---
title: Limitations
slug: limitations
docTags: 
createdAt: 2023-05-12T07:03:49.000Z
---

- Longer wait times (\~6-8 hours) can be expected if multiple earlier jobs are running. Users can keep observing the status of the job by using the GET API or the Dashboard link.
- "Number of attack queries" parameter currently is limited to \<=400000 for all tasks.
- "Number of classes" parameter should be  \<200 for all classification task type.&#x20;
- When executing the reference implementation, it is recommended to install the per-requisite libraries with exact versions.
- The product currently supports Tensorflow version between 2.3.0 and 2.15.0.
- Tabular classification supports scikit-learn models with preferred version 1.4.0 and XGBoost model version 2.0.3.
- Image classification evasion defense might be less effective against very small perturbation.
- Image classification poisoning - Encryption strategy and use model api endpoint not supported. Also it requires two clean model and one test model.&#x20;
- Tabular classification evasion analysis is only supported with a normalized dataset Between 0-1.
- The image should be in **RGB format**, and the model should be trained with images in this format.&#x20;
- When the number of attack queries is low, such as 1000 or fewer, the system automatically generates them.&#x20;