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OCCAM: Object Culling and Concretization for Assurance Maximization

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Description

OCCAM is a whole-program partial evaluator for LLVM bitcode. It can be used to debloat programs and shared/static libraries. To do so, it relies on a manifest that describes the specific deployment context. It uses LLVM version 10.

The available documentation can be found in our wiki.

Docker

A pre-built and installed version of OCCAM can be obtained using Docker:

docker pull sricsl/occam:bionic
docker run -v `pwd`:/host -it sricsl/occam:bionic

Alternatively, it can be built and installed from source as follows.

Prerequisites

OCCAM works on Linux, macOS, and FreeBSD. It depends on an installation of LLVM. OCCAM is built on the top of llvm-10.0 which requires a C++ compiler supporting c++14. You will also need the Google protocol buffer compiler protoc and the corresponding Python package. Some OCCAM components (such as sea-dsa and crab require the boost library >= 1.65.

If you need to generate application bitcode (that OCCAM operates on), you may want to install WLLVM, either from the the pip package or the GitHub repository.

The test harness also requires lit and FileCheck. FileCheck can often be found in the binary directory of your LLVM installation. However, if you built your own, you may need to read this. Hint: the build produces it, but does not install it. (Try locate FileCheck, then copy it to the bin directory.)

Detailed configuration instructions for Ubuntu 18.04 can be gleaned from bootstrap.sh.

Building and Installing

Set where OCCAM's library will be stored:

  export OCCAM_HOME={path to location in your home directory}

Point to your LLVM's location, if non-standard:

  export LLVM_HOME=/usr/local/llvm-10.0
  export LLVM_CONFIG=llvm-config-10.0

Set where system libraries, including Google Protocol Buffers, are located:

  export LD_FLAGS='-L/usr/local/lib'

Clone, build, and install OCCAM with:

  git clone --recurse-submodules https://github.com/SRI-CSL/OCCAM.git
  make
  make install
  make test

This material is based upon work supported by the National Science Foundation under Grant ACI-1440800. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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