GithubHelp home page GithubHelp logo

pombredanne / panda-1 Goto Github PK

View Code? Open in Web Editor NEW

This project forked from moyix/panda

0.0 1.0 0.0 26.28 MB

Deprecated repo for PANDA 1.0 – see PANDA 2.0 repository

Home Page: http://github.com/panda-re/panda

Python 0.71% Shell 0.18% Makefile 0.57% C 82.22% C++ 9.82% Haxe 0.40% Objective-C 1.80% Batchfile 0.01% Assembly 1.49% Forth 2.11% Perl 0.47% PHP 0.10% HTML 0.01% Roff 0.01% GDB 0.01% F# 0.01% QMake 0.01% XSLT 0.05% Lex 0.01% Yacc 0.03%

panda-1's Introduction

PANDA

This repository is deprecated. Please refer to PANDA 2.

No new updates will be made to this repository.

PANDA is an open-source Platform for Architecture-Neutral Dynamic Analysis. It is built upon the QEMU whole system emulator, and so analyses have access to all code executing in the guest and all data. PANDA adds the ability to record and replay executions, enabling iterative, deep, whole system analyses. Further, the replay log files are compact and shareable, allowing for repeatable experiments. A nine billion instruction boot of FreeBSD, e.g., is represented by only a few hundred MB. PANDA leverages QEMU's support of thirteen different CPU architectures to make analyses of those diverse instruction sets possible within the LLVM IR. In this way, PANDA can have a single dynamic taint analysis, for example, that precisely supports many CPUs. PANDA analyses are written in a simple plugin architecture which includes a mechanism to share functionality between plugins, increasing analysis code re-use and simplifying complex analysis development.

It is currently being developed in collaboration with MIT Lincoln Laboratory, NYU, and Northeastern University.

Building

Because PANDA has a few dependencies, we've encoded the build instructions into a script, panda_install.bash. The script should actually work on Debian 7/8 and Ubuntu 14.04, and it shouldn't be hard to translate the apt-get commands into whatever package manager your distribution uses. We currently only vouch for buildability on Debian 7/8 and Ubuntu 14.04, but we welcome pull requests to fix issues with other distros.

Note that if you want to use our LLVM features (mainly the dynamic taint system), you will need to install LLVM 3.3 from OS packages or compiled from source. On Ubuntu 14.04 this will happen automatically via panda_install.bash.

We don't currently support building on Mac/BSD, although it shouldn't be impossible with a few patches. We do rely on a few Linux-specific APIs.

Support

If you need help with PANDA, or want to discuss the project, you can join our IRC channel at #panda-re on Freenode, or join the PANDA mailing list.

We have a basic manual here.

PANDA Plugins

Details about the architecture-neutral plugin interface can be found in docs/PANDA.md. Existing plugins and tools can be found in qemu/panda_plugins and qemu/panda_tools.

Record/Replay

PANDA currently supports whole-system record/replay execution of x86, x86_64, and ARM guests. Documentation can be found in docs/record_replay.md.

Android Support

PANDA supports ARMv7 Android guests, running on the Goldfish emulated platform. Documentation can be found in docs/Android.md.

Publications

  • [1] B. Dolan-Gavitt, T. Leek, J. Hodosh, W. Lee. Tappan Zee (North) Bridge: Mining Memory Accesses for Introspection. 20th ACM Conference on Computer and Communications Security (CCS), Berlin, Germany, November 2013.

  • [2] R. Whelan, T. Leek, D. Kaeli. Architecture-Independent Dynamic Information Flow Tracking. 22nd International Conference on Compiler Construction (CC), Rome, Italy, March 2013.

  • [3] B. Dolan-Gavitt, J. Hodosh, P. Hulin, T. Leek, R. Whelan. Repeatable Reverse Engineering with PANDA. 5th Program Protection and Reverse Engineering Workshop, Los Angeles, California, December 2015.

  • [4] M. Stamatogiannakis, P. Groth, H. Bos. Decoupling Provenance Capture and Analysis from Execution. 7th USENIX Workshop on the Theory and Practice of Provenance, Edinburgh, Scotland, July 2015.

  • [5] B. Dolan-Gavitt, P. Hulin, T. Leek, E. Kirda, A. Mambretti, W. Robertson, F. Ulrich, R. Whelan. LAVA: Large-scale Automated Vulnerability Addition. 37th IEEE Symposium on Security and Privacy, San Jose, California, May 2016.

License

GPLv2.

Acknowledgements

This work was sponsored by the Assistant Secretary of Defense for Research and Engineering under Air Force Contract #FA8721-05-C-0002.

panda-1's People

Contributors

a-helberg avatar aurel32 avatar bet4it avatar bonzini avatar clarkb7 avatar clevcode avatar dbennett455 avatar direwolf314 avatar fry avatar giomasce avatar gitttt avatar hendersa avatar jan-kiszka avatar jhodosh avatar m000 avatar moyix avatar nvb avatar patricksjackson avatar pete128 avatar phulin avatar pm215 avatar rickyulrich avatar rjwhelan avatar rth7680 avatar soly avatar stjanovitz avatar tboning avatar tleek avatar volpino avatar yrp604 avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.