Authors : Aakarsh Mavi

Volume/Issue : Volume 10 - 2025, Issue 7 - July

Google Scholar : https://tinyurl.com/4tfm7suj

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DOI : https://doi.org/10.38124/ijisrt/25jul1858

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Abstract : As supply chain networks become more complex, they’re also becoming more vulnerable to cybersecurity threats. To stay secure, organizations need more than just automated tools that fix issues—they need systems that can constantly monitor their environment, report on compliance, and evolve with new threats. While most traditional security automation frameworks focus on enforcing policies and patching vulnerabilities, they often fall short when it comes to real-time visibility and ongoing improvement. This paper builds on the existing SecAuto Toolkit [5] by introducing three critical additions: Monitoring, Reporting, and Continuous Improvement layers. These new components ensure that security events are tracked in real time, compliance with standards is automatically verified, and the system can adapt as new threats emerge. Additionally, integrating Software Bills of Materials (SBOMs) into the supply chain security process has proven essential for identifying vulnerabilities in third- party components and maintaining transparency in software dependencies. [9] The enhanced framework combines Ansible automation with SIEM tools, compliance dashboards, and machine learning to deliver proactive and intelligent threat management. Designed specifically for supply chain environments, this approach helps organizations stay secure by providing real-time insights, automating audits, and continuously refining their security posture over time.

Keywords : Cybersecurity, Supply Chain, Ansible, Nist, Siem, Compliance, Automation, Continuous Improvement.

References :

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5. Talwar, S., & Mavi, A. (2023). SECAUTO TOOLKIT - HARNESSING ANSIBLE FOR ADVANCEDSECURITY AUTOMATION. International Journal of Applied Engineering & Technology, 5(5S), 2478–2491. https://romanpub.com/resources/Vol.%205%20No.%20S5%20(Sep%20-%20Oct%202023)%20-%2013.pdf
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10. Osha Shukla, 2025, Enhancing Threat Intelligence and Detection with Real-Time Data Integration, IJERT, Vol. 14, Issue 04. https://www.ijert.org/research/enhancing-threat-intelligence-and-detection-with-real-time-data-integration-IJERTV14IS040201.pdf