Exploratory Analysis of vFeed Correlated Vulnerability And Threat Database

Git Hub Repo For My App

Background Summary

This Shiny App is for searching and visualizing vFeed fully aggregated, cross-linked and standardized Vulnerability CVE Database that contains detective and preventive security information repository used for gathering vulnerability and mitigation data on the internet. The data set is from Toolswatch.org Github

There are six metrics used to calculate the exploitability and impact sub-scores of the vulnerability.: - Access Vector – Access Complexity - Authentication – Confidentiality - Integrity – Availability

These sub-scores are used to calculate the overall base score.

Database Synopsis

library(sqldf);library(reshape2);library(rCharts)
db <- dbConnect(SQLite(), dbname="./vFeed.db" )
STATS <-dbReadTable(db, dbListTables(db)[42])
vfeedStats <- melt(STATS)
vfeedStats <- vfeedStats[-c(1,3),]
names(vfeedStats)[1]<-"Titles"
names(vfeedStats)[2]<-"Count"
p1<-rPlot(Count~Titles,color = 'Titles',data = vfeedStats,type = 'bar')
p1$guides(color = list(numticks = length((vfeedStats[,1]))),
          x = list(title="Titles", ticks = ''),
          y = list(title="Count")
)
p1$addParams(width = 1000, height = 650, title = "Title")

The database has a total of 42 tables. I used 5 tables( table[4], table[8], table[9],table[40], table[42] ) out of the 43 tables.

List of Tables and Row Count

vFeed Application

• Click to Load CWE Titles this shiny does not load data right away. Continue to navigate site CWE Titles are being loaded.
• Dashboard to see six metrics used to calculate the exploitability and impact sub-scores of the vulnerability for selected years and risk score.
• Click to View CVE Category to see General CVEs and Web Application related CVEs.
• Selections You can clear all titles and select only those you want to view.

Enjoy!!!!