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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66727
Volume:
10 |
8 |
Aug 2026
Pages:
1-32
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
Jamia Hamdard
Department of computer science
Jamia Hamdard
The rapid digitization of organizational operations has exponentially expanded the attack surface for cyber threats, making cybersecurity a critical concern for enterprises of all sizes. This review paper comprehensively analyzes the landscape of security vulnerabilities prevalent in modern organizations and proposes a multi-layered security framework for robust system protection. The study begins with an extensive examination of common vulnerability categories including weak authentication mechanisms, misconfigured systems, unpatched software, and insider threats. Through a systematic review of literature spanning industry standards (ISO/IEC 27001, NIST Cybersecurity Framework, CIS Controls), vulnerability assessment tools (Nessus, OpenVAS, Qualys, CrowdStrike Falcon), and emerging security paradigms (Zero Trust Architecture, DevSecOps, SIEM/SOAR), this paper identifies critical gaps in current organizational security postures. The research questions address the identification of prevalent vulnerabilities, the effectiveness of assessment tools, mitigation strategies, and framework design principles. A detailed proposed framework is presented, encompassing vulnerability assessment, risk analysis using CVSS, security controls implementation, continuous monitoring and response, and user awareness programs. The framework aligns with established standards while addressing identified research gaps, particularly in automated vulnerability detection integration, SME security challenges, and continuous monitoring implementation. Case studies illustrate practical application across different organizational scales. Expected outcomes include improved threat detection capabilities, reduced incident response times, and enhanced overall security maturity. Limitations include dependence on secondary data and the generalized nature of the framework. Future research directions emphasize AI-driven vulnerability management, cloud-native security integration, and adaptive threat intelligence systems. This paper contributes to the academic discourse by synthesizing contemporary security practices into a coherent, implementable framework suitable for diverse organizational contexts.
KEYWORDS
• CVSS is Industry Standard: CVSS provides consistent prioritization across organizations and tools, and organizations should use it. • CVSS has Limitations: Its context-agnostic, exploitability-focused nature requires supplementation with organizational context, threat intelligence, and asset criticality. • Risk-Based Vulnerability Management is Superior: RBVM enhances CVSS with additional context, providing more accurate risk prioritization. • Environmental Metrics are Underutilized: Organizations should use environmental metrics for more accurate, organization-specific scoring. • CVSS v4.0 Provides Enhancements: Organizations should consider adopting CVSS v4.0 for its new metric groups and improved context.
• CVSS is Industry Standard: CVSS provides consistent prioritization across organizations and tools, and organizations should use it. • CVSS has Limitations: Its context-agnostic, exploitability-focused nature requires supplementation with organizational context, threat intelligence, and asset criticality. • Risk-Based Vulnerability Management is Superior: RBVM enhances CVSS with additional context, providing more accurate risk prioritization. • Environmental Metrics are Underutilized: Organizations should use environmental metrics for more accurate, organization-specific scoring. • CVSS v4.0 Provides Enhancements: Organizations should consider adopting CVSS v4.0 for its new metric groups and improved context.
Publication Date
8/13/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
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