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Decision-Theoretic Incident Response Planning with a Lightweight Large Language Model

A decision-support system powered by a foundation model for recovering from cyberattacks in networked systems.

Requirements

  • Python 3.8+
  • torch
  • torchvision
  • numpy
  • transformers
  • peft
  • bitsandbytes
  • accelerate
  • hf-transfer

Development Requirements

  • Python 3.8+
  • flake8 (for linting)
  • flake8-rst-docstrings (for linting docstrings)
  • tox (for automated testing)
  • pytest (for unit tests)
  • pytest-cov (for unit test coverage)
  • mypy (for static typing)
  • mypy-extensions (for static typing)
  • mypy-protobuf (for static typing)
  • types-PyYaml (for static typing)
  • types-paramiko (for static typing)
  • types-protobuf (for static typing)
  • types-requests (for static typing)
  • types-urllib3 (for static typing)
  • sphinx (for API documentation)
  • sphinxcontrib-napoleon (for API documentation)
  • sphinx-rtd-theme (for API documentation)
  • pytest-mock (for mocking tests)
  • pytest-grpc (for grpc tests)

Installation

# install from pip
pip install llm_recovery==<version>
# local install from source
$ pip install -e llm_recovery
# or (equivalently):
make install
# force upgrade deps
$ pip install -e llm_recovery --upgrade
# git clone and install from source
git clone https://github.com/Limmen/llm_recovery
cd llm_recovery
pip3 install -e .
# Install development dependencies
$ pip install -r requirements_dev.txt

Development tools

Install all development tools at once:

make install_dev

or

pip install -r requirements_dev.txt

Static code analysis

To run the Python linter, execute the following command:

flake8 .
# or (equivalently):
make lint

To run the mypy type checker, execute the following command:

mypy .
# or (equivalently):
make types

Unit tests

To run all the unit tests, execute the following command:

pytest
# or (equivalently):
make unit_tests

To run tests of a specific test suite, execute the following command:

pytest -k "ClassName"

To generate a coverage report, execute the following command:

pytest --cov=llm_recovery

Run tests and code analysis in different python environments

To run tests and code analysis in different python environments, execute the following command:

tox
# or (equivalently):
make tests

Create a new release and publish to PyPi

First build the package by executing:

python -m build
# or (equivalently)
make build

After running the command above, the built package is available at ./dist.

Push the built package to PyPi by running:

python -m twine upload dist/*
# or (equivalently)
make push

To run all commands for the release at once, execute:

make release

Author & Maintainer

Kim Hammar kimham@kth.se

Copyright and license

LICENSE

Creative Commons

(C) 2025, Kim Hammar

Metadata

Release files for llm-recovery 0.0.13

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Source distribution for llm-recovery 0.0.13
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Table of built distributions (wheels) for llm-recovery 0.0.13
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llm_recovery-0.0.13-py3-none-any.whl Python 3 none any Details

Total release size: 47.0 kB

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