PPT-High Performance Fuzzing

Richard Johnson Offensive Summit 2015 Introduction Whoami Richard Johnson richinseattle Research Manager Vulnerability Development Cisco Talos Security Intelligence and Research Group Agenda. “Computing . is changing more rapidly than ever before, and scientists have the unprecedented opportunity to change computing . directions” . “In . 20 or 30 years, you'll be able to hold in your hand as much computing knowledge as exists now in the whole city, or even the whole world. Cows. The “No Bull” Talk on Fuzzing. Security B-Sides Ottawa. November 13, 2010. Mike Sues (Rigel Kent). Karim Nathoo (Inverse Labs). Objectives. We can’t cover fuzzing in-depth in 50 minutes. Raise awareness of fuzzing as an option in higher assurance/product evaluations/more focused assessments.  . 0368-3500. Nurit. . Dor. Shir. Landau-. Feibish. Noam Rinetzky. Preliminaries. Students will group in teams of 2-3 students. . Each group will do one of the projects presented.. Administration. Top Trump Cards. For each of the 7 . “High Performance Materials” . you need to know:. Properties. Examples of use. Reasons for use. Improvements on traditional materials. The cards can be used for revision, testing each other in pairs, and playing games to help you remember the info. By. . Nikolaj . Tolka. čio. v. Agenda. What is web application fuzz testing. Introduction to “Fuzzing Machine”. What results it produces. Youtube. setup in “Fuzzing Machine” . How it can be used in other projects. Top Trump Cards. For each of the 7 . “High Performance Materials” . you need to know:. Properties. Examples of use. Reasons for use. Improvements on traditional materials. The cards can be used for revision, testing each other in pairs, and playing games to help you remember the info.  . 0368-3500. Nurit. . Dor. Shir. Landau-. Feibish. Noam Rinetzky. Preliminaries. Students will group in teams of 2-3 students. . Each group will do one of the projects presented.. Administration. Dawn Song, . Kostya. . Serebryany. ,. Peter . Collingbourne. . Techniques for bug finding. Automatic test case generation. Lower coverage . Lower false positives . Higher false negatives. Fuzzing . Dawn Song, . Kostya. . Serebryany. ,. Peter . Collingbourne. . Techniques for bug finding. Automatic test case generation. Lower coverage . Lower false positives . Higher false negatives. Fuzzing . John . Heasman. Stanford University, April 2009. Agenda. Introductions. What is . fuzzing. ?. What data can be fuzzed?. What does fuzzed data look like?. When (not) to fuzz?. Two approaches and a basic methodology. Welcome. Introduction. Agenda. The Business of . Fuzzing. Fuzzing. Technology. Architecting a Framework. Bennu. Concept Tool. Fuzzing. As We Know It. Fuzzing. is a method of software testing. A high volume of . Facility . Management.”. January 22, 2015 . The Journey Begins……. What does HP/world class. mean to you? . How do . y. ou . g. et . t. here?. How do . y. ou . p. rove . i. t?. High-Performance . Software Vulnerability Detection. . Tielei . Wang. 1,2. , Tao Wei. 1,2. , Guofei Gu. 3. , Wei . Zou. 1,2. 1. Key Laboratory of Network and Software Security Assurance . (. Peking University), . Ministry . Written By. Clinton Longenecker and Robert . Yonker. Presented By. Meagan Frances Ayers. Background. Research . the . FACTORS that contribute to . business leader’s success. Issues/Factors include health and wellness.