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To determine whether an AI agent or Copilot accessed Microsoft 365 data without authorization, investigate in layers: start with Microsoft Purview Audit to identify the user, agent, app, time, operation, and accessed resources; use DSPM for AI to add prompt, response, sensitivity-label, DLP, eDiscovery, and retention context; then use Microsoft Defender to detect runtime behavior such as prompt injection, jailbreaks, credential leakage, and suspicious tool use. Microsoft Sentinel correlates those records across users, agents, alerts, tools, URLs, and resources. After you establish scope, contain the agent, remove stale connections or secrets, correct permissions and ownership, preserve evidence, and apply DLP and unmanaged-app controls. This sequence distinguishes an unusual but authorized interaction from actual unauthorized access and gives responders a defensible path from discovery to prevention.
What counts as unauthorized AI-agent activity in Microsoft 365?
Unauthorized activity is any agent-driven access, action, or disclosure that falls outside the approved user, purpose, data scope, instructions, or owner accountability. It can involve a compromised user account, an over-permissioned custom agent, a forgotten connection, a malicious prompt, an indirect prompt injection in a document, or an unsanctioned AI application receiving Microsoft 365 content.
Do not treat every unfamiliar Copilot event as an incident. An approved agent may legitimately read SharePoint files, send a message, create a record, or call an external service. The investigation must establish four facts:
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- Identity: which person, service principal, agent, or application initiated the activity.
- Authority: what permissions, connections, instructions, and approval covered the action.
- Data and action: which files, sites, messages, prompts, responses, recipients, URLs, or tools were involved.
- Intent and impact: whether the behavior was expected, suspicious, blocked, or capable of exposing data.
Agents can act through delegated user permissions, application permissions, connectors, plugins, or stored credentials. That is why a normal-looking user sign-in does not prove that every subsequent AI action was authorized.
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Where are Copilot and AI-agent audit logs?
Microsoft Purview Audit is the starting point for historical scope. Microsoft states that Copilot and AI audit records contain the user, time, location or context, and references to files, sites, or other resources involved in an interaction. The available detail depends on the workload, licensing, enabled logging, and retention configuration.
Purview Audit for identity and activity scope
In the Microsoft Purview portal, open Audit and filter for Copilot and AI-related operations. Set the narrowest practical time range first, then expand it around the earliest and latest suspicious events. Record the user, workload, application identity, agent name or identifier, operation, timestamp, client or location context, and every referenced resource.
Export the results before changing the environment. Preserve the export with its time zone, search filters, tenant identifier, operator, and export timestamp. A screenshot is useful for a case file, but it is not a substitute for the original export and its metadata.
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DSPM for AI Activity Explorer for content context
Use DSPM for AI Activity Explorer to determine what the interaction contained and what policies applied. Depending on the workload and enabled capabilities, records can include prompts, responses, accessed-file references, sensitivity labels, DLP matches, and policy or compliance context.
This is the layer that answers questions an ordinary audit row cannot: Did a prompt include a confidential contract? Did the response reproduce protected content? Was a sensitivity label present? Did a DLP policy match, and was the action blocked or merely audited? Use Purview audit exports alongside Activity Explorer results because neither view necessarily contains every field needed for a complete timeline.
Retention and availability limits
Microsoft’s current documentation says non-Microsoft AI interaction audit logs require pay-as-you-go billing when enabled and are retained for 180 days. Treat 180 days as a product-retention policy, not as a guarantee that every older event can be recovered. Copilot and Microsoft workload records can have different availability and retention behavior, so verify the exact workload and tenant configuration before concluding that no activity occurred.
How do I investigate whether an AI agent used Microsoft 365 data without permission?
Follow a repeatable sequence: scope the event, establish data context, examine runtime behavior, correlate evidence, preserve the case, and only then contain or remediate. Changing permissions before exporting evidence can destroy the context needed to determine what happened.
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1. Scope the event in Purview Audit
- Define the suspected start time, end time, users, workloads, and agent or application names. Include a buffer before and after the reported event.
- Filter for Copilot and AI operations in Audit. Search by user and agent or application identity separately; an agent may appear under a service identity rather than the person who configured it.
- Capture each event’s timestamp, time zone, operation, workload, user, app identity, agent identifier, location or client context, and referenced files, sites, messages, or other resources.
- Group events into a timeline. Look for a sudden increase in volume, access to an unfamiliar site, a new workload, repeated failures followed by success, or activity outside the agent’s stated purpose.
Audit evidence establishes what was recorded, not automatically whether the action was malicious. Compare the identity and operation with the agent’s approved owner, documented use case, and permission grant.
2. Establish the data and policy context in DSPM for AI
- Open DSPM for AI Activity Explorer for the same time range and identities.
- Match prompts and responses to the audit timeline where those fields are available.
