Analyzing OWASP Mod Security Audit Log with R

Web servers are frequently scanned or attacked by remote HTTP clients. Attackers send HTTP requests via algorithms or by direct "human" intervention. In order to protect web servers against these threats, automated protection systems block potentially malicious HTTP requests. Every time a request is blocked, its description is logged in a audit file. Often, audit files are difficult-to-read/large text files.  For that reason, it is difficult to have a clear overview of the threats blocked by security mechanisms.  

In this tutorial I describe an algorithm that I wrote in order to analyse the HTTP requests blocked by mod security for Apache HTTPD.  In my environment Mod Security is interfaced with OWASP Core Rule Set version 3 but the algorithm should work for other rules. 

1. Parse the Audit File

Mod Security audit log file is organised in sections.  Each section starts on a new line and can be composed of multiple lines.  Sections are separated by a line specifying the transaction IDs and section code. A description of each section can be found here: https://www.feistyduck.com

 [04/Apr/2018:15:35:55 +0000] WsTw20sPICSQr9pUrF5lpQAAAAs x.x.x.x 46351 x.x.x.x 443  
 GET /sitemap.xml HTTP/1.1  
 Accept-Encoding: identity  

For performance issue, we decided to read the audit file line by line in R. This means that our algorithm acts pretty much as a "human" reader would. A set of functions "understand" the content of the current line given the information retrieved in the previous lines. For example, if the previous line was 


Then, the current line must indicates the time of the request, its ID and  the source and destination IP addresses and ports.  (this is because -A-- is an Audit Log Header)

 [04/Apr/2018:15:35:55 +0000] WsTw20sPICSQr9pUrF5lpQAAAAs x.x.x.x 46351 x.x.x.x 443  

Using regex we created a set of function that validate the type of line and extract the relevant content.

1.a Check and extract the content of the Section header and the Audit Log Header (A)

In order to check the presence of a specific text pattern or extract text within a text pattern we use regular expressions. We imported the package "stringr", a great library that makes our life easier. The first function below evaluates if the current line is announcing a new section. The second function extracts the transaction ID.  The third function extracts the section type. The function "auditLogGetTransactionDate" retrieves the date of the transaction as an R Date object. The last function retrieves the source and destination IPs and Ports as two String (i.e. ["ipSource portSource", "ipDest portDest"].

 # Load Regular Expression Library  
 # Returns true if line is an Audit Log Header  
 auditLogIsTransaction <- function(line){  
  return(str_detect(line, "--[:xdigit:]{8}-[ABCDEFGHIJKZ]--"))  
 # Returns The transaction ID from the Audit Log Header  
 auditLogGetTransactionId <- function(line){  
  return(str_extract(line, "[:xdigit:]{8}"))  
 # Returns The section type from the Audit Log Header  
 auditLogGetTransactionSection <- function(line){  
  return(gsub("-","",str_extract(line, "-([ABCDEFGHIJKZ])-")))  
 # Returns the Transaction date  
 auditLogGetTransactionDate <- function(line){  
  extract <- str_extract(line, "[0123][0-9]/(Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)/20(17|18|19|20)")  
  extractDate <- as.Date(extract,"%d/%b/%Y")  
  return( extractDate )  
 # Returns the IP addresses as an array. (i.e. [IP Source, IP Destination])  
 auditLogGetIPAddressesAndPorts <- function(line){  
  return(str_extract_all(line, "[0-9]{1,3}\\.[0-9]{1,3}\\.[0-9]{1,3}\\.[0-9]{1,3}\\s[0-9]{2,5}"))  

In our example, we can now recognize and extract the piece of information highlighted in yellow.

 [04/Apr/2018:15:35:55 +0000] WsTw20sPICSQr9pUrF5lpQAAAAs 66.x.x.x 46351 x.x.x.x 443  
 GET /sitemap.xml HTTP/1.1  
 Accept-Encoding: identity  

We now need to extract the bit of information explaining why the HTTP request was deemed potentially malicious by Mod Security.

