CVE-based security audit of open-source learning management systems in higher education using CVSS and OWASP
Melissa T. Guillermo, Eduardo R. Yu II & Reagan B. Ricafort
Abstract
This study examined publicly disclosed Common Vulnerabilities and Exposures (CVE) records for Moodle, Chamilo, Canvas LMS, Open edX, and Sakai to assess their value for higher education security governance. A non-intrusive secondary-data audit analyzed 236 CVEs from 2018 to 3 June 2026 using platform, National Vulnerability Database (NVD) Published Date year, revised CVSS severity categories, and OWASP Top 10:2021 classifications. Six zero-score records were separated from low severity. A sensitivity analysis compared the full corpus with 211 NVD API-verified records. A blinded independent IT-faculty coder recoded 24 records; severity agreement was 100.0% (Cohen's kappa = 1.000), and OWASP agreement was 91.7% (Cohen's kappa = 0.814). Moodle and Chamilo represented 91.5% of the corpus, a disclosure-weighted pattern rather than a product ranking. A03 Injection (54.2%) and A01 Broken Access Control (31.4%) dominated. Among records with numeric CVSS scores, including six zero-score records, high/critical proportions were 45.3% (67/148) in the full corpus and 44.9% (66/147) in the NVD-verified subset. Canvas and Sakai findings were interpreted cautiously because of small denominators. Public CVE evidence is affected by disclosure asymmetry, incomplete CVSS metadata, NVD non-returned records, and deployment differences. Because identifiable CVSS version/vector metadata were not preserved, severity comparisons are descriptive rather than version-normalized. The audit offers a reproducible governance framework linking vulnerability patterns to patching, authorization review, content-ingestion controls, plugin governance, and supplier accountability without treating raw CVE counts as inherent security rankings.
Keywords
cybersecurity governance, common vulnerabilities and exposures, cybersecurity, vulnerability assessment, OWASP, web application security
Author information & Contribution
Melissa T. Guillermo. Corresponding author. Master of Science in Computer Science. Assistant Professor I, Dr. Filemon C. Aguilar Memorial College of Las Piñas, Las Piñas City, Philippines. Email: mrenrose@gmail.com
Eduardo R. Yu II. Doctor of Information Technology, Licensed Professional Teacher, software engineer, and part-time faculty member. AMA University, Philippines. Email: eduardoryuii@gmail.com
Reagan B. Ricafort. Doctor of Information Technology. Professor/faculty member, AMA University, Philippines. Email: reagan072001@gmail.com
"Melissa T. Guillermo conceptualized the study, curated the dataset, performed the formal analysis, and drafted the manuscript. Reagan B. Ricafort and Eduardo R. Yu II reviewed the methodology, validated the analysis, revised the manuscript for important intellectual content, and supported project administration. All authors contributed to the final version of the manuscript, read and approved the final manuscript, and agree to be accountable for the accuracy and integrity of the work."
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work was not supported by any funding.
Institutional Review Board Statement
Not Applicable
Data and Materials Availability
The data supporting the findings of this study are available from the corresponding author upon reasonable request.
AI Declaration
The authors declare the use of Artificial Intelligence (AI) in preparing this paper. In particular, the authors used ChatGPT for grammar checking, language clarity, low-intervention paraphrasing, formatting review, and consistency checking of manuscript sections. The tool was not used to fabricate data, generate the CVE dataset, create unsupported findings, or replace the authors’ interpretation of the results. Python was also used as a research-support and data-processing tool for organizing the CVE dataset, checking record counts, computing descriptive statistics and percentages, preparing tables, and generating figures used in the manuscript. The authors take full responsibility for reviewing, verifying, and editing all AI-assisted and software-supported outputs.
Notes
Acknowledgement
References
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Cite this article:
Guillermo, M.T., Yu, E.R. & Ricafort, R.B. (2026). CVE-based security audit of open-source learning management systems in higher education using CVSS and OWASP. International Journal of Science, Technology, Engineering and Mathematics, 6(3), 1-26. https://doi.org/10.53378/ijstem.353374
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This work is licensed under a Creative Commons Attribution (CC BY 4.0) International License.
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