mpuodziukas-labs/adversarial-ml-toolkit

Adversarial ML toolkit: FGSM, PGD, prompt injection, data poisoning, OWASP LLM Top 10 defenses

/ 100

Experimental

No License No Package No Dependents

Maintenance 13 / 25

Adoption 0 / 25

Maturity 1 / 25

Community 0 / 25

Stars

—

Forks

—

Language

Python

License

—

Category

Last pushed

Mar 19, 2026

Commits (30d)

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mpuodziukas-labs/adversarial-ml-toolkit"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

QData/TextAttack

TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model...

ebagdasa/backdoors101

Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct...

THUYimingLi/backdoor-learning-resources

A list of backdoor learning resources

zhangzp9970/MIA

Unofficial pytorch implementation of paper: Model Inversion Attacks that Exploit Confidence...

LukasStruppek/Plug-and-Play-Attacks

[ICML 2022 / ICLR 2024] Source code for our papers "Plug & Play Attacks: Towards Robust and...