1.b Check and extract OWASP Rule information in Section H

The section H of the Audit log gives the reason why an HTTP request was blocked. It gives both the rule's ID and the rule's description.  

 Message:... [id "920350"] [rev "2"] [msg "Host header is a numeric IP address"] ... 
 Apache-Error: [file "apache2_util.c"] ... [client %s] ModSecurity: %s%s [uri "%s"]%s  
 Stopwatch: 1522856155328261 2511 (- - -)  
 Stopwatch2: 1522856155328261 2511; combined=1679,..., sr=122, sw=0, l=0, gc=0  
 Response-Body-Transformed: Dechunked  
 Producer: ModSecurity for Apache/2.9.1 (http://www.modsecurity.org/); OWASP_CRS/3.0.2.  
 Server: Apache  
 Engine-Mode: "ENABLED"

If the last section header read by the algorithm was of type "H" then the current line could potentially contains the rule's Id and the rule's message. Testing for the presence and extracting the rule's Id is much easier than the rule's message.

The two following functions test if the line string contains a rule id and extracts the rule id.
 # Returns true if contains a rule id  
 auditLogHasErrorCodeMessage <- function(line){  
  return(str_detect(line, '\\[id "\\d{3,10}"\\]'))  
 # Returns the id of the rule  
 auditLogGetErrorCodeMessage <- function(line){  
  return(str_extract(str_extract(line, '\\[id "[0-9]{3,10}"\\]'),"[0-9]{3,10}"))  

1.c Read *and make sense of* the current Line 

Now we put all the functions described above together in order to make sense of what happens in the current line. A Data Frame called "data" acts as the memory of the reader.  At the first line data would be null and a new data frame needs  to be created. Line by line the reader gains new information that is stored in "data". The information stored in "data" helps the reader to understand the next line.

 processAuditLogLine <- function(fileLine, data){  
  # Create structured storage if absent  
   data <- data.frame(txId = NA, txSection = NA, txDate = NA, txSourceIp = NA, txSourceIpLocation = NA, txSourcePort = NA, txDestIp = NA, txDestPort = NA, txRule = NA )  
  # Check if line is transaction   
   # Retrieve Transaction Id  
   txId <- auditLogGetTransactionId(fileLine)  
   # Retrieve transaction Type  
   txSection <- auditLogGetTransactionSection(fileLine)  
   if(txSection == 'A'){  
    data <- rbind(data, data.frame(txId = txId, txSection = txSection, txDate = NA, txSourceIp = NA, txSourceIpLocation = NA, txSourcePort = NA, txDestIp = NA, txDestPort = NA, txRule = NA))  
    # retrive current data row  
    txRow <- dim(data)[1]  
    data[txRow,'txSection'] <- txSection   
   # retrive current data row  
   txRow <- dim(data)[1]  
   # Check line not empty  
   if(fileLine !=''){  
    # Retrieve current Section Type  
    currentSection <- data[txRow,'txSection']  
       # Check if section is for a new HTTP Request (A)  
    if(currentSection == 'A'){  
      # Retrieve Date  
      data[txRow,'txDate'] <- auditLogGetTransactionDate(fileLine)  
      # Retrieve IP addresses and ports  
      ipAddressesArr <- unlist(auditLogGetIPAddressesAndPorts(fileLine))  
      source <- unlist(strsplit(ipAddressesArr[1]," "))  
      dest <- unlist(strsplit(ipAddressesArr[2]," "))  
            # Store IP addesses and ports in data  
      data[txRow,'txSourceIp'] <- source[1]  
      data[txRow,'txSourcePort'] <- source[2]  
      data[txRow,'txDestIp'] <- dest[1]  
      data[txRow,'txDestPort'] <- dest[2]  
        # Check if section is giving information about the Rule (H)  
    if(currentSection == 'H'){  
     if(startsWith(fileLine, 'Message: ')){  
      data[txRow,'txRule'] <- auditLogGetErrorCodeMessage(fileLine)  

1.d Read the file 

So far, we have seen how we can recognize the information and extract it in R. We also saw how, in one function, we can read and make sense of a line given the previous knowledge gained in the document.  The function below shows how the file is actually read.

