PDF-Unleashing M AYHEM on Binary Code Sang Kil Cha Thanassis Avgerinos Alexandre Rebert and

Author : luanne-stotts | Published Date : 2014-12-26

rebert dbrumley cmuedu Abstract In this paper we present M AYHEM a new sys tem for automatically 64257nding exploitable bugs in binary ie executable programs Every

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Unleashing M AYHEM on Binary Code Sang Kil Cha Thanassis Avgerinos Alexandre Rebert and: Transcript


rebert dbrumley cmuedu Abstract In this paper we present M AYHEM a new sys tem for automatically 64257nding exploitable bugs in binary ie executable programs Every bug reported by M AYHEM is accompanied by a working shellspawning exploit The working. edu Abstract A recurring problem in security is reverse engineering binary code to recover highlevel language data abstrac tions and types Highlevel programming languages have data abstractions such as buffers structures and local vari ables that all Efros Carnegie Mellon University Abstract This paper proposes a conceptually simple but surpris ingly powerful method which combines the effectiveness of a discriminative object detector with the explicit correspon dence offered by a nearestneighbor Efros Carnegie Mellon University Figure 1 In this paper we are interested in de64257ning visual similarity between images across different domains such as photos taken in different seasons paintings sketches etc What makes this challenging is that t ECT 1989 Carnegie Mellon University 89 10 10171 Appved for pus bc te Dtatzlbaton WUftitied brPage 2br Unclassified SECURITY CLASSIFICATION OF THIS PAGE REPORT DOCUMENTATION PAGE Ia JPOfT SECLINTY CLASSIFICATION lb RESTRICTIVE MARKINGS 2a SECURITY C scanfd val Carnegie Mellon return y Ax int matvecint A int x int y mallocNsizeofint int i j for i0 i for j0 j yi Aijxj return y brPage 5br Carnegie Mellon int p p mallocNsizeofint for i0 i pi mallocMsizeofint Carnegie Mellon int p p mallocN We present a general methodology for near optimal sensor placement in these and related problems We demonstrate that many realistic outbreak detection objectives eg de tection likelihood population a64256ected exhibit the prop erty of submodularity Microstructure. -. Properties. Tensors and Anisotropy, Part 2. Profs. A. . D. Rollett, . M. . De . Graef. Microstructure. Properties. Processing. Performance. Last modified. : . 15. th. . Nov. ‘15. Networking Basics and Concurrent Programming. Shiva (. sshankar. ). Section . M. 2. Carnegie Mellon. Topics. Networking Basics. Concurrent Programming. Introduction to Proxy Lab. 3. Carnegie Mellon. Sockets. Machine-Level Programming II: Control. 15. -. 213: . Introduction to Computer Systems. 6. th. . Lecture,. Sep. 17, 2015. Carnegie Mellon. Instructors:. . Randal E. Bryant. and . David. R. . O’Hallaron. 27-750. Texture, Microstructure & Anisotropy. A.D. Rollett. Last revised:. . 22. nd. . Feb. . ‘. 16. 2. Bibliography. R.E. Newnham,. Properties of Materials: Anisotropy, Symmetry, Structure. Midterm Review. 15-213: Introduction to Computer Systems . October 15, 2012. Instructor. :. Agenda. Midterm tomorrow!. Cheat sheet: One 8.5 x 11, front and back. Review. Everything up to caching. Questions. Credit: Some slides from Ed Schwartz. Control Flow Hijack: . Always control computation. computation. . . control. shellcode. (aka payload). padding. 15. -. 213: . Introduction to Computer Systems. 6. th. . Lecture,. Sept. 15, 2016. Carnegie Mellon. Instructor:. . . Randy Bryant. Carnegie Mellon. Today. Control. : Condition codes. Conditional branches. Pittsburgh’s leading cash buyer provides much-needed relief for distressed homeowners, helping them sell their properties at attractive prices.

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