This suite of tests is based on Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models. Adversarial GLUE evaluates how robust a Large Language Model (LLM) is to different types of adversarial prompts across a range of tasks. The results of these tests offer insights that inform users on the potential risks and unsafe behaviors that a model might exhibit once it is deployed in their application and targeted by adversaries that attempt to misuse the model in different tasks.