Copilot Bypasses Labels Twice, Evades DLP

• The CW1226324 bug specifically affected Copilot Chat's ability to process emails with confidentiality labels applied, bypassing Microsoft's DLP policies designed to protect sensitive information[1][3] • CVE-2026-21521 exploits CWE-150 (Improper Neutralization of Escape, Meta, or Control Sequences) through malicious input containing escape sequences that manipulate Copilot's parsing behavior[2] • The vulnerability requires user interaction, likely through social engineering, to process attacker-controlled content through Copilot[2] • Microsoft's response included network-level input validation, temporary functionality limitations for untrusted content, network segmentation, and enhanced monitoring on Copilot services[2] • The bug affected Copilot's interaction with Microsoft 365 apps including Word, Excel, PowerPoint, and Outlook, which began rolling out to business customers in September 2025[3]

These incidents highlight critical gaps in AI security architecture where violations occur within proprietary retrieval pipelines, bypassing traditional security tools like EDR and WAF. Organizations embedding generative AI into data security operations (82% according to Microsoft's 2026 Data Security Index) face increased risk if AI systems themselves become attack vectors. The pattern of repeated Copilot vulnerabilities—from 2024 Copilot Studio exploits to 2026 DLP bypasses—suggests that AI security requires fundamentally different approaches than traditional application security, potentially driving demand for specialized AI governance solutions and stricter controls on AI access to sensitive data repositories.