An Integrated Security Analysis Model for Identifying Software and Hardware System Vulnerabilities
Abstract
The increasing interdependence of software, hardware, cloud infrastructures, embedded platforms, and connected systems has transformed cybersecurity vulnerability assessment from an isolated technical activity into a multidimensional security requirement. Software vulnerabilities can arise from insecure code, configuration weaknesses, vulnerable dependencies, and exploitable application interfaces, whereas hardware vulnerabilities may originate from architectural design limitations, processor-level weaknesses, implementation flaws, and hardware-assisted attack mechanisms. This study develops an integrated security analysis model for identifying vulnerabilities across software and hardware system layers. The proposed approach synthesizes vulnerability taxonomy, attack-surface analysis, risk assessment, exploitability evaluation, hardware security analysis, machine-learning-assisted detection, and adaptive defensive mechanisms. The methodology is conceptually grounded in the supplied literature and uses a layered assessment process to connect vulnerability discovery with exploitability, potential impact, and mitigation priority. Particular attention is given to base-image vulnerabilities, processor-level attacks, artificial-intelligence-supported security analysis, HTTPS deployment weaknesses, embedded-system risks, and cyber-hunting relationships between threats and defensive weaknesses. The analysis indicates that isolated software or hardware assessment can overlook cross-layer attack paths, while an integrated model provides stronger contextual understanding of vulnerabilities and their operational consequences. The study further identifies the need for risk-oriented prioritization, continuous monitoring, and coordinated software-hardware defenses. The proposed model provides a conceptual foundation for systematic vulnerability assessment in heterogeneous computing environments.
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