At every line of the file we execute the method called "method" and pass the data in parameter.  Note that data is first declared as NULL.

 processLogFile <- function(filepath, method) {  
  con = file(filepath, "r")  
  data <- NULL  
  while ( TRUE ) {  
   line = readLines(con, n = 1)  
   if ( length(line) == 0 ) {  
   # execute method on line   
   data <- method(line, data)  

Now to get a data frame containing all the transactions of the audit log we can call:
 # File Location  
 pathAudit <- 'C:/Temp/Logs/modsec_audit_20181001.log'   
 # Parse/Read Audit Log  
 data <- processLogFile(pathAudit, processAuditLogLine)  
 # Display data  
 head(data, 9)  

The 9 first rows are displayed below. Of course source IP addresses have been changed to protect the anonymity of our attackers and ours (A bit of GDPR compliance in this world of savage would not hurt!)


In this table we can see that all sections have been read up to section Z in the column "txSection". Thats because section Z announces the end of a transaction/HTTP request.  The dates in column txDate are actually stored in number of days since the "1970-01-01". 

We already have a lot of information but we would also like to retrieve the country where each Source IP address is registered. 

2.a Add additional Insight from API. (i.e. IP Address Geolocation). 

We would like to extend the data set obtained previously by adding the IP addresses geolocations.  In order to do so, we have to fetch the countries name from an online IP geolocation API.  

In this tutorial we use the API proposed by  http://api.ipstack.com/ which worked really well. You will need to replace the API_Key by your own in order to use the API. The free account provides 10,000 API requests by month. 

 retrieveIPsLocations <- function(threatsData){  
  # Library  
  # Find unique Ips  
  unIps <- unique(threatsData$txSourceIp)  
  countriesForIpsDataFrame <- data.frame(txSourceIp = unIps, txSourceCountry = rep(NA, length(unIps)))  
  # Using https://ipstack.com  
  API_Key <- "########################"  
  countriesForIpsDataFrame$txSourceCountry <- unlist(apply(countriesForIpsDataFrame, 1, FUN = function(x){  
   URL <- paste("http://api.ipstack.com/",x[1],"?access_key=",API_Key, sep = "")  
   jsonObj <- fromJSON(URL)  
   if(is.null(jsonObj) || is.null(jsonObj$country_name))  
  threatsData <- merge(threatsData, countriesForIpsDataFrame, by='txSourceIp')  

We can think of other API uses here. For example we could check which IP addresses are on  blacklist. Many online APIs provide this info for small fees.

3 Analyzing the Data

By running the code above we should have one row per HTTP request. In each row the following information are stored:  the country, date and security rules. 

It is time to unleash our data analysis skills! 

3.a Analyzing the Geography of the attacks

Using the package "rworldmap", a simple world visualization library we can easily plot the amount of request by country.

The function below does just that.

 mapThreats <- function(threathDataset){  
  #Aggregate By countries  
  threathDataset <- threats %>% group_by(txSourceCountry) %>% summarise(ThreatsCount=n()) %>% arrange(desc(ThreatsCount))  
  spMapDF <- joinCountryData2Map(threathDataset, joinCode = "NAME", nameJoinColumn = "txSourceCountry")  
  mapCountryData( spMapDF, nameColumnToPlot="ThreatsCount" )  

 # Visualise threats count by country  

For our audit log we got, *unsurprisingly* the following graph:

The rule 920350  prevents any remote clients to access the web server with an IP address only. While it is a really good rule to be protected against Malicious web vulnerability scanners, it is prone to false positive. Imagine for example that google is trying to index your website by using its IP address.

In order to have a clearer picture we filter the request that were not blocked by the rule 920350.  We use "dplyr" package for filtering but any other package (or none) could be used instead. 