- Review accessed-resource references, sensitivity labels, DLP matches, communication-compliance signals, eDiscovery holds, retention policies, and insider-risk indicators that apply to the interaction.
- Classify the result: metadata-only access, exposure of sensitive content, attempted disclosure, successful disclosure, or an action blocked by policy.
A prompt containing a file name is not proof that the file’s contents were returned. Conversely, a response may reveal sensitive information even when the audit record lists only the conversation. Content-level review is required when the potential impact is high.
3. Hunt for runtime behavior in Defender
Microsoft Defender’s Agent 365 capabilities add runtime telemetry for managed agents. Microsoft says Defender continuously monitors Agent 365-managed agents and detects suspicious or malicious behavior. Document the tenant’s licensing and preview status because some agent protections are preview features and are scoped to agents managed by Agent 365.
Review detections and hunting data for:
- Indirect prompt injection from a document, web page, message, or other retrieved content.
- Jailbreak attempts intended to bypass the agent’s instructions or policy.
- Credential, token, or secret leakage in prompts, tool arguments, logs, or responses.
- Reconnaissance, unusual resource discovery, or access to data outside the agent’s normal pattern.
- Malicious propagation, evasion, repeated failed tool calls, or suspicious user and IP combinations.
- Unexpected tool use, URL access, endpoint changes, recipient changes, or high-volume execution.
4. Correlate the evidence in Advanced Hunting
Use Microsoft Defender Advanced Hunting to join the agent and alert records rather than reading each alert in isolation. Relevant tables named in Microsoft’s guidance include AlertInfo, AlertEvidence, CloudAppEvents, AgentsInfo, BehaviorInfo, and BehaviorEntities.
| Record set | What to correlate | Investigation question |
|---|---|---|
| AgentsInfo | Agent identity, configuration, owner, and managed status | Which agent executed the activity, and who is accountable for it? |
| CloudAppEvents | Cloud application, user, action, resource, and session context | Which Microsoft 365 or connected application received or returned data? |
| AlertInfo and AlertEvidence | Alert title, severity, timestamps, entities, and evidence | What detection fired, and which objects support it? |
| BehaviorInfo and BehaviorEntities | Behavioral detections and related users, tools, URLs, or resources | Does the event form part of a larger attack sequence? |
Pivot on stable identifiers whenever possible: agent ID, alert ID, user or service identity, URL, resource ID, and event time. Expect ingestion delays and different time fields across tables; normalize time zones before drawing conclusions.
5. Correlate at tenant scale with Sentinel
Microsoft Sentinel is useful when the event spans many users, agents, workloads, or days. Microsoft’s AI Investigation Playbook provides configuration guidance, KQL query patterns, detection logic, analytic rules, and evidence-export approaches across Purview, Defender, and Azure AI services.
Build a case timeline that links:
- Purview audit operations and accessed resources.
- DSPM prompts, responses, labels, DLP outcomes, and compliance signals.
- Defender alerts, agent configuration, tool calls, URLs, and behavioral entities.
- Identity events, sign-in context, IP addresses, endpoint activity, and service changes.
Create analytic rules only after confirming the fields and retention available in your tenant. A rule that assumes prompt or response fields exist for every workload will produce misleading gaps.
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6. Preserve evidence before containment
Export Purview searches, Activity Explorer results, Defender incidents and advanced-hunting results, Sentinel incidents, agent configuration, permission assignments, connector details, and relevant policy versions. Hash exported files if your incident process requires chain-of-custody controls. Record who collected each item, when, from which portal, with which filters, and whether the data was redacted.
Preserve the agent’s instructions, tool definitions, action schemas, connection references, secrets’ metadata, owner information, and change history. Do not copy secret values into the case record; rotate them through the approved secrets process instead.
Can Defender detect prompt injection in an AI agent?
Yes, Defender’s Agent 365 detections are designed to identify runtime threats including prompt injection and jailbreak behavior, but coverage depends on the agent being managed and monitored by Agent 365 and on the relevant capability being available in your tenant. Detection is not proof that every injection will be caught, so content review and preventive controls remain necessary.
What prompt-injection evidence looks like
Investigate a retrieved document, message, web page, or tool result that contains instructions unrelated to its business purpose, asks the agent to ignore system instructions, requests secrets, changes recipients or endpoints, or directs the agent to exfiltrate content. Compare the source content with the agent’s declared task and the tool calls that followed.
Distinguish a blocked attempt from a successful action. A Defender alert may show the attempted behavior while Purview and CloudAppEvents establish whether data was actually read, changed, or transmitted.
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Why a clean alert page is not a clean bill of health
Some capabilities are preview features, telemetry can be incomplete, and non-Microsoft interactions may require separate billing and logging configuration. A lack of a Defender alert should lead you to verify audit coverage, agent management scope, retention, and connector telemetry—not to assume that no unauthorized access occurred.
