thunlp/BkdAtk-LWS
Code and data of the ACL 2021 paper "Turn the Combination Lock: Learnable Textual Backdoor Attacks via Word Substitution"
This project helps researchers and developers working with natural language processing (NLP) models to understand and evaluate potential security vulnerabilities. It provides tools to create 'backdoor attacks' by subtly altering words in training data. The output is a "poisoned" NLP model that behaves normally until a specific, secret phrase is encountered, revealing the vulnerability. This is intended for NLP security researchers and AI safety engineers.
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Use this if you need to research or demonstrate how textual backdoor attacks work on NLP models, or to test the robustness of your own models against such attacks.
Not ideal if you are looking for a general-purpose NLP library or a tool for data preprocessing or model training for typical tasks.
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16
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6
Language
Python
License
MIT
Category
Last pushed
Jun 29, 2021
Commits (30d)
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