Bytecode-centric Detection of Known-to-be-vulnerable Dependencies in Java Projects

• URL: http://arxiv.org/abs/2510.19393v1
• Date: Wed, 22 Oct 2025 09:08:46 GMT
• Title: Bytecode-centric Detection of Known-to-be-vulnerable Dependencies in Java Projects
• Authors: Stefan Schott, Serena Elisa Ponta, Wolfram Fischer, Jonas Klauke, Eric Bodden,
• Abstract summary: We present Jaralyzer, a bytecode-centric dependency scanner for Java.<n>Jaralyzer does not rely on the metadata or the source code of the included OSS dependencies being available but directly analyzes a dependency's bytecode.<n>It is the only scanner capable of identifying vulnerabilities across all the above mentioned types of modifications.
• Score: 2.337931591219808
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: On average, 71% of the code in typical Java projects comes from open-source software (OSS) dependencies, making OSS dependencies the dominant component of modern software code bases. This high degree of OSS reliance comes with a considerable security risk of adding known security vulnerabilities to a code base. To remedy this risk, researchers and companies have developed various dependency scanners, which try to identify inclusions of known-to-be-vulnerable OSS dependencies. However, there are still challenges that modern dependency scanners do not overcome, especially when it comes to dependency modifications, such as re-compilations, re-bundlings or re-packagings, which are common in the Java ecosystem. To overcome these challenges, we present Jaralyzer, a bytecode-centric dependency scanner for Java. Jaralyzer does not rely on the metadata or the source code of the included OSS dependencies being available but directly analyzes a dependency's bytecode. Our evaluation across 56 popular OSS components demonstrates that Jaralyzer outperforms other popular dependency scanners in detecting vulnerabilities within modified dependencies. It is the only scanner capable of identifying vulnerabilities across all the above mentioned types of modifications. But even when applied to unmodified dependencies, Jaralyzer outperforms the current state-of-the-art code-centric scanner Eclipse Steady by detecting 28 more true vulnerabilities and yielding 29 fewer false warnings.

Related papers

• Uncovering Hidden Inclusions of Vulnerable Dependencies in Real-World Java Projects [2.337931591219808]
  We present Unshade, a hybrid approach towards dependency scanning in Java.<n>It combines the efficiency of metadata-based scanning with the ability to detect modified dependencies of code-centric approaches.<n>We conducted a large-scale study of the 1,808 most popular open-source Java Maven projects on GitHub.
  arXiv  Detail & Related papers  (2026-01-30T14:30:04Z)
• A Comprehensive Study on the Impact of Vulnerable Dependencies on Open-Source Software [0.2772895608190934]
  We conducted a study on over 1k open-source software projects with about 50k releases comprising several languages such as Java, Python, Rust, Go, Ruby, and JavaScript.<n>Our objective is to investigate the severity, persistence, and distribution of these vulnerabilities, as well as their correlation with project metrics such as team and contributors size, activity and release cycles.<n>Using our approach, we can provide information such as library versions, dependency depth, and known vulnerabilities, and how they evolved over the software development cycle.
  arXiv  Detail & Related papers  (2025-12-03T15:20:10Z)
• What Do They Fix? LLM-Aided Categorization of Security Patches for Critical Memory Bugs [46.325755802511026]
  We developLM, a dual-method pipeline that integrates two approaches based on a Large Language Model (LLM) and a fine-tuned small language model.<n>LM successfully identified 111 of 5,140 recent Linux kernel patches addressing OOB or UAF vulnerabilities, with 90 true positives confirmed by manual verification.
  arXiv  Detail & Related papers  (2025-09-26T18:06:36Z)
• Decompiling Smart Contracts with a Large Language Model [51.49197239479266]
  Despite Etherscan's 78,047,845 smart contracts deployed on (as of May 26, 2025), a mere 767,520 ( 1%) are open source.<n>This opacity necessitates the automated semantic analysis of on-chain smart contract bytecode.<n>We introduce a pioneering decompilation pipeline that transforms bytecode into human-readable and semantically faithful Solidity code.
  arXiv  Detail & Related papers  (2025-06-24T13:42:59Z)
• Discovery of Timeline and Crowd Reaction of Software Vulnerability Disclosures [47.435076500269545]
  Apache Log4J was found to be vulnerable to remote code execution attacks. More than 35,000 packages were forced to update their Log4J libraries with the latest version. It is practically reasonable for software developers to update their third-party libraries whenever the software vendors have released a vulnerable-free version.
  arXiv  Detail & Related papers  (2024-11-12T01:55:51Z)
• An Overview and Catalogue of Dependency Challenges in Open Source Software Package Registries [52.23798016734889]
  This article provides a catalogue of dependency-related challenges that come with relying on OSS packages or libraries. The catalogue is based on the scientific literature on empirical research that has been conducted to understand, quantify and overcome these challenges.
  arXiv  Detail & Related papers  (2024-09-27T16:20:20Z)
• The Impact of SBOM Generators on Vulnerability Assessment in Python: A Comparison and a Novel Approach [56.4040698609393]
  Software Bill of Materials (SBOM) has been promoted as a tool to increase transparency and verifiability in software composition. Current SBOM generation tools often suffer from inaccuracies in identifying components and dependencies. We propose PIP-sbom, a novel pip-inspired solution that addresses their shortcomings.
  arXiv  Detail & Related papers  (2024-09-10T10:12:37Z)
• The Code the World Depends On: A First Look at Technology Makers' Open Source Software Dependencies [3.6840775431698893]
  Open-source software (OSS) supply chain security has become a topic of concern for organizations. Patching an OSS vulnerability can require updating other dependent software products in addition to the original package. We do not know what packages are most critical to patch, hindering efforts to improve OSS security where it is most needed.
  arXiv  Detail & Related papers  (2024-04-17T21:44:38Z)
• Empirical Analysis of Vulnerabilities Life Cycle in Golang Ecosystem [0.773844059806915]
  A comprehensive investigation was undertaken to examine the life cycle of vulnerability in Golang. It turned out that 66.10% of modules in the Golang ecosystem were affected by vulnerabilities. By analyzing reasons behind non-lagged and lagged vulnerabilities, timely releasing and indexing patch versions could significantly enhance ecosystem security.
  arXiv  Detail & Related papers  (2023-12-31T14:53:51Z)
• Dependency Practices for Vulnerability Mitigation [4.710141711181836]
  We analyze more than 450 vulnerabilities in the npm ecosystem to understand why dependent packages remain vulnerable. We identify over 200,000 npm packages that are infected through their dependencies. We use 9 features to build a prediction model that identifies packages that quickly adopt the vulnerability fix and prevent further propagation of vulnerabilities.
  arXiv  Detail & Related papers  (2023-10-11T19:48:46Z)
• On the Security Blind Spots of Software Composition Analysis [46.1389163921338]
  We present a novel approach to detect vulnerable clones in the Maven repository. We retrieve over 53k potential vulnerable clones from Maven Central. We detect 727 confirmed vulnerable clones and synthesize a testable proof-of-vulnerability project for each of those.
  arXiv  Detail & Related papers  (2023-06-08T20:14:46Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.