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Measuring the Security of the Evolving Software Supply Chain: a Research Agenda
Sarah Meriem Ourari
TL;DR
Software supply-chain measurement remains fragmented, with dependency resolution, transitive exposure, and reachability complicating comparisons across ecosystems. The paper outlines a research agenda combining a generalized measurement framework with reachability analysis and study of LLM-era dependency patterns; its synthesis identifies popular packages and influential maintainers as structural risk patterns.
Problem
Fragmented, ecosystem-specific approaches and difficulty modeling transitive dependencies and real-world reachability limit comparable cross-ecosystem risk assessment.
Source: §I · p. 1Method
The agenda proposes a generalized cross-ecosystem measurement framework, source-code reachability analysis, and an extension to study LLM-generated dependencies and temporal ecosystem changes.
Source: §I · p. 1, C. Design of a generalized measurement… · p. 5, D. LLM-driven code generation and… · p. 5Results
The synthesis identifies popular packages as high-impact attack surfaces and a small number of influential maintainers as affecting large portions of ecosystems.
Source: A. Ecosystem risk dynamics and… · p. 2Takeaways & Limitations
The proposed research would examine dependency structures and vulnerability exposure consistently across ecosystems while accounting for reachable transitive vulnerabilities and emerging LLM-related patterns.
Source: §I · p. 1, D. LLM-driven code generation and… · p. 5
Abstract
from arXiv · showhide
Software supply chain security has become increasingly critical due to the widespread reliance on third-party dependencies and the growing attack surface of modern software ecosystems. However, existing quantitative, measurement-based analysis and vulnerability management approaches remain largely fragmented and ecosystem-specific, limiting their ability to provide comparable risk assessments across environments. This paper presents a structured research plan, starting with a Systematization of Knowledge (SoK) to synthesize the current state of research and identify key gaps, highlighting the limitations in dependency modeling and vulnerability propagation analysis, particularly in the treatment of transitive dependencies and their real-world exploitability. Based on these insights, we argue for a unified measurement perspective capable of consistently representing and analyzing the cross-ecosystem dependency structure. We further identify emerging challenges introduced by AI-assisted software development, where coding LLMs are likely to contribute to new dependency patterns that are not captured by traditional Software Composition Analysis (SCA) tools. These shifts motivate a rethink of dependency modeling to account for evolving software-generation practices and their long-term structural impact on software security.
I. INTRODUCTION
The introduction identifies fragmented, ecosystem-specific measurement and unresolved transitive-dependency and reachability challenges. It proposes a generalized cross-ecosystem measurement agenda that also investigates dependency patterns associated with LLM-assisted development.
I. INTRODUCTION
- The software supply chain spans an application's lifecycle from upstream development through downstream operations, requiring security practices across code generation and artifact delivery.Examples include secure coding, vulnerability scanning, and dependency validation.Source: §I · p. 1
- Existing approaches are fragmented and ecosystem-specific, while transitive-risk analysis and SCA dependency resolution, execution, and reachability remain challenging.These limitations make cross-ecosystem comparison and risk assessment difficult.Source: §I · p. 1
- AI-generated code may introduce novel dependency relationships that existing measurement and modeling methods may need to adapt to capture.The agenda asks how such dependencies arise and how patterns changed after LLM-assisted development became widespread.Source: §I · p. 1
- The research agenda proposes a generalized framework for measuring software security across multiple ecosystems and addressing gaps in dependency modeling and vulnerability analysis.Its questions cover the state of the art, unified dependency-graph measurement, and source-code reachability for transitive vulnerabilities.Source: §I · p. 1
II. STATE OF THE ART1
The state-of-the-art review gathers and filters research on quantifiable ecosystem security, dependency analysis, and vulnerability management. It uses bibliometric visualization and thematic categories to organize the selected literature.
II. STATE OF THE ART1
- The review selected recent scientific research on quantifiable ecosystem security, dependency analysis, and vulnerability management, excluding non-scientific and low-quality sources.Sources included IEEE Xplore, ACM Digital Library, SpringerLink, Google Scholar, and Web of Science; the review is described as condensed, with a full-length SoK under submission.Source: §II · p. 2
- Citation graphs built with VOSviewer and CiteNet Explorer visualize relationships among papers, influential works, and citation patterns.The resulting VOSviewer graph is shown in Figure 2.Source: §II · p. 2
- The selected literature is grouped into ecosystem and software metrics, SCA tools, vulnerability mitigation and patching, and dependency-graph structure and management.These categories frame the review's synthesis of findings.Source: §II · p. 2
A. Ecosystem risk dynamics and dependency metrics
The reviewed studies identify structural risk around popular packages and influential maintainers, while documenting ecosystem-specific vulnerability and remediation patterns. They also connect maintenance bottlenecks with attack vectors and the effectiveness of dependency updates.
