Add hooks, fickling.load(), and a JSON output format for usability #79
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Add hooks, fickling.load(), and a JSON output format for usability #79
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December 13, 2023 10:33
Boyan-MILANOV
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@suhacker1 good job on this! It needs some restructuring but the core idea is there :) I've left a bunch of comments, some are nits, but most of them are about code and architecture. Let's address all of them and then I'll make a second pass on the PR.
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Note: We decided not to include the PyTorch global hook in this PR. We also decided to remove the UNKNOWN severity type as we felt it was redundant. |
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@Boyan-MILANOV This is ready for another review! |
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LGTM now! Good job! 🚀
dguido
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Renames AGENTS.md to CLAUDE.md and expands it from vulnerability reporting guidance into full project context: commands, architecture, design rules, testing patterns, code style, and CI. Design rules distilled from PR review history (#79, #87, #195, #207, #210, #220). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
thomas-chauchefoin-tob
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Renames AGENTS.md to CLAUDE.md and expands it from vulnerability reporting guidance into full project context: commands, architecture, design rules, testing patterns, code style, and CI. Design rules distilled from PR review history (#79, #87, #195, #207, #210, #220). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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This PR makes multiple feature additions for usability. Specifically, this PR adds a fickling import hook, global function hook,
fickling.load()function, and a JSON output format for thecheck_safetycomponent of the CLI. Each of these features can make it easier to integrate fickling into different codebases and tools.This PR also updates the examples and tests to reflect these new features. Additional important changes made include:
is_likely_safeinfickle.pywithcheck_safetyinanalysis.py: A newcheck_safetymethod was added tofickle.pyas a wrapper withis_likely_safebeing marked for deprecation.analysis.py: Not only wasProtoAnalysissplit for simplicity, but more structure was added throughout the different analysis classes to enable the reporting of detailed results.pytorch.py: ThePyTorchModelWrapperclass now reports the identified file formats from the validation method.I would especially appreciate feedback on:
torch.loadshould be includedExample JSON Output ("test_unused_variables.json"):