Secure Open-Source AI Agents with Existing DLP

You can now secure open-source AI agents using your existing Data Loss Prevention, or DLP, policies. This approach helps govern how AI agents access and move enterprise data. Open-source AI guardrails identify unsafe behavior, while enterprise DLP protects sensitive data. Together, they offer stronger protection for AI workflows without needing a separate security framework. For example, Symantec Distributed Detection Service extends current DLP policies to secure AI agent interactions. The market is moving towards keeping frontier models separate and bringing governed enterprise data to them on demand. This is done through the Model Context Protocol, or MCP, which is supported by companies like Anthropic, OpenAI, Google, and Microsoft. This means data governance needs to happen at the connection point between your data and the AI model. Building effective guardrails is a top challenge for IT and data leaders, cited by 76% in a recent survey. This integrated approach allows organizations to leverage their current security investments for new AI challenges.