A. Ecosystem risk dynamics and dependency metrics
- Popular packages create high-impact attack surfaces, and a small number of influential maintainers affect large portions of software ecosystems.The review presents these as two convergent structural patterns.Source: A. Ecosystem risk dynamics and… · p. 2
- Zahan et al. report install scripts, unmaintained packages, and expired domains among attack vectors associated with overloaded maintainers; Rahman et al. [4] introduce dependency remediation and update-time metrics.Their quantitative findings indicate that dependency-update effectiveness reflects how well a package addresses vulnerabilities.Source: A. Ecosystem risk dynamics and… · p. 2
- Studies of npm and PyPI report mostly medium- or high-severity vulnerabilities, with XSS common, while patching and disclosure timing differ between ecosystems.Both studies identify indirect dependencies as increasing exposure and emphasize timely updates.Source: A. Ecosystem risk dynamics and… · p. 2
- Maven studies find recurring weaknesses involving input validation, access control, unencrypted data, and authentication, alongside relatively slow patching.The review notes a need for faster vulnerability discovery, reporting, and documentation.Source: A. Ecosystem risk dynamics and… · p. 3
B. Software Composition Analysis and reachability
The review describes SCA accuracy problems tied to dependency resolution, ecosystem characteristics, and execution reachability. It also reports developer responses to automated fixes and research using reachability and graph-based methods to refine vulnerability detection.
B. Software Composition Analysis and reachability
- SCA tools may miss inherited or incorrectly versioned packages, produce false positives, and overlook external references or copy-pasted code; results also depend on execution environment.The Scan Scope Maven concept defines dependencies for project analysis to reduce false positives and false negatives.Source: B. Software Composition Analysis and… · p. 3
- In more than half of examined cases, developers applied Dependabot fixes without major integration issues, while automated fixes were less frequent for major upgrades due to compatibility constraints.A cohort study also reported reduced vulnerability counts and severity for built projects using OWASP Dependency-Check.Source: B. Software Composition Analysis and… · p. 3
- Source-code reachability research finds that only a small percentage of identified vulnerable functions are reachable, contributing to unnecessary SCA alerts and updates.Some vulnerabilities are deeply embedded in dependency trees or require complex exploitation conditions.Source: B. Software Composition Analysis and… · p. 3
- Graph-based methods include a knowledge graph linking packages to vulnerabilities and an algorithm to reconstruct dependency graphs more accurately across repositories.The described approach improves execution efficiency through reduced runtime and simpler adaptation to heterogeneous repositories, at the cost of greater computational effort during dependency resolution.Source: B. Software Composition Analysis and… · p. 3
C. Vulnerability remediation and lifecycle principles
Prior work addresses vulnerability management through lifecycle-aware principles and automated remediation, while patch-to-vulnerability matching remains challenging.
C. Vulnerability remediation and lifecycle principles
- Iannone et al. call for vulnerability assessment to incorporate development timelines, developer actions, and contextual changes.Okafor et al. propose dependency transparency, component validity, and separation of development stages for ecosystem-wide analysis.Source: C. Vulnerability remediation and… · p. 3
- Ranger restores version ranges while preserving compatibility, reducing breaking-change risk and the persistence of security flaws.The system is described as automating version-range restoration.Source: C. Vulnerability remediation and… · p. 3
- PatchFinder uses semantic similarity and contextual code understanding to identify relevant patch commits, improving result reliability.Accurately linking vulnerabilities to their fixes remains challenging.Source: C. Vulnerability remediation and… · p. 3
D. Dependency graph construction and mining frameworks
Dependency graph research seeks more standardized and reusable analysis, but ecosystem-specific approaches and resolution costs complicate cross-study comparison.
D. Dependency graph construction and mining frameworks
- The Dependency Graph Mining Framework (DGMF) builds graphs from different repositories, with improved runtime and simpler adaptation but greater dependency-resolution computation.The passage identifies a trade-off between efficiency and computational effort.Source: D. Dependency graph construction and… · pp. 3–4
- Goblin reconstructs dependency graphs with temporal information for historical analysis and on-demand ecosystem metrics, while transitive dependencies raise metric-processing costs.Dataset size and structure, along with dependency updates and management, can also influence research outcomes.Source: D. Dependency graph construction and… · p. 4
- MARIN automates repetitive Maven analysis tasks using parallel processing, while inspect4py analyzes Python source structure and extracts software artifacts.The passage links repeated custom-tool building to duplicated effort, limited reuse, and abandoned or unmaintained artifacts.Source: D. Dependency graph construction and… · p. 4
- Most proposed solutions remain ecosystem-specific, making comparisons across studies difficult and motivating more comprehensive mitigation and management metrics.The passage describes limited generalizability as a problem for existing approaches.Source: D. Dependency graph construction and… · p. 4
III. LITERATURE SYNTHESIS AND RESEARCH QUESTIONS
The synthesis identifies ecosystem-specific measurement, transitive-dependency analysis, and AI-generated dependency patterns as research gaps. It formulates questions about unified measurement, reachability, and changes associated with LLM-assisted development.