 # Filter for IP Rule   
 threats <- threats %>% filter(txRule!=920350)  
 # Visualise threats count by country  

We can see that most request have been filtered out. We passed from 2,253 request in the country with the highest number of blocked request to just 102.  The result however are consistent. Most of the request originate from the USA, China, Sweden, Poland, Romania, France, Germany and the Netherlands.

3.b Analyzing the Type of attack

From section 3.a it is obvious that by far the most frequently triggered security rule is 920350. We will now visualize the other rules in a bar plot.   
 barPlotModSecRules <- function(threatsDataset){  
  rules <- as.data.frame(threats %>% group_by(txRule) %>% summarise(ThreatsCount=n()) %>% arrange(desc(ThreatsCount)))  
  rules$txRule <- as.factor(rules$txRule)  
  ggplot(data=rules[1:10,], aes(x=txRule, y=ThreatsCount)) +  
   geom_bar(stat="identity", width=0.5)  
 # Visualize rules in a Bar plot  

The description and count of the rules in the bar plot are given below:

host header is a numeric IP address (could be search engines)
Restricted File Access Attempt
Request Missing a Host Header
Anomaly score correlation rule
XSS Attack Detected via libinjection
Multiple/Conflicting Connection Header Data Found.
URL file extension is restricted by policy
Found User-Agent associated with security scanner
GET or HEAD Request with Body Content.
Invalid HTTP Request Line
Path Traversal Attack (/../)
PHP Injection Attack: High-Risk PHP Function Call Found
Request Containing Content, but Missing Content-Type header
Remote Command Execution: Direct Unix Command Execution

It seems that attacker mainly attempts to access restricted files. In total over the period of the log, 95 requests were made without a proper host header, this can be the work of Scanner Hacker or misconfigured HTTP clients (false positive)   

3.c Analyzing the chronology of attacks

Using our data.frame, we can visualize the chronology of attacks and search for seasonal patterns. In addition we can search for trends or stationarity.

 # Count blocked HTTP requests for each day in our dataset  
 dataAtHand <- threats %>% group_by(txDate) %>% summarise(count=n()) %>% arrange(txDate)  
 # Create dataset with all days between the first and last day of the log  
 allDates <-data.frame(txDate= seq(as.Date(unlist(head(dataAtHand,1)[1])), as.Date(unlist(tail(dataAtHand,1)[1])), by="days"))  
 # Merge data frame containing all the dates with the data frame containing the count.   
 datesData <- merge(allDates, dataAtHand , by="txDate" ,all.x=TRUE) %>% arrange(txDate)  
 # Set count equal to zero when no request for one day  
 datesData[is.na(datesData$count),'count']<- 0  
 # Plot time series  
 plot(ts(datesData$count), axes=F, ylab="Warnings",xlab="")  
 title(xlab="Time", line=6, cex.lab=1.2)  
 labelsIndexes <-seq(1,length(datesData$txDate), by=30)  
 axis(1, at = labelsIndexes, labels = datesData$txDate[labelsIndexes], las=3)  

The code above returns the following time series plot:

No clear seasonality and trend could be found be inspecting the graph visually.  Further test statistics could be used to assess whether either seasonality or trend effect are present.

4. Conclusion

It is difficult to have an overview of the threat by looking at the log files. With the code above we can not only have an overview of the attacks but also analyse our attackers and their behaviors. We can monitor the time of their attack, the type of their attack and their geographic location.   

The resulting data set can be used to test statistical hypothesis and improve our defense by understanding our attackers.

This post is intended to be used on https://www.r-bloggers.com


Interaction between VBA(Excel) and Java


In the code below, I implemented a one way communication between my Excel AddIn and the Main java application of the World cancer research fund Continuous Update project.

Basically, when a user highlight a cell with a WCRF_CODE (string code attributed to a publication), the button "View In App" is enabled and once clicked, launch the window of the selected publication in the main java application. (If the java application is not found, then it starts a new process).

