Design and Implementation of Distributed Web Application Vulnerability Assessment Tools for Securing Complex Microservices Environment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Modern web applications with complex distributed architectures present significant challenges in vulnerability assessment that traditional approaches fail to address effectively.This research introduces the Distributed Vulnerability Management System (DVMS), implementing a multi-agent architecture to enhance vulnerability detection while eliminating single points of failure.The methodology employs the Nuclei vulnerability scanner across five Open Web Application Security Project (OWASP) security domains, expanding beyond conventional vulnerabilities to include Security Misconfiguration, Vulnerable Components, and Sensitive Data Exposure.Experimental results demonstrate detection accuracies of 80% for Injection, 85.71% for XSS, 80% for Security Misconfiguration, 50% for Vulnerable Components, and 90.91% for Sensitive Data Exposure.The distributed architecture enables parallel processing and optimizes security resource allocation across network infrastructures.While showing promising results in comprehensive security coverage, the system identifies areas for future enhancement in detection accuracy and vulnerability scope expansion.This research contributes a scalable, distributed approach to vulnerability management particularly suited for modern web applications, providing organizations with enhanced security assessment capabilities in complex technological environments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it