III. LITERATURE SYNTHESIS AND RESEARCH QUESTIONS
- LLM adoption is presented as a source of new challenges and transformations for software development and security analysis.The synthesis calls for further investigation of its impact.Source: §III · p. 4
- Ecosystem-specific approaches constrain transfer across environments and keep evaluations tied to single-ecosystem datasets, limiting cross-ecosystem structural comparison.The synthesis calls for a unified measurement model for dependency graphs and vulnerability exposure across diverse ecosystems.Source: §III · p. 4
- Existing studies often emphasize direct dependencies, while transitive and third-party packages materially affect ecosystem security.RQ2 asks whether source-code-level reachability analysis can identify executable vulnerabilities in transitive dependencies and reduce alert fatigue.Source: §III · p. 4
- SCA tools can miss packages or include unrelated dependencies, and vulnerabilities in a dependency tree are not necessarily reachable during execution.CodeQL4 is described as a GitHub static-analysis engine for querying source code as a database.Source: §III · p. 4
- LLM-generated code may introduce new dependency forms and hidden source-level security risks, motivating research on how measurement and graph models should capture them.The proposed questions ask to what extent LLM-generated code introduces dependencies and how frameworks can be extended to represent them.Source: §III · p. 4
- The study proposes comparing dependency structures before and after widespread LLM adoption to examine changes in relationships, depth, and versioning practices.RQ4 frames this as a comparison across software ecosystems and pre-LLM and post-adoption periods.Source: §III · p. 5
IV. PROPOSED RESEARCH METHODOLOGY
The proposed research proceeds from literature synthesis to generalized measurement design and investigation of its applicability to software supply chain security.
IV. PROPOSED RESEARCH METHODOLOGY
- The methodology has three stages: literature review and state of the art, generalized measurement design, and investigation of applicability to supply chain security.The overall workflow is illustrated in Figure 3.Source: §IV · p. 5
A. Systematic literature review
The literature-review phase analyzes research on software system security, dependency management, and vulnerability mitigation through a SoK. It identifies gaps that inform research questions about generalizable ecosystem-level analysis.
A. Systematic literature review
- The review examines existing studies on software system security, dependency management, and vulnerability mitigation.Source: A. Systematic literature review · p. 5
- The review culminates in a SoK that analyzes the current research state, tools, and metrics.Source: A. Systematic literature review · p. 5
- Identified limitations and gaps lead to research questions focused on a more generalizable framework for ecosystem-level analysis.Source: A. Systematic literature review · p. 5
B. Data collection and ecosystem extraction
The research plan collects ecosystem data to build heterogeneous dependency networks, then explores a unified measurement framework for dependency-related risk and security exposure. It also proposes source-code reachability analysis to distinguish theoretical vulnerability exposure from real-world exploitability.
B. Data collection and ecosystem extraction
- Data from package managers, repositories, and dependency metadata APIs includes dependency graphs, version histories, release metadata, and vulnerability reports.The resulting heterogeneous dependency networks support static and temporal analysis.Source: B. Data collection and ecosystem… · p. 5
C. Design of a generalized measurement approach
- The proposed unified dependency graph captures direct and transitive relationships across heterogeneous ecosystems.Source: C. Design of a generalized measurement… · p. 5
- The framework is intended to quantify vulnerability exposure, dependency risk propagation, and ecosystem-level security impact across environments.Source: C. Design of a generalized measurement… · p. 5
- Source-code reachability analysis checks whether vulnerabilities in transitive dependencies are executable, distinguishing theoretical exposure from real exploitability.The mechanism aims to reduce alert fatigue.Source: C. Design of a generalized measurement… · p. 5
D. LLM-driven code generation and ecosystem evolution analysis
The plan investigates how LLM-assisted development introduces dependency patterns and how ecosystem structures change over time. It is motivated by the literature review's finding that generalized ecosystem-level security measurement is absent.
D. LLM-driven code generation and ecosystem evolution analysis
- The study analyzes LLM-generated code for implicit, redundant, or non-explicit package dependencies and extends its framework to capture these patterns.The extension may use probabilistic graphical models.Source: D. LLM-driven code generation and… · p. 5
- A temporal analysis compares dependency structures before and after widespread adoption of LLM-assisted development tools.It examines dependency density, transitive depth, and vulnerability exposure patterns across ecosystems over time.Source: D. LLM-driven code generation and… · p. 5