerabilities that safeguarded $400M in TVL. Compared to SOTA baselines including both official industrial tools and academic tools, Heimdallr at most reduces analysis time by 97.59% and financial costs by 98.77% while boosting detection precision by over 93.66%. Notably, when applied to auditing contests, Heimdallr can achieve a 92.45% detection rate at a negligible cost of $2.31 per 10K LOC. We provide production-ready auditing services and release valuable benchmarks for future work.

cs.CR↗

arXiv2025

Cybersquatting in Web3: The Case of NFT

Cybersquatting refers to the practice where attackers register a domain name similar to a legitimate one to confuse users for illegal gains. With the growth of the Non-Fungible Token (NFT) ecosystem, there are indications that cybersquatting tactics have evolved from targeting domain names to NFTs. This paper presents the first in-depth measurement study of NFT cybersquatting. By analyzing over 220K NFT collections with over 150M NFT tokens, we have identified 8,019 cybersquatting NFT collections targeting 654 popular NFT projects. Through systematic analysis, we discover and characterize seven distinct squatting tactics employed by scammers. We further conduct a comprehensive measurement study of these cybersquatting NFT collections, examining their metadata, associated digital asset content, and social media status. Our analysis reveals that these NFT cybersquatting activities have resulted in a significant financial impact, with over 670K victims affected by these scams, leading to a total financial exploitation of $59.26 million. Our findings demonstrate the urgency to identify and prevent NFT squatting abuses.

cs.CR↗

arXiv2025

WalletProbe: A Testing Framework for Browser-based Cryptocurrency Wallet Extensions

Serving as the first touch point for users to the cryptocurrency world, cryptocurrency wallets allow users to manage, receive, and transmit digital assets on blockchain networks and interact with emerging decentralized finance (DeFi) applications. Unfortunately, cryptocurrency wallets have always been the prime targets for attackers, and incidents of wallet breaches have been reported from time to time. Although some recent studies have characterized the vulnerabilities and scams related to wallets, they have generally been characterized in coarse granularity, overlooking potential risks inherent in detailed designs of cryptocurrency wallets, especially from perspectives including user interaction and advanced features. To fill the void, in this paper, we present a fine-grained security analysis on browser-based cryptocurrency wallets. To pinpoint security issues of components in wallets, we design WalletProbe, a mutation-based testing framework based on visual-level oracles. We have identified 13 attack vectors that can be abused by attackers to exploit cryptocurrency wallets and exposed 21 concrete attack strategies. By applying WalletProbe on 39 widely-adopted browser-based wallet extensions, we astonishingly figure out all of them can be abused to steal crypto assets from innocent users. Identified potential attack vectors were reported to wallet developers timely and 26 issues have been patched already. It is, hence, urgent for our community to take action to mitigate threats related to cryptocurrency wallets. We promise to release all code and data to promote the development of the community.

cs.CR↗

arXiv2025

OpDiffer: LLM-Assisted Opcode-Level Differential Testing of Ethereum Virtual Machine

As Ethereum continues to thrive, the Ethereum Virtual Machine (EVM) has become the cornerstone powering tens of millions of active smart contracts. Intuitively, security issues in EVMs could lead to inconsistent behaviors among smart contracts or even denial-of-service of the entire blockchain network. However, to the best of our knowledge, only a limited number of studies focus on the security of EVMs. Moreover, they suffer from 1) insufficient test input diversity and invalid semantics; and 2) the inability to automatically identify bugs and locate root causes. To bridge this gap, we propose OpDiffer, a differential testing framework for EVM, which takes advantage of LLMs and static analysis methods to address the above two limitations. We conducted the largest-scale evaluation, covering nine EVMs and uncovering 26 previously unknown bugs, 22 of which have been confirmed by developers and three have been assigned CNVD IDs. Compared to state-of-the-art baselines, OpDiffer can improve code coverage by at most 71.06%, 148.40% and 655.56%, respectively. Through an analysis of real-world deployed Ethereum contracts, we estimate that 7.21% of the contracts could trigger our identified EVM bugs under certain environmental settings, potentially resulting in severe negative impact on the Ethereum ecosystem.