Here are the steps that lead to functional interprocess communication between a custom excel Ribbon and a java application.

1) An Excel 2010 ribbon with one button with callback that is triggered when  the cell selection change or if the content change in the workbook.
 <?xml version="1.0" encoding="UTF-8"?>  
 <customUI xmlns="http://schemas.microsoft.com/office/2009/07/customui" onLoad="ribbonLoad">  
  <ribbon startFromScratch="false">  
    <tab id="cupTabAddIn" label="CUP">  
       <group id="MyGroup2"  
         label="Java Application">  
           <button id="button_launch" label="See in App" imageMso="MailMergeResultsPreview" onAction="seeWCRF" getEnabled="isWCRFSelected" />  
The callback for the button is "isWCRFselected" if it is true, then the button is enabled. The main action of the button is of course "seeWCRF". I edited the code of the xaml file (my addin) with Custom UI editor.

2) Now that my controls exists there is plenty code to write to make them actually do something useful. First of all I need to catch the events "SheetChange" and "SheetSelectionChange". Since my excel file is an addin I can't just write them down in ThisWorkbook as this is never called. Instead I need to write a class module: "clsApplicationEvents" with the following code.

 Option Explicit  
 Private WithEvents oApp As Excel.Application  
 Property Set XL(Application As Excel.Application)  
 Set oApp = Application  
 End Property  
 Property Get XL() As Excel.Application  
   Set XL = oApp  
 End Property  
 Private Sub oApp_SheetChange(ByVal Sh As Object, ByVal Target As Range)  
 ribbon.ribbon.InvalidateControl "button_launch"  
 End Sub  
 Private Sub oApp_SheetSelectionChange(ByVal Sh As Object, ByVal Target As Range)  
    ribbon.ribbon.InvalidateControl "button_launch"  
 End Sub  

In a normal module called "clsApplicationEventStandard", I wrote

 Option Explicit  
 Global AnyWorkbook As clsApplicationEvents  

And finally I wrote, in ThisWorkbook:
 Option Explicit  
 Private Sub Workbook_Open()  
   Set AnyWorkbook = New clsApplicationEvents  
   Set AnyWorkbook.XL = Excel.Application  
   Debug.Print "Opening"  
 End Sub  

Now we have an addin with buttons, and we can use the workbook event as in non-addins environment. But our button if pressed are not doing anything yet.
 We need to define some more methods...
 Option Explicit  
 ' We keep a reference to the loaded Ribbon  
 Public ribbon As IRibbonUI  
 ' Save a reference to the Ribbon  
 ' This is called from the ribbon's OnLoad event  
 Public Sub ribbonLoad(rb As IRibbonUI)  
   Set ribbon = rb  
 End Sub  
 Public Sub splitribbon(control As IRibbonControl)  
   Call wcrf_buttons.splitup  
 End Sub  
 Public Sub mergeribbon(control As IRibbonControl)  
   Call wcrf_buttons.getConcatenatedList  
 End Sub  
 Public Sub isWCRFSelected(control As IRibbonControl, ByRef enabled)  
   enabled = method_util.isWCRFCode(ActiveCell.Value)  
 End Sub  
 Public Sub seeWCRF(control As IRibbonControl)  
   Call JavaInterprocess.sendApp(ActiveCell.Value)  
 End Sub  

Now, we have methods behind our buttons and these methods of course call other methods (so that I can use these methods without passing by the ribbon as well). The methods behind  splitribbon and mergeribbon are trivials as well as the "isWCRFSelectedMethod" but I will write them down so you can have an idea of what they do.  It is worth to note that  isWCRFSelectedMethod uses regex and so need to have "Microsoft Vb Script Regular Expression 5.5" activated.

