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Goal of this section is to explain in some detail how you can understand a vulnerabilty as reported by Kiuwan.

We will focus the explanation on Injection-related vulnerabilities, as an example of complex vulnerabitlites.

To do it,

  • firstly we will provide an overview of Tainted Flow Analysis (the theoretical basis behind the scenes), and
  • then we will focus on Kiuwan vulnerability reporting.


Tainted Flow Analysis


Root cause of many security breaches is trusting unvalidated input:

  • Input from the user is considered as tainted (possibly controlled by adversary), i.e user is considered as a untrusted source
  • Data is used, assuming it is untainted (must not be controlled by adversary), i.e. sensitive data sinks rely on trusted (untainted) data



The goal of Tainted Flow Analysis is to detect tainted data flows:

For all possible sinks, prove that tainted data will never be used where untainted data is expected.

Kiuwan implements Tainted Flow Analysis by inferring flows in the source code of your application:

  • What sinks are reached by what sources
  • If any flows are illegal, i.e., whether a tainted source may flow to an untainted sink without going across a “sanitizer”


When inferring flows from an untainted sink to a tainted source, Kiuwan is able to detect if any well-known sanitizer is used, dropping those flows and thus avoiding to raise false vulnerabilities.

Kiuwan contains a built-in library of sanitizers for every supported programming language and framework.

These sanitizers are commonly used directly by programmers or by frameworks. And Kiuwan detects the use of them.



How to understand tainted-flow vulnerabilities


Vulnerabilities are reported at Code Security – Vulnerabilities section.





All the vulnerabilities of the same type (i.e. coming from the same Kiuwan rule that checks for it) are grouped under the Kiuwan rule name, indicating how many files are “affected” and how many vulnerabilities were found.


Finding Vulnerabilities (e.g. SQL Injection)


For our explanation, we will follow an example based on Waratek – Spiracle software, focused on SQL-Injection vulnerabilities.

Below image shows SQl-Injection vulnerabilities.

We can see in the image that there are 2 files affected, i.e. two files where there’s a sink that is being feed by tainted data, i.e. an injection point.

Also, we can see that for every file there are a number of vulnerabilities.

What do those vulnerabilities mean? See next image.



Finding Sources and Sinks 



Clicking on the affected file will open all its affected sinks.


In this case, there’s only one sink for every file (only one injection point), but it could be many… Kiuwan will display all the line numbers of the affected sinks.



Clicking on a sink will display its details as well as all the sources where data is collected form an untrusted source and flows to the sink without being neutralized (or sanitized).



Sink's detailed information


Sink data


Sink detail includes following information:

  • Specific CWE, related vulnerability as defined by CWE (hyperlink to definition at MITRE)
  • Sink Data
    • Category (vulnerability type, e.g. sql_injection, xss, etc)
    • Resource (affected resource, e.g. database, web, etc.)
    • Container (function/method where the sink is located)
    • Injection point (tainted data, i.e. variable name)
    • Variable declaration (tainted variable declaration)
    • Source code line and text of sink
    • List of Sources
      • Full list of sources with tainted-flow paths ending in the sink 
      • Every row indicates the source file and line where data coming from an untrusted source flows to the sink without being neutralized (or sanitized).



Most commonly, every source will be a different file. But depending on the flow path, you could find same source and line many times.

Let’s see how to understand every source.




Source's detailed information

Clicking on a source will open a frame with information about the source.


Source data


Source detail includes following information:

  • Category (source type, e.g. user_input, , etc)
  • Resource (resource where the data is gathered, e.g. web, etc.)
  • Container (function/method where the source is located)
  • Source code line and text of sink
  • Propagation path (data-flow between the source and sink)


Propagation Path


Propagation Path


Important: You should not understand the propagation path as a typical stack of method calls. It’s not that.

You should understand it as a data-flow path.


Let’s see with the example.




Any propagation path is composed of a source node, a sink node and as many propagation nodes as different methods are involved in the propagation path.


In the example, we can see the next propagation path (flowing from source to sink) :

  • Source node indicates that file line 32 (within sanitizeNull method) gets the value from a request parameter. 
    • This is marked a source because HttpServletRequest.getParameter(..) is considered as an untrusted input source (i.e. is directly manipulated by the user) and no neutralization routine has been found.
  • First propagation node indicates that line 68 receives back the above tainted data.
  • Second propagation node indicates that line 75 sends the tainted data (via method parameter) to another object through UpdateUtil.executeUpdate(…)  method call. 
    • Looking at the source code, you could see that the tainted data is directly appended to a sql string without any neutralization, allowing this way to directly insert user code into the sql sentence.
  • Sink node indicates that file line 61 (within executeUpdate(…) method) injects tainted data (sql sentence) to a PreparedStatement that finally is executed against the database.

Once explained a concrete source-sink propagation path, let’s go back to the initial sink information.



As said above, for every sink there will appear the list of sources that are “feeding” that sink.

But you might be wondering why are there 5 sources with the same file name and line.

We’ve selected this specific example because it shows something that would be possible to happen in your own code. Let’s go in detail exploring the 2nd source.



In the 2nd source you can see that the propagation nodes are different from the previous one.

While in the 1st the propagation was through, in the 2nd goes through a different file:

Remainder sources for the same sink shows that there are still other different propagation paths between same source and sink.

This example is a special case where the call sequence consists of 5 servlets calling a utility (ParameterNullFix.sanitizeNull(..)) to recover some request parameters, building a SQL sentence with those tainted data and sending the sql sentence to another utility (UpdateUtil.executeUpdate(…) ) to execute the database update.

This is the reason Kiuwan shows one sink with 5 different sinks. That difference is because the propagation paths are through the different servlets.  In this case, the easiest fix would be to sanitize the user data at the source, therefore remediating 5 found defects with only one fix.



As a summary, you can understand any injection vulnerability as a unique propagation path from source to sink, regardless source and sink be the same.


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