  Textual adversarial attacking has received wide and increasing attention in
recent years. Various attack models have been proposed, which are enormously
distinct and implemented with different programming frameworks and settings.
These facts hinder quick utilization and fair comparison of attack models. In
this paper, we present an open-source textual adversarial attack toolkit named
OpenAttack to solve these issues. Compared with existing other textual
adversarial attack toolkits, OpenAttack has its unique strengths in support for
all attack types, multilinguality, and parallel processing. Currently,
OpenAttack includes 15 typical attack models that cover all attack types. Its
highly inclusive modular design not only supports quick utilization of existing
attack models, but also enables great flexibility and extensibility. OpenAttack
has broad uses including comparing and evaluating attack models, measuring
robustness of a model, assisting in developing new attack models, and
adversarial training. Source code and documentation can be obtained at
https://github.com/thunlp/OpenAttack.