''Normally this method is in a module called wcrf_buttons
Sub getConcatenatedList()  
 Dim clipboard As MSForms.DataObject  
 Dim rng As Range  
 Set clipboard = New MSForms.DataObject  
 Dim text$  
 Dim isFirst As Boolean  
 isFirst = True  
 Set rng = Selection.SpecialCells(xlCellTypeVisible)  
 For Each cell In rng  
   If (isFirst) Then  
     text = Trim(cell.Value)  
     isFirst = False  
     text = text & ";" & Trim(cell.Value)  
   End If  
 clipboard.SetText text  
 End Sub

Given a selected range of cells, the method above will concatenate the value in a string with a semi colon as separator. This string will then be placed in the clipboard.

 Sub splitup()  
   Dim arrayOfRs  
   Dim delimitor$  
   Dim output$  
   Dim clipboard As MSForms.DataObject  
   Set clipboard = New MSForms.DataObject  
   delimitor = InputBox("Delimiter please", "Parameter required")  
   arrayOfRs = split(ActiveCell.Value, delimitor)  
   For i = 0 To UBound(arrayOfRs)  
     If (i <> 0) Then  
       output = output & vbCrLf & arrayOfRs(i)  
       output = arrayOfRs(i)  
     End If  
   Next i  
   On Error Resume Next  
   clipboard.SetText output  
 End Sub  

Given a String of item separated by a certain character, this method will split the text in row than can then be paste in Excel.

The method below return true if the format of the text is the one of a WCRF code.
''Normally this method is in a module called method_util
 Public Function isWCRFCode(text As String) As String  
   Dim strPattern As String  
   Dim wcrfCodeList$  
   strPattern = "(LUN|COL|BRE|STM|OES|oes|SKI|NAS|CER|PAN|PRO|LIV)[0-9]{4,7}"  
   Dim regEx As New RegExp  
   Dim strInput As String  
   Dim Myrange As Range  
   Dim matches  
   With regEx  
       .Global = True  
       .MultiLine = True  
       .IgnoreCase = False  
       .Pattern = strPattern  
   End With  
   isWCRFCode = regEx.test(text)  
 End Function  

Now come the big deal, we want to send data to the server (our main java application) For that I created a module called "JavaInterProcess" In the module you can find these methods

 Private Declare Sub Sleep Lib "kernel32" (ByVal dwMilliseconds As Long)  

This is just a small definition of a kernel32 class that when called, will pause the application for dwMilliseconds. It is needed because if our application is not started when we send the command... nothing will happen. So we will use this to wait 10 seconds before the time we launch our application and the time we send the command to the server of our application.

 Public Sub sendApp(wcrfcode As String)  
 Dim ProcID As Integer  
 'Find process of java application  
 'On error StartApp  
 On Error GoTo startApp  
 ProcID = findProcess()  
 GoTo manipulateApp  
   ProcID = startApp()  
 ' Activate the Java Application application.  
 On Error GoTo erreurmsg:  
 AppActivate (ProcID)  
 'send Command via server  
 Call serverSocket.sendMsg("", 8084, "JAVACUP:" & wcrfcode)  
 Exit Sub  
 MsgBox ("unexpected error occured!")  
 End Sub  

This is the main method of our interprocess communication, it first see if our java application process is running by calling the method "findProcess()". If a process is there, it is fine we can activate the window of our  current java process then call the method serverSocket.sendMsg(add, port, msg). Conversely if the application is not running then, we start the java application, wait 10 seconds and send the command.

 Private Function findProcess() As Integer  
 Dim oShell As Object  
 Set oShell = CreateObject("WScript.Shell")  
 Dim oExec As Object  
 Dim oOutput As Object  
 Set oExec = oShell.Exec("jps")  
 Set oOutput = oExec.StdOut  
 Dim s As String  
 Dim sLine As String  
 While Not oOutput.AtEndOfStream  
   sLine = oOutput.ReadLine  
   'in debug ApplicationEntryPoint  
   If (InStr(1, sLine, "Program")) Then  
     s = Replace(sLine, "Program", "")  
     s = Replace(s, " ", "")  
   End If  
 On Error GoTo erreur:  
   findProcess = CInt(s)  
   Exit Function  
   findProcess = CVErr(xlErrValue)  
 End Function 

The method findProcess above return  a PID of the process or an errer xlErrValue if there is no process running.

