Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

America's cybersecurity agency left its production credentials sitting in a public GitHub repo for six months. The same failure pattern is now being automated by AI agents in every enterprise running Cursor, Claude Desktop, or Copilot.

Your AI agents had a productive day. Nobody can tell you what data they touched. A developer opens Cursor and connects it to a GitHub MCP server and a Postgres MCP server. The agent reads the repo to understand a schema change, finds an AWS access key in a config file, and uses it to run a migration against staging. The key now lives in the agent's context, in the Postgres query log, in the chat history, and in whatever artifact the developer copies out. No alert fired. No policy triggered.

Each requires MCP observability that legacy DLP cannot provide.

What you need to know: MCP can evade traditional DLP, IAM, and SIEM controls because agent traffic looks like authorized API calls, sensitive data is semantically transformed before it leaves the perimeter, and exfiltration happens through tool invocations rather than file transfers.

What you need to know: MCP bypasses traditional DLP, IAM, and SIEM controls because agent traffic looks like legitimate API calls, sensitive data is semantically transformed before it leaves, and exfiltration happens through tool calls rather than file transfers.