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Security
Microsoft 365 Copilot is becoming a major security discussion as AI gains access to organizational data, permissions, and business workflows. This guide explains the risks, governance requirements, and security best practices MSPs should understand before deploying Copilot for clients.
Level
Tuesday, June 16, 2026
Microsoft 365 Copilot is rapidly becoming a security topic, not just a productivity topic. As organizations deploy AI assistants across email, documents, chats, meetings, and business data, security teams are discovering that Copilot introduces new risks around permissions, data exposure, prompt injection, governance, and compliance.
That reality became even more apparent during Microsoft's June 2026 Patch Tuesday. Security updates included critical vulnerabilities affecting Microsoft Copilot and Microsoft 365 Copilot, including command injection flaws that could lead to code execution or information disclosure. According to the National Vulnerability Database, CVE-2026-45497 is a command injection vulnerability in Microsoft Copilot that could allow an authorized attacker to execute code over a network. The National Vulnerability Database also lists CVE-2026-42824 as a command injection vulnerability in Microsoft 365 Copilot that could allow an unauthorized attacker to disclose information over a network. The broader June 2026 security release included more than 200 vulnerabilities across Microsoft products, as noted by the SANS Internet Storm Center.
For MSPs, this serves as an important reminder: Copilot should be treated as a security-sensitive business application. Organizations that focus only on productivity gains may overlook governance and security requirements that become increasingly important as AI gains access to business data.
Traditional productivity tools generally require users to manually search for information. Microsoft 365 Copilot changes that model by actively retrieving, summarizing, and generating content based on data available through Microsoft Graph and the user's permissions.
According to Microsoft Learn, Copilot grounds responses using organizational data that users already have permission to access. This is an important distinction because Copilot does not bypass security controls. Instead, it can amplify existing permission issues.
For example, many organizations have accumulated years of SharePoint sites, Teams channels, OneDrive folders, and Microsoft 365 groups with overly broad permissions. Employees may technically have access to sensitive information they never knew existed because finding it required effort. Copilot can make that information significantly easier to discover.
This means the question is no longer simply, "Can users access this data?" The question becomes, "Should users be able to instantly discover, summarize, and reuse this data through AI?"
As organizations adopt generative AI, data governance becomes a critical security control rather than an administrative exercise.
The June 2026 Patch Tuesday release marked an important shift in how security professionals should think about AI assistants.
Historically, discussions about AI tools focused on ethics, hallucinations, productivity, or future risks. The June vulnerabilities demonstrated that AI assistants now belong firmly within mainstream cybersecurity programs.
The most notable Copilot-related vulnerabilities included:
Importantly, some of these vulnerabilities were addressed as cloud service issues by Microsoft, meaning customers may not have needed to install software updates themselves. However, that does not reduce their significance. Instead, it highlights that MSPs must monitor AI-related security advisories and understand how cloud-based AI services fit into their vulnerability management processes.
The lesson is not that Copilot is inherently unsafe. The lesson is that AI assistants now represent a new attack surface that requires ongoing security oversight.
While software vulnerabilities receive attention, they are only one part of the Copilot security picture.
For most organizations, the greatest risks come from how Copilot interacts with business data and user permissions.
One of the most significant Copilot security risks is oversharing.
Organizations often discover permission problems only after deploying AI tools. SharePoint sites that were intended for a specific department may be visible to broader groups. Old Teams channels may contain confidential discussions. Archived project folders may still be accessible to employees who no longer need them.
Because Copilot can summarize and retrieve information across Microsoft 365, it can expose weaknesses in access control that previously went unnoticed.
This is why permission hygiene should be considered a prerequisite for Copilot deployment.
Microsoft provides security and compliance controls that help protect sensitive information. According to Microsoft Learn, Microsoft 365 Copilot respects existing permissions and integrates with data protection technologies.
Organizations can further reduce risk using sensitivity labels and information protection controls. The documentation from Microsoft Purview explains how sensitivity labels can classify and protect sensitive content across Microsoft 365 environments.
However, these controls only work when they are properly configured and maintained.
Prompt injection is emerging as one of the most important AI-specific security threats.
In a prompt injection attack, malicious instructions are embedded within content that an AI system processes. These instructions can influence model behavior and potentially cause unintended actions.
The AI security community increasingly recognizes prompt injection as a major concern. The OWASP Foundation includes prompt injection among the most critical risks for large language model applications.
As organizations adopt AI assistants, security teams should assume prompt injection attempts will become more common.
Another overlooked risk involves user behavior.
Employees may assume AI-generated responses are complete, accurate, and trustworthy. In reality, AI-generated outputs should still be reviewed and validated.
Overreliance on AI can lead to poor decisions, inaccurate reporting, compliance issues, and operational mistakes.