Below is the code to start our application.

 Private Function startApp() As Integer  
 Dim pid%  
 pid = Shell("java -jar ""C:\Program Files (x86)\wcrfapp\wcrfapp.jar"" ", vbHide)  
 Sleep (10000)  
 startApp = pid  
 End Function  

I found the code of a server in VBA on this forum. So I will just copy paste it here as a reference:
 Public Const AF_INET = 2  
 Public Const SOCK_STREAM = 1  
 Public Const SOCKET_ERROR = 1  
 Public Const FD_SETSIZE = 64  
 Public Const FIONBIO = 2147772030#  
 Public Const SOCKADDR_IN_SIZE = 16  
 Public Type WSADATA  
   wVersion As Integer  
   wHighVersion As Integer  
   szDescription As String * 257  
   szSystemStatus As String * 129  
   iMaxSockets As Integer  
   iMaxUdpDg As Integer  
   lpVendorInfo As Long  
 End Type  
 Public Type SOCKADDR_IN  
   sin_family As Integer  
   sin_port As Integer  
   sin_addr As Long  
   sin_zero As String * 8  
 End Type  
 Public Type fd_set  
   fd_count As Long  
   fd_array(FD_SETSIZE) As Long  
 End Type  
 Public Type timeval  
   tv_sec As Long  
   tv_usec As Long  
 End Type  
 Public Declare Function WSAStartup Lib "wsock32.dll" (ByVal intVersionRequested As Integer, lpWSAData As WSADATA) As Long  
 Public Declare Function WSACleanup Lib "wsock32.dll" () As Long  
 Public Declare Function w_socket Lib "wsock32.dll" Alias "socket" (ByVal lngAf As Long, ByVal lngType As Long, ByVal lngProtocol As Long) As Long  
 Public Declare Function w_closesocket Lib "wsock32.dll" Alias "closesocket" (ByVal SocketHandle As Long) As Long  
 Public Declare Function w_bind Lib "wsock32.dll" Alias "bind" (ByVal socket As Long, Name As SOCKADDR_IN, ByVal namelen As Long) As Long  
 Public Declare Function w_connect Lib "wsock32.dll" Alias "connect" (ByVal socket As Long, Name As SOCKADDR_IN, ByVal namelen As Long) As Long  
 Public Declare Function w_send Lib "wsock32.dll" Alias "send" (ByVal socket As Long, buf As Any, ByVal length As Long, ByVal flags As Long) As Long  
 Public Declare Function w_recv Lib "wsock32.dll" Alias "recv" (ByVal socket As Long, buf As Any, ByVal length As Long, ByVal flags As Long) As Long  
 Public Declare Function w_select Lib "wsock32.dll" Alias "select" (ByVal nfds As Long, readfds As fd_set, writefds As fd_set, exceptfds As fd_set, timeout As timeval) As Long  
 Public Declare Function htons Lib "wsock32.dll" (ByVal hostshort As Integer) As Integer  
 Public Declare Function ntohl Lib "wsock32.dll" (ByVal netlong As Long) As Long  
 Public Declare Function inet_addr Lib "wsock32.dll" (ByVal Address As String) As Long  
 Public Declare Function ioctlsocket Lib "wsock32.dll" (ByVal socket As Long, ByVal cmd As Long, argp As Long) As Long  
 Public Declare Function FormatMessage Lib "kernel32" Alias "FormatMessageA" (ByVal dwFlags As Long, lpSource As Any, ByVal dwMessageId As Long, ByVal dwLanguageId As Long, ByVal lpBuffer As String, ByVal nSize As Long, Arguments As Long) As Long  
 Private Sub CloseSocket(socket As Long)  
   If socket <> -1 Then  
     w_closesocket socket  
   End If  
 End Sub  
 Public Function sendMsg(Address As String, port As Integer, URI As String)  
   Dim ret As Long  
   Dim SocketHandle As Long  
   Dim wd As WSADATA  
   Dim localAddress As SOCKADDR_IN  
   Dim serverAddress As SOCKADDR_IN  
   Dim URIRequest As String  
   Dim retBuff(1024) As Byte  
   Dim retString As String  
   Dim tempString As String  
   VcitajURI = ""  
   SocketHandle = -1  
   ret = WSAStartup(&H101, wd)  
   If ret <> 0 Then GoTo ErrorHandler  
   SocketHandle = w_socket(AF_INET, SOCK_STREAM, 0)  
   If SocketHandle = -1 Then GoTo ErrorHandler  
   localAddress.sin_family = AF_INET  
   localAddress.sin_port = 0  
   localAddress.sin_addr = 0  
   ret = w_bind(SocketHandle, localAddress, SOCKADDR_IN_SIZE)  
   If ret = -1 Then GoTo ErrorHandler  
   serverAddress.sin_family = AF_INET  
   serverAddress.sin_port = htons(port)  
   serverAddress.sin_addr = inet_addr(Address)  
   ret = w_connect(SocketHandle, serverAddress, SOCKADDR_IN_SIZE)  
   If ret = -1 Then GoTo ErrorHandler  
   URIRequest = URI & vbCrLf  
   ret = w_send(SocketHandle, ByVal URIRequest, Len(URIRequest), 0)  
   If ret = -1 Then GoTo ErrorHandler  
   CloseSocket SocketHandle  
 End Function  

