Research Paper on HESS: An Endpoint Security Tool

In the current rapidly evolving digital landscape, cybersecurity has shifted from being a luxury for large scale corporations to an absolute survival necessity for Micro, Small, and Medium Enterprises (MSMEs). These smaller organizations are frequently targeted by automated cyberthreats because they lack the high budget security infrastructure and specialized human resources required for continuous monitoring. This thesis presents the development of HESS (Host Endpoint Security Scanner), a centralized, agent based security scanning ecosystem designed to eliminate the common "visibility gaps" in distributed office networks. The core research addresses the inefficiency of manual security audits by introducing a Distributed System Architecture. In this framework, lightweight Python agents are deployed across multiple Windows endpoints to communicate with a central FastAPI based orchestration server. Unlike traditional scanners that focus solely on malware, HESS performs a multi dimensional audit of the host s security posture, including Windows Firewall configurations, critical Network port exposures (such as RDP and SMB), hardware level hardening (BitLocker, TPM, and Secure Boot), and Identity hygiene (blank passwords and administrative privilege c ounts). A key contribution of this project is the Automated Risk Scoring Engine, which translates complex, raw technical data into a simplified 0 100 Security Posture Score. This allows nontechnical administrators to immediately identify high risk assets w ithin their network. Furthermore, the system ensures data integrity through HMAC (Hash based Message Authentication Code) verification, preventing unauthorized or spoofed scan results.The research culminates in the automated generation of structured Excel and PDF reports that provide clear remediation steps, effectively bridging the compliance gap for regulations such as provide clear remediation steps, effectively bridging the compliance gap for regulations such as the DPDP Act 2023 and CERT In guidelines. Practical testing in a c ontrolled LAN environment demonstrates that HESS significantly reduces audit time while providing a production grade, scalable solution for enterprise level endpoint hardening A key contribution of this project is the Automated Risk Scoring Engine , which translates complex, raw technical data into a simplified 0 100 Security Posture Score. This allows nontechnical administrators to immediately identify high risk assets within their network. Furthermore, the system ensures data integrity through HMAC (Hash based Message Authentication Code) verification, preventing unauthorized or spoofed scan results.