David S. Read

SQL Injection is commonly given as a  root cause when news sites report about stolen data. Here are a few recent headlines for articles describing data loss related to SQL injection: Hackers steal customer data by accessing supermarket database¹, Hacker swipes details of 4m Pirate Bay users², and Mass Web Attack Hits Wall Street Journal, Jerusalem Post³. I understand that SQL injection is prevalent; I just don’t understand why developers continue to write code that offers this avenue to attackers.

From my point of view SQL injection is very well understood and has been for many years. There is no excuse for a programmer to create code that allows for such an attack to succeed. For me this issue falls squarely on the shoulders of people writing applications. If you do not understand the mechanics of SQL injection and don’t know how to effectively prevent it then you shouldn’t be writing software.

The mechanics of SQL injection are very simple. If input from outside an application is incorporated into a SQL statement as literal text, a potential SQL injection vulnerability is created. Specifically, if a parameter value is retrieved from user input and appended into a SQL statement which is then passed on to the RDBMS, the parameter’s value can be set by an attacker to alter the meaning of the original SQL statement.

Note that this attack is not difficult to engineer, complicated to execute or a risk only with web-based applications. There are tools to quickly locate and attack vulnerable applications. Also note that using encrypted channels (e.g. HTTPS) does nothing to prevent this attack. The issue is not related to encrypting the data in transit, rather, it is about keeping the untrusted data away from the backend RDMBS’ interpretation environment.

Here is a simple example of how SQL injection works. Assume we have an application that accepts a last name which will be used to search a database for contact information. The program takes the input, stores it in a variable called lastName, and creates a query:

String sql = "select * from contact_info where lname = '" + lastName + "'";

Now, if an attacker tries the input of: ‘ or 1=1 or ’2′=’

It will create a SQL statement of:

select * from contact_info where lname = '' or 1=1 or '2'=''

This is a legal SQL statement and will retrieve all the rows from the contact_info table. This might expose a lot of data or possibly crash the environment (a denial of service attack). In any case, using other SQL keywords, particularly UNION, the attacker can now explore the database, including other tables and schemas.

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In an earlier blog entry I discussed the potential reduction in refactoring effort if our data is represented as RDF triples rather than relational structures.  As a way to give myself easy access to RDF data and to work more with semantic web tool features I have created a program to export relational data to RDF.

The program is really a proof-of-concept.  It takes a SQL query and converts the resulting rows into assertions of triples.  The approach is simple: given a SQL statement and a chosen primary key column (PK) to represent the instance for the exported data, assert triples with the primary key column value as the subject, the column names as the predicates and the non-PK column values as the objects.

Here is a brief sample taken from the documentation accompanying the code.

• Given a table named people with the following columns and rows:

       id    name    age
       --    ----    ---
       1     Fred    20
       2     Martha  25

• And a query of:  select id, name, age from people
• And the primary key column set to: id
• Then the asserted triples (shown using Turtle and skipping prefixes) will be:

       dsr:PK_1
          a       owl:Thing , dsr:RdbData ;
          rdfs:label "1" ;
          dsr:name "Fred" ;
          dsr:age "20" .

       dsr:PK_2
          a       owl:Thing , dsr:RdbData ;
          rdfs:label "2" ;
          dsr:name "Martha" ;
          dsr:age "25" .

You can see that the approach represents a quick way to convert the data.

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I have create my first slightly interesting, to me anyway, program that uses some semantic web technology.  Of course I’ll look back on this in a year and cringe, but for now it represents my understanding of a small set of features from Jena and Pellet.

The basis for the program is an example program that is described in Hebler, Fischer et al’s book “Semantic Web Programming” (ISBN: 047041801X).  The intent of the program is to load an ontology into three models, each running a different level of reasoner (RDF, RDFS and OWL) and output the resulting assertions (triples).

I made a couple of changes to the book’s sample’s approach.  First I allow any supported input file format to be automatically loaded (you don’t have to tell the program what format is being used).  Second, I report the actual differences between the models rather than just showing all the resulting triples.

As I worked on the code, which is currently housed in one uber-class (that’ll have to be refactored!), I realized that there will be lots of reusable “plumbing” code that comes with this type of work.  Setting up models with various reasoners, loading ontologies, reporting triples, interfacing to triple stores, and so on will become nuisance code to write.

Libraries like Jena help, but they abstract at a low level.  I want a semantic workbench that makes playing with the various libraries and frameworks easy.  To that end I’ve created a Sourceforge project called “Semantic Workbench“.

I intend for the Semantic Workbench to provide a GUI environment for manipulating semantic web technologies. Developers and power users would be able to use such a tool to test ontologies, try various reasoners and validate queries.  Developers could use the workbench’s source code to understand how to utilize frameworks like Jena or reasoner APIs like that of Pellet.

I invite other interested people to join the Sourceforge project. The project’s URL is: http://semanticwb.sourceforge.net/

On the data side, in order to have a rich semantic test data set to utilize, I’ve started an ontology that I hope to grow into an interesting example.  I’m using the insurance industry as its basis.  The rules around insurance and the variety of concepts should provide a rich set of classes, attributes and relationships for modeling.  My first version of this example ontology is included with the sample program.

Finally, I’ve added a semantic web section to my website where I’ll maintain links to useful information I find as well as sample code or files that I think might be of interest to other developers.  I’ve placed the sample program and ontology described earlier in this post on that page along with links to a variety of resources.

My site’s semantic web page’s URL is: http://monead.com/semantic/
The URL for the page describing the sample program is: http://monead.com/semantic/proj_diffinferencing.html

Encapsulation, one of Object Orientation’s (OO) “Big Three” (or four if you include composition), is the concept most often forgotten when I ask an interview candidate to define the key tenants of OO.  Giving the benefit of the doubt, perhaps it is considered “obvious” and hence not necessarily related to OO design in the person’s mind.  Once I bring it up though, there is usually agreement that it is an important aspect to achieving significant value from OO design.

Classically, encapsulation, also called information hiding, “serves to separate the contractual interface of an abstraction and its implementation.”¹ The idea is that the user of the functionality only knows about the public interface (contractual interface) and has no knowledge, nor any ability to tie itself, to the implementation.  The implementation includes both data representation and, effectively, algorithm.

Many times I’ll get an alternate definition; essentially the respondent will define encapsulation as, “as an approach which allows an object’s behavior to be called without the caller having knowledge of how the behavior is implemented.”  This seems very close to the classical definition but misses the key point of “contractual interface.”

I could argue that when any method is called the caller doesn’t have knowledge of how the method is implemented; it just gets a value back.  The missing aspect, the key aspect, is the constraint regarding which methods the caller may call, e.g. the public interface.

What started me on this topic was a recent conversation with a peer regarding read-only objects.  Before I get into specifics, let me baseline the traditional encapsulation approach in a typical object.

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