cs.SE↗

arXiv2025

The Promise and Pitfalls of WebAssembly: Perspectives from the Industry

As JavaScript has been criticized for performance and security issues in web applications, WebAssembly (Wasm) was proposed in 2017 and is regarded as the complementation for JavaScript. Due to its advantages like compact-size, native-like speed, and portability, Wasm binaries are gradually used as the compilation target for industrial projects in other high-level programming languages and are responsible for computation-intensive tasks in browsers, e.g., 3D graphic rendering and video decoding. Intuitively, characterizing in-the-wild adopted Wasm binaries from different perspectives, like their metadata, relation with source programming language, existence of security threats, and practical purpose, is the prerequisite before delving deeper into the Wasm ecosystem and beneficial to its roadmap selection. However, currently, there is no work that conducts a large-scale measurement study on in-the-wild adopted Wasm binaries. To fill this gap, we collect the largest-ever dataset to the best of our knowledge, and characterize the status quo of them from industry perspectives. According to the different roles of people engaging in the community, i.e., web developers, Wasm maintainers, and researchers, we reorganized our findings to suggestions and best practices for them accordingly. We believe this work can shed light on the future direction of the web and Wasm.

cs.SE↗

arXiv2025

Following Devils' Footprint: Towards Real-time Detection of Price Manipulation Attacks

Price manipulation attack is one of the notorious threats in decentralized finance (DeFi) applications, which allows attackers to exchange tokens at an extensively deviated price from the market. Existing efforts usually rely on reactive methods to identify such kind of attacks after they have happened, e.g., detecting attack transactions in the post-attack stage, which cannot mitigate or prevent price manipulation attacks timely. From the perspective of attackers, they usually need to deploy attack contracts in the pre-attack stage. Thus, if we can identify these attack contracts in a proactive manner, we can raise alarms and mitigate the threats. With the core idea in mind, in this work, we shift our attention from the victims to the attackers. Specifically, we propose SMARTCAT, a novel approach for identifying price manipulation attacks in the pre-attack stage proactively. For generality, it conducts analysis on bytecode and does not require any source code and transaction data. For accuracy, it depicts the control- and data-flow dependency relationships among function calls into a token flow graph. For scalability, it filters out those suspicious paths, in which it conducts inter-contract analysis as necessary. To this end, SMARTCAT can pinpoint attacks in real time once they have been deployed on a chain. The evaluation results illustrate that SMARTCAT significantly outperforms existing baselines with 91.6% recall and ~100% precision. Moreover, SMARTCAT also uncovers 616 attack contracts in-the-wild, accounting for \$9.25M financial losses, with only 19 cases publicly reported. By applying SMARTCAT as a real-time detector in Ethereum and Binance Smart Chain, it has raised 14 alarms 99 seconds after the corresponding deployment on average. These attacks have already led to $641K financial losses, and seven of them are still waiting for their ripe time.

cs.CR↗

arXiv2024

SeeWasm: An Efficient and Fully-Functional Symbolic Execution Engine for WebAssembly Binaries

WebAssembly (Wasm), as a compact, fast, and isolation-guaranteed binary format, can be compiled from more than 40 high-level programming languages. However, vulnerabilities in Wasm binaries could lead to sensitive data leakage and even threaten their hosting environments. To identify them, symbolic execution is widely adopted due to its soundness and the ability to automatically generate exploitations. However, existing symbolic executors for Wasm binaries are typically platform-specific, which means that they cannot support all Wasm features. They may also require significant manual interventions to complete the analysis and suffer from efficiency issues as well. In this paper, we propose an efficient and fully-functional symbolic execution engine, named SeeWasm. Compared with existing tools, we demonstrate that SeeWasm supports full-featured Wasm binaries without further manual intervention, while accelerating the analysis by 2 to 6 times. SeeWasm has been adopted by existing works to identify more than 30 0-day vulnerabilities or security issues in well-known C, Go, and SGX applications after compiling them to Wasm binaries.

cs.CR↗

arXiv2024

All Your Tokens are Belong to Us: Demystifying Address Verification Vulnerabilities in Solidity Smart Contracts

In Ethereum, the practice of verifying the validity of the passed addresses is a common practice, which is a crucial step to ensure the secure execution of smart contracts. Vulnerabilities in the process of address verification can lead to great security issues, and anecdotal evidence has been reported by our community. However, this type of vulnerability has not been well studied. To fill the void, in this paper, we aim to characterize and detect this kind of emerging vulnerability. We design and implement AVVERIFIER, a lightweight taint analyzer based on static EVM opcode simulation. Its three-phase detector can progressively rule out false positives and false negatives based on the intrinsic characteristics. Upon a well-established and unbiased benchmark, AVVERIFIER can improve efficiency 2 to 5 times than the SOTA while maintaining a 94.3% precision and 100% recall. After a large-scale evaluation of over 5 million Ethereum smart contracts, we have identified 812 vulnerable smart contracts that were undisclosed by our community before this work, and 348 open source smart contracts were further verified, whose largest total value locked is over $11.2 billion. We further deploy AVVERIFIER as a real-time detector on Ethereum and Binance Smart Chain, and the results suggest that AVVERIFIER can raise timely warnings once contracts are deployed.

