Young hacker smiling

We hack your software

zero false positives

Expert intelligence + effective automation

Can machines learn to hack?

Machine-learning to hack

Machine learning for vulnerability discovery

To date the most important security vulnerabilities have been found via laborius code auditing. Also, this is the only way vulnerabilities can be found and fixed during development. However, as software production rates increase, so does the need for a reliable, automated method for checking or classifiying this code in …



Python proofreading a document

Pars orationis non est secura

Using parser combinators to detect flaws

We like bWAPP around here, because it’s very buggy!. We have shown here how to find and exploit vulnerabilities like SQL injection, directory traversal, XPath injection, and UNIX command injection. All of these have one thing in common, namely: they could have been prevented with a little Input Validation …



Pythia and supplicant in the Oracle of Delphi

The Oracle of Code

About code as data

“Most programs are too large to understand in complete detail”. This was written in the 80’s.[1] Imagine the situation today. Hence the need for automated tools to aid in the process of analyzing code. The solution, according to Oege de Moor from Semmle, is obvious: treat code as …



Person playing chess against a robotic arm

Will machines replace us?

Automatic detection vs. manual detection

More than 20 years have passed since Garry Kasparov, the chess world champion, was defeated by Deep Blue, the supercomputer designed by IBM. For many people, that event was proof that machines had managed to exceed human intelligence [1]. This belief raised many doubts and concerns regarding technological advance, that …



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