We now have a functioning client that will send data to our application. Now we need to program the application so that it understand the command (WCRF code) send by the client.

This is the start of our application.

  public static void main(String[] args) {  
      * Listener, if any key is sent from Excel the code of the key will be  
      * */  
     Thread server=new Thread(new Listener());  

All the code of the server is centralised in the class "Listener below":

 package GUI.InterProcessCommunication;  
 import BO.Incidence.IncidenceMain_BO;  
 import GUI.Incidence.IncidenceSearch_Launcher;  
 import GUI.SplashScreen.SplashScreen_DataLoading;  
 import java.awt.*;  
 import java.awt.event.KeyEvent;  
 import java.io.BufferedReader;  
 import java.io.IOException;  
 import java.io.InputStreamReader;  
 import java.io.PrintWriter;  
 import java.net.InetSocketAddress;  
 import java.net.ServerSocket;  
 import java.net.Socket;  
 import java.nio.ByteBuffer;  
 import java.nio.channels.ServerSocketChannel;  
 import java.nio.channels.SocketChannel;  
 import java.util.ArrayList;  
 import java.util.Optional;  
  * Created by casteven on 11/10/2016.  
 public class Listener implements Runnable {  
   int port = 8084;  
   public void run() {  
     int portNumber = 8084;  
     try {  
       ServerSocket socket = new ServerSocket(portNumber);  
       while (true) {  
         Socket clientSocket = socket.accept();  
         BufferedReader in = new BufferedReader(new InputStreamReader(clientSocket.getInputStream()));  
         // Initiate conversation with client  
         String inputLine = "";  
         while ((inputLine = in.readLine()) != null) {  
           if (inputLine.startsWith("JAVACUP:")) {  
             String wcrf = inputLine.replaceAll("JAVACUP:", "");  
             Optional<IncidenceMain_BO> publicationFromExcel = BL.Incidence.IncidenceMain_BL.selectAll_Studies_per_WCRF(wcrf).stream().findAny();  
             if (publicationFromExcel.isPresent()) {  
               Runnable r = new IncidenceSearch_Launcher(SplashScreen_DataLoading.Instance(), publicationFromExcel.get());  
               Thread t = new Thread(r);  
     }catch(IOException e){  

As you can see it is an infinite loop in a thread that accepts connections and in case that the received WCRF_Code exists, launch the window with right publication data.

This is how to ribbon looks like for those interested:

Now the idea is to extend this communications with more objects and methods! Yeeepie yeah