cs.CR↗

arXiv2024

Remeasuring the Arbitrage and Sandwich Attacks of Maximal Extractable Value in Ethereum

Maximal Extractable Value (MEV) drives the prosperity of the blockchain ecosystem. By strategically including, excluding, or reordering transactions within blocks, block producers can extract additional value, which in turn incentivizes them to keep the decentralization of the whole blockchain platform. Before September 2022, around $675M was extracted in terms of MEV in Ethereum. Despite its importance, current work on identifying MEV activities suffers from two limitations. On the one hand, current methods heavily rely on clumsy heuristic rule-based patterns, leading to numerous false negatives or positives. On the other hand, the observations and conclusions are drawn from the early stage of Ethereum, which cannot be used as effective guiding principles after The Merge. To address these challenges, in this work, we innovatively proposed a profitability identification algorithm. Based on this, we designed two robust algorithms to identify MEV activities on our collected largest-ever dataset. Based on the identified results, we have characterized the overall landscape of the Ethereum MEV ecosystem, the impact the private transaction architectures bring in, and the adoption of back-running mechanisms. Our research sheds light on future MEV-related work.

cs.CR↗

arXiv2024

WALLETRADAR: Towards Automating the Detection of Vulnerabilities in Browser-based Cryptocurrency Wallets

Cryptocurrency wallets, acting as fundamental infrastructure to the blockchain ecosystem, have seen significant user growth, particularly among browser-based wallets (i.e., browser extensions). However, this expansion accompanies security challenges, making these wallets prime targets for malicious activities. Despite a substantial user base, there is not only a significant gap in comprehensive security analysis but also a pressing need for specialized tools that can aid developers in reducing vulnerabilities during the development process. To fill the void, we present a comprehensive security analysis of browser-based wallets in this paper, along with the development of an automated tool designed for this purpose. We first compile a taxonomy of security vulnerabilities resident in cryptocurrency wallets by harvesting historical security reports. Based on this, we design WALLETRADAR, an automated detection framework that can accurately identify security issues based on static and dynamic analysis. Evaluation of 96 popular browser-based wallets shows WALLETRADAR's effectiveness, by successfully automating the detection process in 90% of these wallets with high precision. This evaluation has led to the discovery of 116 security vulnerabilities corresponding to 70 wallets. By the time of this paper, we have received confirmations of 10 vulnerabilities from 8 wallet developers, with over $2,000 bug bounties. Further, we observed that 12 wallet developers have silently fixed 16 vulnerabilities after our disclosure. WALLETRADAR can effectively automate the identification of security risks in cryptocurrency wallets, thereby enhancing software development quality and safety in the blockchain ecosystem.

cs.CR↗

arXiv2023

WRTester: Differential Testing of WebAssembly Runtimes via Semantic-aware Binary Generation

Wasm runtime is a fundamental component in the Wasm ecosystem, as it directly impacts whether Wasm applications can be executed as expected. Bugs in Wasm runtime bugs are frequently reported, thus our research community has made a few attempts to design automated testing frameworks for detecting bugs in Wasm runtimes. However, existing testing frameworks are limited by the quality of test cases, i.e., they face challenges of generating both semantic-rich and syntactic-correct Wasm binaries, thus complicated bugs cannot be triggered. In this work, we present WRTester, a novel differential testing framework that can generated complicated Wasm test cases by disassembling and assembling of real-world Wasm binaries, which can trigger hidden inconsistencies among Wasm runtimes. For further pinpointing the root causes of unexpected behaviors, we design a runtime-agnostic root cause location method to accurately locate bugs. Extensive evaluation suggests that WRTester outperforms SOTA techniques in terms of both efficiency and effectiveness. We have uncovered 33 unique bugs in popular Wasm runtimes, among which 25 have been confirmed.

