Microsoft storms RAMPART, adds Clarity to agentic AI safety

Summary

Security Microsoft storms RAMPART, adds Clarity to agentic AI safety Redmond open sources two tools for building and maintaining safer agents Microsoft on Wednesday open-sourced two AI tools designed to help developers and security teams build and maintain safer AI agents.The first is called RAMPART, which stands for Risk Assessment and Measurement Platform for Agentic Red Teaming. It’s a pytest framework for agentic AI applications built on Microsoft’s open‑source PyRIT toolkit that embeds automated red‑team tests into CI/CD pipelines. This allows developers to simulate real‑world attack scenarios - like prompt injection - and verify that agents stay within approved tool use, actions, and behavioral boundaries. It also supports statistical trials, meaning that teams can set policies such as “this action must be safe in at least 80 percent of runs,” to account for models’ probabilistic behavior. Plus, it allows red teams and incident responders to reproduce any AI security findings to ensure agents behave as intended - and that security mitigations work as they should. “It’s high time we stop talking about AI safety as a philosophy and start thinking about AI safety as an engineering discipline,” Ram Shankar Siva Kumar, Microsoft’s data cowboy and founder of its AI red team, told The Register. Microsoft has been using RAMPART internally, and while Kumar said he couldn’t provide specific details, he told us that a security researcher found an issue, and then the Redmond red team used RAMPART to test for the flaw across the agentic AI application.“RAMPART was able to take that one particular vector and find close to 100 different variants of that vector,” Kumar said. “And then we were able to use RAMPART to essentially go through this asset and see is this working, not just one time, not two times, but close to 300 times. We were also able to do in the context of multi-turn conversations.”The testing framework also allowed the developers to build mitigations into the ...