library(shodan)
library(ggplot2)
library(xtable)
library(maps)
library(rworldmap)
library(ggthemes)


# if you're behind a proxy, setting this will help
# but it's strongly suggested/encouraged that you stick the values in a file and 
# read them in vs paste them in a script
# options(RCurlOptions = list(proxy="host:port", proxyuserpwd="user:pass"))

setSHODANKey("~/.shodankey")

# query example taken from Michael “theprez98” Schearer's DEFCON 18 presentation
# https://www.defcon.org/images/defcon-18/dc-18-presentations/Schearer/DEFCON-18-Schearer-SHODAN.pdf

# find all Cisco IOS devies that may have an unauthenticated admin login
# setting trace to be TRUE to see the progress of the query
result = SHODANQuery(query="cisco last-modified www-authenticate",trace=TRUE)

#find the first 100 found memcached instances
#result = SHODANQuery(query='port:11211',limit=100,trace=TRUE)

df = result$matches

# aggregate result by operating system
# you can use this one if you want to filter out NA's completely
#df.summary.by.os = ddply(df, .(os), summarise, N=sum(as.numeric(factor(os))))
#this one provides count of NA's (i.e. unidentified systems)
df.summary.by.os = ddply(df, .(os), summarise, N=length(os))

# sort & see the results in a text table
df.summary.by.os = transform(df.summary.by.os, os = reorder(os, -N))
df.summary.by.os

# plot a bar chart of them
(ggplot(df.summary.by.os,aes(x=os,y=N,fill=os)) + 
   geom_bar(stat="identity") + 
   theme_few() +
   labs(y="Count",title="SHODAN Search Results by OS"))

# generate a PDF world map of locations of the devices (PDFs are nice & scaleable)
# using the ggplot2 polygon & point method
world = map_data("world")
(ggplot() +
   geom_polygon(data=world, aes(x=long, y=lat, group=group)) +
   geom_point(data=df, aes(x=longitude, y=latitude), colour="#EE760033",size=1.75) +
   labs(x="",y="") +
   theme_few())

# sort & view the results by country
# see above if you don't want to filter out NA's
df.summary.by.country_code = ddply(df, .(country_code, country_name), summarise, N=sum(!is.na(country_code)))
df.summary.by.country_code = transform(df.summary.by.country_code, country_code = reorder(country_code, -N))

df.summary.by.country_code

(ggplot(df.summary.by.country_code,aes(x=country_code,y=N)) + 
  geom_bar(stat="identity") +
  theme_few() +
  labs(y="Count",x="Country",title="SHODAN Search Results by Country"))

# except make a choropleth
# using the very simple rworldmap process
shodanChoropleth = joinCountryData2Map( df.summary.by.country_code, joinCode = "ISO2", nameJoinColumn = "country_code")
par(mai=c(0,0,0.2,0),xaxs="i",yaxs="i")
mapCountryData(shodanChoropleth, nameColumnToPlot="N",colourPalette="terrain",catMethod="fixedWidth" )