Microsoft Confirms Copilot Bug Exposed Customer Emails Despite Data Policies
Microsoft has acknowledged a critical bug in its Copilot AI feature that inadvertently summarized confidential emails from paying customers, bypassing established data loss prevention (DLP) policies. The vulnerability, active in late 2025 and early 2026, raised serious concerns over enterprise data privacy and AI governance.

Microsoft has confirmed a significant security flaw in its Microsoft 365 Copilot AI assistant that allowed the system to process and summarize confidential corporate emails, even when strict data loss prevention (DLP) policies were in place. The bug, which was active from late 2025 through early 2026, exposed sensitive communications of enterprise customers to the AI model, undermining foundational trust in Microsoft’s AI-driven productivity suite.
According to BleepingComputer, the vulnerability stemmed from a misconfiguration in Copilot’s email summarization module, which failed to properly validate DLP policy restrictions before accessing message content. This meant that emails marked as confidential, restricted, or subject to compliance regulations—such as those containing personally identifiable information (PII), financial data, or legal communications—were still ingested by Copilot for summarization purposes. The issue affected organizations using Microsoft 365 E3, E5, and Business Premium plans that had configured DLP policies to block AI access to sensitive content.
Office365ITPros reported on February 13, 2026, that Microsoft had issued an emergency patch and updated its DLP policy enforcement protocols to ensure Copilot Chat and related AI features would no longer override customer-defined data boundaries. The article detailed how the fix introduced a new layer of policy validation at the data ingestion stage, requiring explicit policy compliance before any email content could be processed by the AI model. "This was a systemic oversight," said Tony Redmond, a leading Microsoft 365 consultant and author of the Office365ITPros analysis. "Organizations trusted Microsoft’s assurances that DLP policies would be honored. This breach of that trust was profound."
While Microsoft has not confirmed whether the bug was exploited by external actors, a separate report from MSN highlighted a broader pattern of cybercriminal activity targeting Windows and Office vulnerabilities during the same timeframe. Microsoft’s own advisory, referenced in the MSN article, warned of active exploitation of zero-day vulnerabilities in Office applications, raising concerns that the Copilot bug could have been weaponized to harvest sensitive data at scale. Security researchers speculate that attackers may have used social engineering or compromised credentials to trigger Copilot’s summarization feature, effectively turning a productivity tool into an unauthorized data exfiltration channel.
Legal and compliance teams across global enterprises have since initiated internal audits of AI usage policies. Industry watchdogs, including the International Association of Privacy Professionals (IAPP), have called for mandatory transparency reports from AI vendors regarding data ingestion practices. "This isn’t just a bug—it’s a governance failure," said Dr. Elena Vargas, a data ethics researcher at Stanford. "If AI systems can bypass corporate policies designed to protect privacy, then we need regulatory frameworks that treat AI access as a security control, not a feature."
Microsoft has since updated its Copilot documentation to emphasize that DLP policies must be actively monitored and tested, and has offered affected customers free compliance reviews. The company stated it has not found evidence of data misuse or external breaches directly tied to the bug, but acknowledged the incident as a "serious lapse in our data protection architecture."
As organizations worldwide accelerate AI adoption, this incident underscores a critical tension: the promise of AI-driven efficiency versus the imperative of data sovereignty. For now, Microsoft’s response has been technical, but the broader industry is demanding structural change—ensuring that AI systems are not merely intelligent, but also inherently trustworthy.