How do I disable or contain a rogue Copilot agent?
Contain the smallest set of identities and capabilities that stops further exposure while preserving evidence. If active exfiltration is suspected, disable the agent or revoke its execution path immediately, then continue the investigation with exported records.
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Immediate containment checklist
- Disable or restrict the suspect agent in the control plane where it is registered.
- Revoke or suspend the user, service identity, connector, or application permission being abused.
- Remove unused actions, dormant agents, stale connections, and embedded credentials.
- Rotate exposed secrets and tokens; do not merely rename the connection.
- Block suspicious destinations, recipients, URLs, or external applications through the applicable security control.
- Preserve the agent’s configuration and logs before deleting it, unless deletion is required to stop active harm.
- Notify the data owner, incident commander, privacy or compliance team, and the agent owner according to your escalation plan.
When to disable the user instead of only the agent
Disable or restrict the user account when sign-in evidence, token theft, impossible travel, unfamiliar IP activity, or multiple unrelated applications indicate account compromise. If only one agent has excessive permissions and the user’s other activity is normal, isolate the agent and connection first, then validate the user session and tokens.
Verify that containment worked
- Attempt no production action with the suspect agent; use a controlled test account if validation is required.
- Confirm that new tool calls, cloud-app events, Purview operations, and Defender detections stop or show an expected blocked result.
- Check for parallel copies, alternate connectors, scheduled flows, or another agent using the same credentials.
- Search for delayed actions and queued messages that were created before disablement.
How do I remediate an over-permissioned or abandoned agent?
Remediation is more than changing a password. An agent remains risky when its owner is unknown, its actions are broader than its purpose, or it can dynamically choose recipients, endpoints, or sensitive operations.
Re-establish ownership and lifecycle accountability
- Assign a named business owner and a technical owner.
- Document the use case, approved data classes, permitted workloads, tools, destinations, and escalation contact.
- Set a review date and an inactivity or ownership-transfer process.
- Retire orphaned agents after preserving evidence and confirming that no business process depends on them.
Orphaned agents are a specific governance risk: they can continue running or accessing data without an accountable person to notice abnormal behavior or approve changes.
Reduce permissions and decision freedom
- Use the narrowest delegated or application permissions that satisfy the task.
- Separate read, write, send, delete, and administrative actions instead of granting a broad bundle.
- Require approval for external recipients, new endpoints, sensitive records, destructive operations, and high-impact changes.
- Prefer authenticated, official integrations over ad hoc endpoints, and require HTTPS for network connections.
- Keep secrets out of prompts, instructions, source documents, and logs; store them in an approved secret-management system.
Harden instructions and retrieved content
Tell the agent to treat retrieved documents, messages, and web content as data rather than authority. Define which sources are trusted, what the agent must refuse, and when it must ask for human approval. Limit dynamic changes to recipients, URLs, query scopes, and tool parameters.
Apply data-governance controls
Use Purview DLP to detect and block inappropriate movement of sensitive information. Communication compliance, eDiscovery, retention, and insider-risk controls can provide additional review and preservation paths where the organization’s policies and legal requirements call for them. Configure controls for the actual workloads and identities involved; a policy that covers email but not a connected application leaves a gap.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do I control unmanaged AI applications that receive Microsoft 365 data?
Microsoft Defender for Cloud Apps can discover, monitor, and block specific AI applications, while Defender for Endpoint can prevent unsanctioned applications on onboarded devices. DSPM policies and Microsoft Edge controls can also surface AI activity and protect prompts, subject to tenant configuration and licensing.
Discover before blocking
- Inventory AI applications seen in cloud, endpoint, browser, proxy, and identity telemetry.
- Classify each application by business owner, data handled, authentication method, geographic or contractual requirements, and whether it supports enterprise controls.
- Identify users sending Microsoft 365 content, browser uploads, copied text, or automated connector traffic to each application.
- Move applications into approved, monitored, restricted, or blocked categories.
Blocking without discovery can drive users to unsanctioned alternatives and remove useful evidence. Use a staged policy where feasible: monitor, warn, require justification or approval, then block when the risk and business impact are understood.
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Close the common exfiltration paths
- Apply DLP to copied or uploaded sensitive content.
- Restrict unmanaged browser sessions and downloads where policy requires it.
- Block unsanctioned applications on managed endpoints.
- Review OAuth grants, browser extensions, connectors, and service accounts that can move Microsoft 365 data outside approved applications.
Which Microsoft 365 control should I use first?
