{"data":{"id":"3e9623a3-a146-45b1-a5c5-70ce5330c24f","title":"Microsoft releases open-source tools to operationalize AI agent safety","summary":"Microsoft has released two open-source tools, Rampart and Clarity, designed to catch safety problems in AI agents (software systems that can take actions autonomously) earlier in development. Rampart automates repeated safety testing throughout the development process to find issues like prompt injection (tricking an AI by hiding instructions in its input) and unsafe tool use, while Clarity helps engineers document and validate their design assumptions before coding begins.","solution":"Microsoft's explicit solutions are: (1) Rampart, which transforms red-team findings into repeatable automated tests that run continuously in CI/CD workflows (continuous integration/continuous deployment, the automated systems developers use to test and release code) to surface issues before production; and (2) Clarity, a tool available as a desktop app, web UI, or embedded in coding agents that guides engineers through structured conversations about agent behavior, permissions, and trust boundaries, with outputs saved as markdown files in the repository for review and version control.","labels":["safety","security"],"sourceUrl":"https://www.csoonline.com/article/4175592/microsoft-releases-open-source-tools-to-operationalize-ai-agent-safety-2.html","publishedAt":"2026-05-21T10:28:06.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"news","affectedPackages":null,"affectedVendors":["Microsoft"],"affectedVendorsRaw":["Microsoft"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":"2026-05-21T10:28:06.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["safety","integrity"],"aiComponentTargeted":"agent","llmSpecific":false,"classifierConfidence":0.92,"researchCategory":null,"atlasIds":null}}