When AI Ignores Your Labels: What Copilot’s Confidential Email Bug Really Exposes

What happened with Copilot isn’t just “a bug,” it’s a preview of a structural problem in today’s AI tech scene. Sensitivity labels and DLP policies were configured correctly, but the AI layer still accessed and summarized confidential content in ways the controls weren’t designed to anticipate. As more work is mediated by copilots, agents, and autonomous workflows, these gaps stop being edge cases and quickly become the norm.

Bonfy was built for exactly this class of failure. Rather than trusting every AI system and plugin to implement data controls perfectly, Bonfy applies adaptive content security across the entire data path, including email, files, SaaS apps, collaboration tools, Copilot, AI agents, and custom GenAI workflows. Our entity‑aware engine understands not just what the content is, but who it belongs to (customers, consumers, internal entities) and how it is supposed to be used, enabling high‑accuracy detection and real enforcement when AI systems read, index, or generate sensitive information.

In a Copilot-like scenario, Bonfy provides three critical guardrails:

1. Upstream AI data access: We automatically classify and label unstructured content with granular, contextual, entity‑aware tags, and can publish those labels into Microsoft Purview so AI systems only ground on appropriately governed content instead of blindly indexing every sent item or draft.
2. Data‑in‑use controls for AI and agents: Through our MCP Server interface and real‑time inspection, AI agents can call Bonfy during their reasoning and composition process to ask “is this content safe to use or send?” before a summary or response is generated, not after it has already leaked.
3. Downstream communication protection: Bonfy evaluates outbound email and content in real time, catching confidential clauses, customer‑specific data, PII, and other high‑risk material before it leaves the organization, even when AI systems are accelerating how fast people draft and send information.

The lesson from this Copilot incident is not that organizations should slow down AI adoption, but that they need a unified, AI‑aware data security layer that is independent of any single vendor’s assistant or configuration model.

Legacy DLP and static label‑driven controls were never designed for multi‑hop, AI‑driven workflows that continuously read, transform, and generate content across tools and channels. Bonfy gives security and governance teams the visibility and prevention they need across humans, systems, and AI agents, so the next “DLP bypass” by an AI feature becomes a non‑event instead of tomorrow’s headline.

If you’re interested in getting a live demo of Bonfy in action, click here.