Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM68185
Volume:
10 |
10 |
Oct 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of computer science
Chikitsak Samuha's Sir Sitaram and Lady Shantabai Patkar College of Arts and Science and V. P. Varde College of Commerce and Economics, (Empowered Autonomous) Affiliated to University of Mumbai
Cloud-native software delivery pipelines are becoming more complex in orchestrating source code repositories, automated container building, third party dependencies, vulnerability scanners with diverse capabilities, and deployment clusters. Although such automation allows for increased delivery velocity, it often introduces significant software supply chain vulnerabilities because the security information is scattered among disparate tools. In this paper, we introduce DeployHub AI, a DevSecOps orchestration platform designed for orchestrating container compiling, multi-tool security scanning, findings schema normalization, artificial intelligence-assisted findings interpretation, deterministic policy gating, Kubernetes deployment, and cluster monitoring in one process. The system consists of Next.js web console, Go-based orchestration control plane, PostgreSQL for transactional storage, Redis for asynchronous task queues, Docker BuildKit for isolated building, Helm for Kubernetes rollouts, and security multi-engine core consisting of Trivy, Semgrep, Gitleaks, Syft, and Grype engines. The Hugging Face inference layer is used solely for advisory interpretation, making sure that deterministic policy gating and scanner evidence are always authoritative in terms of deployment gating. For establishing scientific rigor of the experimental prototype, in this paper we define a structured delivery process and evaluation framework covering build reliability, normalization fidelity, schema validity, policy correctness, and deployment rollbacks traceability.
KEYWORDS
DeployHub AI is a cohesive DevSecOps system that integrates the power of artificial intelligence in bridging the gap in operational execution from containerized application delivery to software supply chain security. Through its implementation of build sandbox isolation, multi-scan normalization of vulnerabilities, deterministic policy enforcement, schema validation of remediation advice, and Kubernetes automation, DeployHub AI delivers a comprehensive solution for deploying applications in the cloud environment securely. The design of the solution to have a clear demarcation between generative intelligence in terms of advice and deterministic enforcement provides a sound approach to utilizing AI responsibility. Future work would involve the completion of full laboratory testing on the proposed evaluation aspects as well as the addition of cryptographic signing of artifacts using Sigstore Cosign, in-toto supply chain attestations, policy enforcement through Open Policy Agent (OPA) and Kyverno, and distributed tracing using OpenTelemetry.
[1] OWASP Foundation, "Software Supply Chain Security," OWASP Cheat Sheet Series, 2026. [Online]. Available: https://cheatsheetseries.owasp.org/cheatsheets/Software_Supply_C hain_Security_Cheat_Sheet.html [2] K. I. Mohammed, B. Shanmugam, and J. El-Den, "Evolution of DevSecOps and Its Influence on Application Security: A Systematic Literature Review," Technologies, vol. 13, no. 12, art. no. 548, 2025. DOI: 10.3390/technologies13120548 [3] R. N. Rajapakse, M. Zahedi, M. A. Babar, and H. Shen, "Challenges and solutions when adopting DevSecOps: A systematic review," Information and Software Technology, vol. 141, art. no. 106700, 2022. DOI: 10.1016/j.infsof.2021.106700 [4] K. Scarfone, M. Souppaya, and D. Dodson, "Secure Software Development Framework (SSDF) Version 1.1: Recommendations for Mitigating the Risk of Software Vulnerabilities," NIST SP 800-218, National Institute of Standards and Technology, 2022. DOI: 10.6028/NIST.SP.800-218 [5] B. M. Reichert and R. R. Obelheiro, "Software supply chain security: a systematic literature review," International Journal of Computers and Applications, vol. 46, no. 10, pp. 853–867, 2024. DOI: 10.1080/1206212X.2024.2390978 [6] D. Anjaria and M. Kulkarni, "Effective DevSecOps Implementation: A Systematic Literature Review," Cardiometry, no. 24, pp. 410–417, 2022. DOI: 10.18137/cardiometry.2022.24.410417 [7] P. Martínez-Moreno, J. A. Vergara-Camacho, V. A. Lueváno-Mondragón, and K. A. Jiménez-Martínez, "DevSecOps for Secure Software Development: A Systematic Literature Review of Practices, Benefits, and Adoption Barriers," Int. J. of Combinatorial Optimization Problems and Informatics, vol. 17, no. 4, 2026. DOI: 10.61467/2007.1558.2026.v17i4.1299 [8] OWASP Foundation, "OWASP Top 10 CI/CD Security Risks," OWASP Project, 2026. [Online]. Available: https://owasp.org/projects/top-10-cicd-security-risks [9] OWASP Foundation, "A08:2025 Software and Data Integrity Failures," OWASP Top 10 Application Security Risks, 2025. [Online]. Available: https://top10.owasp.org/2025/A08_2025-Software_or_Data_Integrity_Failures/ [10] Kubernetes Authors, "Deployments and Workload Controllers," Kubernetes Documentation, 2026. [Online]. Available: https://kubernetes.io/docs/concepts/workloads/controllers/deployme nt/
Publication Date
10/22/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
1
Total views since publication
PDF Downloads
6
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...