No single control answers every investigative question. Choose based on the depth, speed, workload scope, and governance outcome you need.
| Control | Visibility depth | Response speed | Primary scope | Best use |
|---|---|---|---|---|
| Purview Audit | Identity, time, operation, workload, context, and referenced resources | Historical review; availability depends on logging and retention | Copilot and Microsoft 365 AI operations | Establish who did what and when |
| DSPM for AI Activity Explorer | Prompts, responses, accessed resources, labels, DLP and compliance context where available | Investigation and policy review | AI interactions covered by the tenant’s configuration | Determine what data may have been exposed |
| Defender Agent 365 | Agent inventory, runtime behavior, tools, execution patterns, and detections | Near-real-time alerts and incidents | Agent 365-managed agents; some capabilities are preview | Detect injection, jailbreaks, leakage, and suspicious execution |
| Defender Advanced Hunting | Joined alerts, agents, users, tools, URLs, resources, and behaviors | Analyst-driven hunting | Data available in the listed Defender tables | Find related activity and attack chains |
| Microsoft Sentinel | Cross-service correlation, analytics, incidents, and long-term case evidence | Automated rules plus analyst investigation | Connected Microsoft 365, Defender, Purview, and Azure AI sources | Scale detection and response across the tenant |
| Defender for Cloud Apps and Endpoint | Discovery and enforcement for cloud and endpoint application use | Policy-based monitoring or blocking | Unmanaged or unsanctioned AI applications | Prevent data movement to unapproved services |
What should a Microsoft 365 AI-agent detection program monitor?
Turn the investigation sequence into recurring detections and reviews rather than waiting for a user report.
High-value detection conditions
- An agent accesses a sensitivity-labeled resource outside its documented data scope.
- A new owner, connector, action, endpoint, or permission appears without an approved change.
- Tool calls or resource discovery spike above the agent’s normal baseline.
- A prompt or retrieved document contains injection or jailbreak language followed by a privileged action.
- Credentials, tokens, or secrets appear in prompts, responses, tool arguments, or external requests.
- An orphaned or inactive agent resumes execution.
- The same identity operates from an unusual IP, location, endpoint, or application immediately before AI activity.
- An AI application outside the approved catalog receives sensitive Microsoft 365 content.
Review cadence
Review agent ownership, permissions, connectors, actions, and retention settings on a scheduled basis and after every material change. Use incident-driven retrospectives to tune baselines: an alert should explain why the behavior differs from the agent’s approved purpose, not simply report that the agent ran.
What are the main investigation pitfalls?
- Searching only by a person’s name: service identities and application identities may perform the action.
- Relying on one portal: Purview shows audit context, DSPM adds content and policy context, and Defender adds runtime behavior.
- Assuming an alert proves data exposure: confirm the accessed resource and transmission outcome.
- Assuming no alert proves safety: verify Agent 365 management scope, preview status, ingestion, and retention.
- Deleting the agent immediately: preserve configuration, ownership, permissions, and evidence first unless active harm requires instant removal.
- Leaving the connection in place: rotating a secret without removing stale permissions or alternate connectors may leave the path open.
- Ignoring queued or delayed actions: disablement may not cancel work already submitted to another service.
- Treating retention as universal: the documented 180-day period applies to enabled non-Microsoft AI interaction audit logs, not every Microsoft 365 record.
What is the defensible end state after an incident?
Close the incident only when you can state the affected identities, time range, resources, prompts or responses available for review, policy outcomes, external destinations, and containment actions. Document what could not be established because telemetry was unavailable or expired. Then record the permanent changes: ownership assignment, permission reduction, connector removal, secret rotation, DLP or blocking policy, detection rule, and review date.
Microsoft describes the overall model succinctly: “AI interactions generate telemetry across Microsoft Purview, Defender, and Sentinel.” Treat those services as complementary layers. Audit establishes the event, DSPM explains the data and policy context, Defender identifies runtime threats, and Sentinel makes the evidence searchable and actionable across the organization.
Frequently Asked Questions
How long should I keep Microsoft 365 AI investigation records?
Keep exports for the period required by your incident-response, legal, and records-management policies, and preserve them under the applicable eDiscovery or retention hold when necessary. The documented 180-day period for enabled non-Microsoft AI interaction audit logs is an availability limit, not a recommendation for your organization’s case-retention schedule.
What if Purview shows an AI interaction but no prompt or response?
Treat the event as a metadata lead, not as proof that no content was exposed. Correlate the referenced resource with Defender tool telemetry, CloudAppEvents, endpoint or network records, and any downstream application logs, then review the source content and destination permissions.
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No. Microsoft’s documentation scopes the stated continuous monitoring to Agent 365-managed agents, and some capabilities are preview features. Verify that the agent is enrolled, the relevant workload is supported, and the tenant has the required licensing and telemetry before relying on a detection gap.
Should I block all generative-AI applications after an incident?
Usually, a risk-tiered approach is more durable: discover use, approve applications with suitable controls, monitor restricted services, and block destinations that cannot meet data-protection requirements. Pair blocking with DLP and endpoint or browser enforcement so users cannot simply move the same data through another path.
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