Back to directory

RAMPART

A pytest-native framework for writing and running safety and security tests against agentic AI applications, covering adversarial attacks, benign failures, and a range of harm categories with evaluation-driven assertions.

RAMPART

RAMPART (Risk Assessment & Measurement Platform for Agentic Red Teaming) provides a structured, developer-friendly way to write and run safety and security tests for AI agents. Tests integrate directly with pytest, so assertions about agent behavior read like ordinary test cases rather than a separate evaluation harness.

Test coverage spans adversarial attacks intended to make an agent misbehave, benign failures that occur without any adversarial intent, and a broad range of harm categories, all judged through evaluation-driven assertions rather than manual review.

It is written in Python and released under the MIT license by Microsoft.

More in Testing

See all 69
  • Canary

    runcanary.ai

    An independent testing service, backed by Y Combinator, that runs an application and tries to break every change an AI coding agent makes, reporting what would have reached production.

  • MoEWatch

    github.com

    A diagnostic and audit library for Mixture-of-Experts models in HuggingFace Transformers that instruments router modules to catch expert collapse, routing entropy collapse and load imbalance during training.

  • Mockwave

    github.com

    An open-source, multi-protocol mock server for HTTP, GraphQL, SOAP, and gRPC, with weighted traffic splitting, dynamic JavaScript responses, chaos-testing fault injection, and an MCP server so an AI assistant can generate mock rules directly.