Organizations should train users to treat Copilot as an assistant rather than an authority.
Many organizations approach Copilot deployment similarly to how they deploy a new productivity application.
That approach can create problems.
Copilot governance should be established before licenses are assigned to large groups of users. According to Microsoft Learn, organizations should address oversharing risks, establish governance controls, and evaluate compliance requirements before broad deployment.
Similarly, Microsoft's Zero Trust guidance from Microsoft Learn emphasizes least-privilege access, identity protection, sensitivity labels, and data loss prevention controls.
Before enabling Copilot, MSPs should evaluate:
Organizations that complete these steps before deployment typically experience fewer security issues and gain greater confidence in AI adoption.
Securing AI assistants requires a layered approach that combines identity security, governance, monitoring, and user education.
Identity remains the foundation of Copilot security.
Organizations should implement multifactor authentication, conditional access policies, privileged access controls, and regular account reviews. Since Copilot operates within the context of user permissions, identity security directly impacts AI security.
Permission reviews should focus on SharePoint, OneDrive, Teams, Microsoft 365 Groups, and guest access.
Many organizations discover permission sprawl during Copilot readiness assessments. Addressing these issues before deployment reduces risk significantly.
Data classification helps organizations determine which information should be available to AI systems and which information requires additional protection.
The guidance from Microsoft Purview highlights how organizations can use sensitivity labels, DLP policies, and compliance controls to protect information used by generative AI applications.
Copilot governance is not a one-time project.
Organizations should continuously monitor for permission drift, unusual access patterns, risky sharing behavior, policy violations, and data exposure risks.
Regular reviews help ensure that security controls remain aligned with business needs.
Employees should understand:
User awareness remains one of the most effective risk reduction strategies.
The answer depends on the client's security maturity.
Organizations with strong Microsoft 365 governance, mature identity controls, established compliance programs, and effective monitoring capabilities are often well positioned to benefit from Copilot.
Organizations with unmanaged permissions, excessive sharing, weak security controls, or limited governance may introduce unnecessary risk by deploying Copilot too quickly.
A phased rollout is usually the safest approach.
MSPs can begin with a small pilot group, evaluate data exposure risks, review user behavior, identify governance gaps, and refine security controls before expanding deployment.
This approach allows clients to realize productivity gains while maintaining appropriate security oversight.
The broader AI risk management principles outlined by the National Institute of Standards and Technology support this measured approach by encouraging organizations to identify, assess, and manage AI-related risks throughout the technology lifecycle.
Effective Copilot governance typically includes five core practices:
Evaluate identity security, permissions, compliance requirements, and data governance before deployment.
Review SharePoint permissions, Microsoft 365 groups, guest access, and external sharing settings.
Implement sensitivity labels, DLP policies, encryption controls, and classification standards.
Track access patterns, permission changes, policy violations, and potential exposure risks.
Provide clear guidance regarding acceptable AI use, security expectations, and responsible data handling practices.
Organizations that follow these practices are generally better positioned to balance AI productivity benefits with security requirements.
Microsoft 365 Copilot security depends on more than Microsoft 365 settings alone.
Organizations still need visibility into endpoints, user activity, patching status, device health, and operational support workflows. While Microsoft provides the underlying Copilot platform and governance controls, MSPs need operational tools that help them manage the broader IT environment.
Level helps MSPs maintain endpoint visibility, support users remotely, and manage day-to-day operational workflows that surround AI adoption initiatives. As organizations deploy technologies such as Microsoft 365 Copilot, maintaining visibility into the endpoints accessing those services remains an important part of overall IT operations.
For MSPs, Copilot adoption often creates opportunities to provide security assessments, Microsoft 365 reviews, governance consulting, readiness evaluations, and ongoing managed services. Level can support the operational side of those engagements by helping MSPs manage and support client environments efficiently.
Microsoft Copilot security risks include oversharing, excessive permissions, prompt injection attacks, sensitive data exposure, user overreliance on AI, and governance failures.
Yes. June 2026 Patch Tuesday included vulnerabilities affecting Microsoft Copilot and Microsoft 365 Copilot. The National Vulnerability Database and the National Vulnerability Database document two notable command injection vulnerabilities disclosed during that release cycle.
No. According to Microsoft Learn, Copilot operates within the permissions already assigned to the signed-in user.
Prompt injection is an attack technique that uses malicious instructions embedded within content processed by AI systems. The OWASP Foundation identifies prompt injection as one of the most significant security risks facing LLM-based applications.
Not necessarily. MSPs should evaluate governance maturity, security controls, permissions, compliance requirements, and monitoring capabilities before recommending deployment.
Organizations can improve Copilot security through identity protection, permission reviews, sensitivity labels, DLP policies, continuous monitoring, and user education.
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