TextAttack
A Python framework for adversarial attacks and NLP model training.
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is TextAttack?
TextAttack is a Python library that enables researchers and developers to perform adversarial attacks, data augmentation, and model training in natural language processing tasks. It's designed to help improve the robustness of NLP models against adversarial examples.
Key differentiator
“TextAttack stands out by offering a robust set of tools specifically tailored for adversarial attacks and data augmentation in NLP, making it an essential library for researchers and developers focused on enhancing model reliability.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Most examples and pre-trained models are in English, lacking comprehensive support for other languages
Adversarial attacks and data augmentation processes may require significant computational resources and time
Fit analysis
Who is it for?
✓ Best for
Researchers looking to test their NLP models' robustness against adversarial attacks
Developers needing tools for advanced data augmentation in NLP tasks
Teams working on improving the reliability of text classification and generation systems
✕ Not a fit for
Projects requiring real-time processing capabilities, as TextAttack is designed for offline experimentation
Users looking for a comprehensive cloud-based service with managed infrastructure support
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with TextAttack
Step-by-step setup guide with code examples and common gotchas.