PPT-All You Ever Wanted to Know About Dynamic Taint Analysis an

but might have been afraid to ask IEEE SampP 2010 Overview Two Main Contributions Precisely describe the algorithms for dynamic taint analysis and forward symbolic execution as extensions to the runtime semantics of a general language. Paper by: James Newsome and Dawn Song. Network and Distributed Systems Security Symposium (NDSS), Feb 2005.. . CS451 Spring 2011. Instructor: Christos Papadopoulos. Original slides by . Devendra. . Incorporating Synchronization Arcs in . Dataflow-Analysis-Based Parallel Monitoring. Michelle Goodstein. *. , Shimin Chen. †. , . Phillip B. Gibbons. ‡. , Michael A. Kozuch. ‡. . and Todd C. Mowry. About Dynamic . Taint . Analysis & Forward . Symbolic . Execution (. but might have been afraid to ask. ). Edward J. Schwartz, . ThanassisAvgerinos. , David . Brumley. Presented by: . Vaibhav . Rastogi. Data tainting and analysis. Roadmap. Background. TaintDroid. JavaScript. Conclusion. Background. In smartphone, we. . use third-party applications such as . - Google map, Angry bird … . etc. More than 10Billion Apps. Yinzhi Cao. Reference: . http. ://www.cs.tau.ac.il/~. omertrip/pldi09/TAJ.ppt. www.cs.cmu.edu/~. soonhok/talks/20110301.pdf. 2. Motivating Example. *. * Inspired by . Refl1. in. SecuriBench Micro. Taint Flow #1. David Devecsery,. Peter M. Chen, Satish Narayanasamy, Jason Flinn. University of Michigan. Motivation – Problem . Dynamic analysis is essential. Memory errors. Buffer overflow, use-after-free, double free, memory leak…. Edward J. Schwartz, . Thanassis. Avgerinos, David . Brumley. Presented by: . Haitao Xu. 1. The Root of All Evil. Humans write programs. This Talk:. Computers Analyzing Programs Dynamically at Runtime. Suman Jana. Dynamic Taint Analysis. Track information flow through a program at runtime. Identify sources of taint – . “. TaintSeed. ”. What are you tracking?. Untrusted input. Sensitive data. Taint Policy – . Yinzhi Cao. Reference: . http. ://www.cs.tau.ac.il/~. omertrip/pldi09/TAJ.ppt. www.cs.cmu.edu/~. soonhok/talks/20110301.pdf. 2. Motivating Example. *. * Inspired by . Refl1. in. SecuriBench Micro. Taint Flow #1. About Dynamic . Taint . Analysis & Forward . Symbolic . Execution (. but might have been afraid to ask. ). Edward J. Schwartz, . ThanassisAvgerinos. , David . Brumley. Presented by: . Vaibhav . Rastogi. Roadmap. Background. TaintDroid. JavaScript. Conclusion. Background. In smartphone, we. . use third-party applications such as . - Google map, Angry bird … . etc. More than 10Billion Apps. Because it’s useful.. Dynamic Taint Analysis. Track information flow through a program at runtime. Identify sources of taint – . “. TaintSeed. ”. What are you tracking?. Untrusted input. Sensitive data. Taint Policy – . App Sets. Will Klieber*, Lori Flynn, . Amar Bhosale , Limin Jia, and Lujo Bauer . Carnegie Mellon University. *presenting. Motivation. Detect malicious apps that leak sensitive data.. Dataflow-Analysis-Based Parallel Monitoring. Michelle Goodstein. *. , Shimin Chen. †. , . Phillip B. Gibbons. ‡. , Michael A. Kozuch. ‡. . and Todd C. Mowry. *. *. Carnegie Mellon University. .