Webcasts
November 29, 2011 - Fuzzing 101 Webinar:
Defensics X Features and Live Demonstration
About Fuzzing 101 and Codenomicon
Codenomicon has been active in the field of Fuzzing since 1996. The company works with companies industries to improve the security of a wide range of communication products and services. Fuzzing 101 webcasts provide vendor neutral advice on Fuzzing, and demonstrates how Fuzzing tools can be used for various purposes.
Abstract
It's what you don't know that makes you vulnerable
Codenomicon, the leading vendor of proactive security testing solutions, recently announced the release of Defensics X, the latest version of their security and robustness testing software. The major update introduces better coverage through infinite test case generation and usability enhancements on the user interface. Improved interoperability checks quickly adapt the tests to any test environment. Finally, new reporting functionality makes it faster to resolve all the discovered zero-day vulnerabilities.
Unknown zero-day vulnerabilities are problems that hide in software exposing them to zero-day attacks. Resolving them is the highest priority for software companies, device manufacturers and end-users such as enterprises, carriers and network operators. The new Defensics X is the answer to modern day security testing requirements. In addition to improved test coverage, Defensics X integrates feedback from hundreds of Defensics user organizations globally. These improvements provide enhancements to usability, test automation and reporting.
In this webcast we will go through the key features in Defensics X, and demonstrate how Defensics fuzzing platform is configured and used in a live test setup.
Speaker
Juha-Matti Tirilä
Mr. Juha-Matti Tirilä works as a security researcher at Codenomicon. Mr. Tirilä's research activities at Codenomicon range from general investigations of robustness testing methods and related software quality management processes to specific case studies in fuzzing, using different kinds of tehcnologies as target systems. Relating to his research at Codenomicon, Mr. Tirilä also collaborates with fuzzing researchers at the University of Oulu. Prior to joining Codenomicon, Mr. Tirilä has worked in academia as an applied mathematics researcher, working on statistical methods for time series analysis, and also gaining experience in statistical inference and machine learning techniques, as well as software development.
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