FAVD: Featherweight Assisted Vulnerability Discovery

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Deep LearningFAVD
Overview

source under MIT license data under CC BY 4.0 license DOI

FAVD: Featherweight Assisted Vulnerability Discovery

This repository contains the replication package for the paper "Featherweight Assisted Vulnerability Discovery", David Binkley, Leon Moonen, Sibren Isaacman, Information and Software Technology, 2022, 106844, ISSN 0950-5849, DOI: 10.1016/j.infsof.2022.106844. https://www.sciencedirect.com/science/article/pii/S0950584922000209.

The replication package is archived on Zenodo with DOI: 10.5281/zenodo.5957264. The source code is distributed under the MIT license, the data is distributed under the CC BY 4.0 license.

Repository Organization

The overall process consists of three steps, organized as three directories:

  1. gathering of the labeled function names that are used as the source for step 2, in names
  2. dangerous word identification, in dangerous-words
  3. analysis of the data gathered during step 2, in analysis

The directory Model holds a copy of the pre-trained LAVDNN model as provided by the authors at https://github.com/StablelJay/LAVDNN/raw/master/Model/model_of_LAVDNN

Requirements

The following tools are required for the replication:

  • python >= 3.5
  • R
  • tcsh
  • csvcut from csvkit
  • cntk as keras backend for running the LAVDNN model

In addition, the following python packages are needed

Finally, for the analysis in step 3, the following R libraries are needed:

  • agricolae, ggplot2, reshape2, xtable

Citation

If you build on this data or code, please cite this work by referring to the paper:

@article{binkley2022:featherweight,
   title = {Featherweight assisted vulnerability discovery},
   author = {David Binkley and Leon Moonen and Sibren Isaacman},
   journal = {Information and Software Technology},
   pages = {106844},
   year = {2022},
   issn = {0950-5849},
   doi = {https://doi.org/10.1016/j.infsof.2022.106844},
   url = {https://www.sciencedirect.com/science/article/pii/S0950584922000209},
   copyright = {Open Access},
   publisher = {Elsevier},
}

Acknowledgement

Part of this work has been financially supported by the Research Council of Norway through the secureIT project (RCN contract #288787).

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Comments
  • Bump numpy from 1.21 to 1.22.0 in /dangerous-words

    Bump numpy from 1.21 to 1.22.0 in /dangerous-words

    Bumps numpy from 1.21 to 1.22.0.

    Release notes

    Sourced from numpy's releases.

    v1.22.0

    NumPy 1.22.0 Release Notes

    NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

    • Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
    • A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
    • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
    • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
    • A new configurable allocator for use by downstream projects.

    These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

    The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

    Expired deprecations

    Deprecated numeric style dtype strings have been removed

    Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

    (gh-19539)

    Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

    numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

    (gh-19615)

    ... (truncated)

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secureIT
IKTLUSS funded research project on automated detection of software security vulnerabilities
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