Microsoft Copilot AI combines the capabilities of large language models with content from Microsoft Graph — including emails, chats, messages, and Microsoft 365 productivity apps — to create one of the most powerful AI tools in the Microsoft ecosystem.
While Microsoft Copilot is not inherently insecure, its sophisticated orchestration engine can sometimes lead to the inadvertent exposure of sensitive data.
This blog examines the key Microsoft Copilot security concerns and outlines the access controls and security controls security teams can implement to help mitigate these risks.
Data Security Risks Associated with Copilot AI
Microsoft’s vision for Copilot is to remove the manual effort of repetitive work, freeing people to focus on creativity and decision-making. Copilot stands apart from other AI assistants and large language models like ChatGPT for one key reason: it retrieves and analyzes data from your Microsoft 365 environment and adds context to help you make informed decisions.
However, with LLMs like Microsoft 365 Copilot pulling information directly from your subscription, the risk of exposing sensitive information has only increased. Copilot can access all the sensitive data available to an individual based on their Microsoft 365 permissions. If those permissions are too broad or include erroneous access permissions, Copilot could surface proprietary data, business-sensitive data, customer data, or other business-critical files.
Beyond permission risks, there are other Microsoft Copilot security risks to consider, including data poisoning, prompt injection attacks, adversarial exploits, and unsafe API configurations — some involving malicious instructions hidden in user prompts — which we have covered in a separate post.
In this new data-sharing model, best practices like permissions management, sensitivity labeling, and strict access controls are essential for securing Microsoft Copilot AI and protecting organizational data.
Loose access controls
Misconfigured privacy settings, broad search visibility, and inconsistent access controls can allow sensitive information to end up in the wrong hands. If Microsoft 365 Copilot is already configured in SharePoint, its enhanced search capabilities can quickly compound this security risk.
Teams and SharePoint sites set to “public” can become unintentional data mines for Copilot users, increasing the likelihood that proprietary data, user documents, or other business-critical files will be surfaced to individuals who should not have access.
Poor Data Quality
Data poisoning is one of the most subtle threats to AI tools. It occurs when malicious actors inject corrupted or misleading training data into source files, manipulating Copilot’s output and introducing inaccurate patterns or biases.
Even without malicious interference, poor data hygiene can create significant data security risks. Outdated, incomplete, or stale documents in your Microsoft 365 environment can be surfaced by Copilot as if they were current. In turn, Copilot generates insights that may mislead decision-makers or misinform critical business processes.
A Framework for Securing Microsoft 365 Copilot
Balancing security with collaboration often creates tension — a fine line that an experienced Microsoft security consultant can help navigate.
At CrucialLogics, we focus on protecting your businesses by leveraging Microsoft technologies and the security controls you have. Our Microsoft 365 Copilot security and governance framework addresses all underlying permission models, security settings, groups, and link policies to protect sensitive information and reduce data security risks.
Below is an outline of the guiding framework we use to help IT teams and data security teams safeguard Copilot access.
AI Readiness Assessment
Copilot promises to remove the inefficiencies from your workflow, but it is not a simple plug-and-play tool. Its effectiveness depends entirely on the quality of your organizational data and IT hygiene. If your data is inaccurate, irrelevant, or poorly structured, the output from Microsoft 365 Copilot will be equally flawed.
An AI readiness review should include a thorough assessment of your security posture, compliance requirements, and adherence to regulations.
Security teams should also manage access controls carefully, putting the right safeguards in place to prevent unauthorized personnel from viewing or manipulating sensitive information. This includes reviewing permission models, eliminating erroneous access permissions, and ensuring only authorized users have the right access.
Finally, limit the use of shadow AI or non-approved cloud services to reduce the risk of data breaches and prevent organizational data from being processed by external platforms.
Sensitivity Labels
Microsoft 365 includes built-in sensitivity labels to help prevent data loss and control access to sensitive information. These labels act as guardrails, tagging data with classifications such as sensitive, confidential, company-wide, or department-specific categories like HR, marketing, or operations.
While this is a strong foundation for safeguarding business-critical files, the reality paints a grim picture. As employees create and update content, labels can become outdated or applied inconsistently, especially in large organizations. This not only increases security concerns but also adds complexity for data security teams.
Ideally, sensitivity labels should be intuitive, consistently named, and reviewed on a fixed schedule. During each audit, validate all sensitive files and ensure labels are correct, relevant, and up to date. Files without a sensitivity label should be assessed and classified appropriately to maintain effective data loss prevention.
SharePoint Governance
At the core of every Microsoft 365 workspace lies SharePoint, which serves as the primary repository for organizational data. Effective governance of data, permissions, and access is essential to prevent data leaks — both to and from AI tools like Microsoft 365 Copilot.
Ensure each user has the right access without unnecessary or excessive permissions. This aligns with a zero trust framework, which bases access on explicit verification, assumes breach as a possibility, and enforces least privilege.
Establish clear policies for site ownership and compliance. Site administrators should be able to identify inactive sites, notify their owners, and take appropriate actions such as archiving or restricting access to business-critical files.
For shared OneDrive sites, enforce strict access controls that consider device compliance, user location, and risk level. This ensures only authorized personnel can view or interact with sensitive data, reducing the likelihood of data security risks.
Data Loss Prevention
The foundation of strong data hygiene is a clear understanding of your data estate. Identify what types of data reside in SharePoint Online and OneDrive, assess their relevance, determine whether they contain sensitive information, and confirm if sensitivity labels are in place.
Microsoft 365 Copilot does not consider when a file was last modified — it will use the data as it exists and generate insights from it. If outdated or inaccurate source files remain in your environment, Copilot could surface misleading or irrelevant information.
Optimizing your data means archiving or deleting outdated content to reduce clutter and maintain relevance. Consolidate data across tenants by merging duplicates, removing redundancies, and ensuring proprietary data is stored securely.
Within SharePoint, update metadata and review team and group activity to identify inactive or unused spaces. This not only improves searchability for user documents but also minimizes the number of dormant workspaces that could pose security risks.
Establish a standardized process for creating new workspaces with pre-configured settings, ensuring a consistent structure and alignment with security compliance requirements.
Conditional Access Policies with Microsoft Entra
Ensure that tenant-level conditional access policies are correctly configured for Microsoft 365 Copilot. Using Microsoft Entra, security teams can control access to applications and resources based on factors such as user group, cloud action, location, device state, client app, and risk level.
These access policies are designed to ensure only authorized personnel can reach sensitive information. If a user attempts to access Microsoft 365 from outside the corporate network, they may be required to complete multi-factor authentication before proceeding.
Conditional access checks can also be combined with other verification steps — such as device compliance and user compliance — to enforce explicit verification and strengthen permission models. This layered approach to access controls reduces the risk of data breaches, erroneous access permissions, and exposure of business-critical files.
Conclusion
Broadly, Microsoft 365 Copilot only accesses user data within your Microsoft 365 tenant. It will not surface data owned by other guests in a group, and its foundational training is not based on your input, meaning you do not need to worry about Copilot using your prompts to train its model.
The primary concern is maintaining strong permissions, practicing good data hygiene, ensuring AI readiness, applying accurate sensitivity labels, training employees, and configuring access controls effectively.
Securing AI in your Microsoft 365 environment does not require investing in additional third-party tools. This aligns with our security philosophy at CrucialLogics: safeguarding your business with the Microsoft technologies you already own.
Contact us today for a tailored AI readiness assessment, configuration, deployment, or any Microsoft 365 Copilot security consultation.
