🗣️ Tool to generate adversarial text examples and test machine learning models against them

Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]

Task-agnostic universal black-box attacks on computer vision neural network via procedural noise (CCS'19)

[NeurIPS2020] The official repository of "AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows".

Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

Sparse and Imperceivable Adversarial Attacks (accepted to ICCV 2019).

[NeurIPS'20] Learning Black-Box Attackers with Transferable Priors and Query Feedback

Ensemble Adversarial Black-Box Attacks against Deep Learning Systems Trained by MNIST, USPS and GTSRB Datasets

Code for the paper "Addressing Model Vulnerability to Distributional Shifts over Image Transformation Sets", ICCV 2019

Black-box Adversarial Attacks on Video Recognition Models. (VBAD)

QROA: A Black-Box Query-Response Optimization Attack on LLMs

📄 [Talk] OFFZONE 2022 / ODS Data Halloween 2022: Black-box attacks on ML models + with use of open-source tools

Code for the ICLR 2022 paper "Attacking deep networks with surrogate-based adversarial black-box methods is easy"

Distributed Black-Box Attacks against Image Classification.

Deep Learning Cloud Service for Black-Box Adversarial Attacks

[ICML 2022] Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems

Distributed Black-Box attacks against Image Classification.

Code for 'SoK: Pitfalls in Evaluating Black-Box Attacks' , SaTML 2024.

Attack models that are pretrained on ImageNet. (1) Attack single model or multiple models. (2) Apply white-box attacks or black-box attacks. (3) Apply non-targeted attacks or targeted attacks.