Vulnerability Report

The vulnerability report provides information about critical vulnerabilities related to model attacks. It includes an overview of the severity of the issue and associated risks, and suggests mitigation measures.

Following are the different parts explaining the model metrics in detail:

Part 1: Overview This section of the report presents metadata information for the job ID, including details such as the attack type, number of attack queries, stolen model accuracy, alert level (low or high), and whether defense measures are recommended or not.

Part 2: Security In this section of the report, we emphasize the relative metrics score achieved by the extracted model.

Part 3: Performance In this section of the report, we examine the critical aspects of inference time and respective metrics for both the original model and the extracted model. We discuss the time required for the models to generate predictions on new data, as well as the performance metrics used to measure their accuracy and overall effectiveness.

Part 4: Drift This section highlights the application of statistical tests for detecting data drift. Data drift refers to changes in the statistical properties of the input data used to train a model. We will introduce this upcoming feature to our product.

Part 5: Appendix The Appendix section of the report serves as a comprehensive resource, offering essential information regarding the architectures of both the Original Model and Model attack type.

To see sample vulnerability report for respective attack types, refer the below table.