cs.SE↗

arXiv2023

SoK: On the Security of Non-Fungible Tokens

Non-fungible tokens (NFTs) drive the prosperity of the Web3 ecosystem. By November 2023, the total market value of NFT projects reached approximately 16 billion USD. Accompanying the success of NFTs are various security issues, i.e., attacks and scams are prevalent in the ecosystem. While NFTs have attracted significant attentions from both industry and academia, there is a lack of understanding of kinds of NFT security issues. The discovery, in-depth analysis, and systematic categorization of these security issues are of significant importance for the prosperous development of the NFT ecosystem. To fill the gap, we performed a systematic literature review related to NFT security, and we have identified 142 incidents from 213 security reports and 18 academic papers until October 1st, 2023. Through manual analysis of the compiled security incidents, we have classified them into 12 major categories. Then we explored potential solutions and mitigation strategies. Drawing from these analyses, we established the first NFT security reference frame. Except, we extracted the characteristics of NFT security issues, i.e., the prevalence, severity, and intractability. We have indicated the gap between industry and academy for NFT security, and provide further research directions for the community. This paper, as the first SoK of NFT security, has systematically explored the security issues within the NFT ecosystem, shedding light on their root causes, real-world attacks, and potential ways to address them. Our findings will contribute to the future research of NFT security.

cs.CR↗

arXiv2023

WASMixer: Binary Obfuscation for WebAssembly

WebAssembly (Wasm) is an emerging binary format that draws great attention from our community. However, Wasm binaries are weakly protected, as they can be read, edited, and manipulated by adversaries using either the officially provided readable text format (i.e., wat) or some advanced binary analysis tools. Reverse engineering of Wasm binaries is often used for nefarious intentions, e.g., identifying and exploiting both classic vulnerabilities and Wasm specific vulnerabilities exposed in the binaries. However, no Wasm-specific obfuscator is available in our community to secure the Wasm binaries. To fill the gap, in this paper, we present WASMixer, the first general-purpose Wasm binary obfuscator, enforcing data-level (string literals and function names) and code-level (control flow and instructions) obfuscation for Wasm binaries. We propose a series of key techniques to overcome challenges during Wasm binary rewriting, including an on-demand decryption method to minimize the impact brought by decrypting the data in memory area, and code splitting/reconstructing algorithms to handle structured control flow in Wasm. Extensive experiments demonstrate the correctness, effectiveness and efficiency of WASMixer. Our research has shed light on the promising direction of Wasm binary research, including Wasm code protection, Wasm binary diversification, and the attack-defense arm race of Wasm binaries.

cs.CR↗

arXiv2023

Abusing the Ethereum Smart Contract Verification Services for Fun and Profit

Smart contracts play a vital role in the Ethereum ecosystem. Due to the prevalence of kinds of security issues in smart contracts, the smart contract verification is urgently needed, which is the process of matching a smart contract's source code to its on-chain bytecode for gaining mutual trust between smart contract developers and users. Although smart contract verification services are embedded in both popular Ethereum browsers (e.g., Etherscan and Blockscout) and official platforms (i.e., Sourcify), and gain great popularity in the ecosystem, their security and trustworthiness remain unclear. To fill the void, we present the first comprehensive security analysis of smart contract verification services in the wild. By diving into the detailed workflow of existing verifiers, we have summarized the key security properties that should be met, and observed eight types of vulnerabilities that can break the verification. Further, we propose a series of detection and exploitation methods to reveal the presence of vulnerabilities in the most popular services, and uncover 19 exploitable vulnerabilities in total. All the studied smart contract verification services can be abused to help spread malicious smart contracts, and we have already observed the presence of using this kind of tricks for scamming by attackers. It is hence urgent for our community to take actions to detect and mitigate security issues related to smart contract verification, a key component of the Ethereum smart contract ecosystem.

cs.CR↗

arXiv2023

A Deep Dive into NFT Rug Pulls

NFT rug pull is one of the most prominent type of scam that the developers of a project abandon it and then run away with investors' funds. Although they have drawn attention from our community, to the best of our knowledge, the NFT rug pulls have not been systematically explored. To fill the void, this paper presents the first in-depth study of NFT rug pulls. Specifically, we first compile a list of 253 known NFT rug pulls as our initial ground truth, based on which we perform a pilot study, highlighting the key symptoms of NFT rug pulls. Then, we enforce a strict rule-based method to flag more rug pulled NFT projects in the wild, and have labelled 7,487 NFT rug pulls as our extended ground truth. Atop it, we have investigated the art of NFT rug pulls, with kinds of tricks including explicit ones that are embedded with backdoors, and implicit ones that manipulate the market. To release the expansion of the scam, we further design a prediction model to proactively identify the potential rug pull projects in an early stage ahead of the scam happens. We have implemented a prototype system deployed in the real-world setting for over 5 months. Our system has raised alarms for 7,821 NFT projects, by the time of this writing, which can work as a whistle blower that pinpoints rug pull scams timely, thus mitigating the impacts.

cs.CR↗