PPT-Fuzzing and Patch Analysis:

SAGEly Advice Introduction Goal Exercise target program to achieve full coverage of all possible states influenced by external input Code graph reachability exercise Input interaction with conditional logic in program code determines what states you can reach . 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. Eliminate Unnecessary Patch Testing With Oracle's Patch Wizard. !. Mello-Dee . Simmons. Liza . Klosterman. Introduction. Who We Are. Largest community-owned utility in Florida and the eighth largest in the United States. . Zichao Qi. , Fan Long, Sara . Achour. , and. Martin . Rinard. MIT CSAIL. Buggy Program. Generate-And-Validate . Patch . G. eneration . Systems. Test suite of test cases. Candidate patch space. Generate-And-Validate . 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. Analysis of the Impact of Patching on League of Legends. Artian. . Kica. , Andrew La Manna, Lindsay O’Donnell, Tom . Paolillo. . Mark . Claypool. In . Proceedings of the 2nd International Workshop on Collaboration and Gaming (.  . 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 . Richard Johnson | Offensive Summit 2015. Introduction . Whoami. Richard Johnson / @richinseattle. Research Manager, Vulnerability Development. Cisco, Talos Security Intelligence and Research Group. Agenda. 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 . Semi-Auto Vulnerability Research. Professional Vulnerability. Research. Finding bugs is not the problem . Fuzzing works . Microsoft found over 1800 bugs in Office 2010 . http://. blogs.technet.com/b/office2010/archive/2010/05/11/how-the-sdl-helped-improve-security-in-office-2010.aspx. 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 . Fuzzing and Patch Analysis: SAGEly Advice Introduction Goal: Exercise target program to achieve full coverage of all possible states influenced by external input Code graph reachability exercise