MINI MINI MANI MO
#!/usr/bin/env lua
require("io");
function table.val_to_str ( v )
if "string" == type( v ) then
v = string.gsub( v, "\n", "\\n" )
if string.match( string.gsub(v,"[^'\"]",""), '^"+$' ) then
return "'" .. v .. "'"
end
return '"' .. string.gsub(v,'"', '\\"' ) .. '"'
else
return "table" == type( v ) and table.tostring( v ) or
tostring( v )
end
end
function table.key_to_str ( k )
if "string" == type( k ) and string.match( k, "^[_%a][_%a%d]*$" ) then
return k
else
return "[" .. table.val_to_str( k ) .. "]"
end
end
function table.tostring( tbl )
local result, done = {}, {}
for k, v in ipairs( tbl ) do
table.insert( result, table.val_to_str( v ) )
done[ k ] = true
end
for k, v in pairs( tbl ) do
if not done[ k ] then
table.insert( result,
table.key_to_str( k ) .. "=" .. table.val_to_str( v ) )
end
end
return "{" .. table.concat( result, "," ) .. "}"
end
function main()
local mf = require "moonfilter"
-- define the classes to use
mf.classes("/var/log/httpd/spam", "/var/log/httpd/ham")
-- create ham+spam DB on disk -- this is only necessary the first time
-- use command line moonfilter.lua to initially create the DBs outside
-- of ModSecurity
--mf.create()
local anomaly_score = m.getvar("TX.ANOMALY_SCORE", "none");
anomaly_score = tonumber(anomaly_score);
if not (anomaly_score) then
local score = ""
local args = {};
args = m.getvars("ARGS", {"none"});
if (#args == "0") then
m.log(4, "# of ARGS: " ..#args.. ".");
return nil;
end
-- Place ARGS data into key/value pairs for inspection
for k,v in pairs(args) do
name = v["name"];
value = v["value"];
m.log(4, "Arg Name: " ..name.. " and Arg Value: " ..value.. ".");
mf.text = value;
local class_result = mf.classify()
class_result = table.tostring(class_result)
m.log(4, "Classify Results: " .. class_result .. ".")
class = string.gsub(class_result, ".*class=\"(.*)\".*", "%1")
if (class == "/var/log/httpd/spam") then
score = string.gsub(class_result, ".*prob=(%d\.%d%d%d%d%d%d%d%d%d%d%d%d%d%d)\,.*", "%1")
score = tonumber(score)
if (score) then
if (score > 0.90) then
m.log(4, "Classify Results: " .. class .. ".")
m.setvar("tx.bayes_score", class_result);
m.setvar("tx.bayes_var_name", name);
m.setvar("tx.bayes_var", value);
return("Bayesian Analaysis Alert for " .. name .. " with payload: \"" .. value .. "\"")
end
end
end
end
end
return nil;
end
OHA YOOOO