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Introduction:
Microsoft’s May 2026 Defender Portal update marks a paradigm shift toward true unified security operations by elevating Azure Sentinel to a top-level sidebar section, embedding Defender for Cloud, and — most critically — introducing an AI agent inventory under Assets. This gives defenders visibility into previously invisible attack surfaces, such as Copilot Studio agents, while adding a built‑in API explorer and native case management across Sentinel and XDR workloads.
Learning Objectives:
- Navigate the new Defender Portal layout and integrate Sentinel + Defender for Cloud workflows.
- Use the built‑in API explorer to test and automate Defender REST API calls for incident response.
- Identify, monitor, and harden AI agent configurations (Copilot Studio, custom bots) against privilege escalation and data leakage.
You Should Know:
1. Mapping the New Single‑Pane‑of‑Glass Layout
The May 2026 update restructures the left navigation bar. Sentinel is now a top‑level section (no longer buried under “Advanced hunting”), and Defender for Cloud appears under “Cloud Security.” The Assets section contains the new AI agent inventory – listing every Copilot Studio agent, custom bot, and AI plugin with its permissions, data connections, and activity logs.
Step‑by‑step guide to explore the layout:
1. Log into the Microsoft Defender Portal (security.microsoft.com).
- In the left sidebar, click Sentinel – you’ll see incidents, workbooks, and hunting queries immediately.
- Click Defender for Cloud to review security posture, recommendations, and cloud workload protections.
- Navigate to Assets > AI agents to enumerate all AI agents in your tenant.
– For each agent, review: exposed APIs, authentication method, data sources (SharePoint, SQL, etc.), and recent interactions.
5. Use the Case management pane (accessible from both Sentinel and Incidents) to link alerts from XDR and Sentinel into a single case.
Tip: On Linux/macOS (using
curl) or Windows PowerShell, you can retrieve the agent list via Microsoft Graph API (requires `CloudAppDeviceManagement.Read.All` scope):
> “`bash
> Linux/macOS
curl -X GET “https://graph.microsoft.com/v1.0/security/collaboration/aiAgents” \
> -H “Authorization: Bearer $ACCESS_TOKEN”
> “`
> “`bash
> Windows PowerShell
> $token = “your_access_token”
> $headers = @{Authorization = “Bearer $token”}
Invoke-RestMethod -Uri “https://graph.microsoft.com/v1.0/security/collaboration/aiAgents” -Headers $headers
> “`
- Using the Built‑in API Explorer for Defender REST Calls
The new native API explorer (under System > API explorer) allows you to test all Defender REST endpoints without leaving the portal. You can generate authentication samples, run queries, and export code snippets for Python, PowerShell, or curl.
Step‑by‑step API testing and automation:
- Inside Defender Portal, go to System > API explorer.
- Select an operation, e.g., `GET /api/alerts` or
POST /api/advancedHunting/run. - Click Try it – the portal automatically injects your session’s bearer token.
- Examine the response JSON. Click Export to generate a ready‑to‑use script.
5. For automation, copy the PowerShell snippet:
$body = @{ Query = "AlertEvents | take 10" } | ConvertTo-Json
$response = Invoke-RestMethod -Uri "https://api.security.microsoft.com/api/advancedHunting/run" `
-Method Post -Headers @{Authorization = "Bearer $token"} -Body $body -ContentType "application/json"
$response.Results
(On Linux, use `curl -X POST https://api.security.microsoft.com/api/advancedHunting/run -H “Authorization: Bearer $token” -H “Content-Type: application/json” -d ‘{“Query”: “AlertEvents | take 10”}’`)
- Securing AI Agent Inventory – Attack Surface Analysis
The AI agent inventory reveals that each Copilot Studio agent has its own API endpoint, knowledge base connections, and potentially over‑privileged service accounts. Attackers who compromise an agent can pivot to SharePoint, Teams, or databases. You must now treat AI agents as identity‑driven workloads.
Step‑by‑step hardening for AI agents:
- In Defender Portal, go to Assets > AI agents.
- Sort by “Last activity” – stale agents should be disabled.
- Click any agent, then review Permissions. Remove unnecessary Microsoft Graph scopes (e.g., `Mail.Read` if not required).
- Go to Data sources – limit connections to specific SharePoint sites or SQL tables using row‑level security.
- Enable audit logging (under agent’s settings) to send all agent‑user interactions to Sentinel.
6. Create a custom detection rule in Sentinel:
`AIAgentInteraction | where ActionType contains “DataExport” and ActivityTime > now(-1h)`
Windows / Linux command to check agent endpoint accessibility (penetration test perspective):
Linux – test for open AI agent endpoint nmap -p 443 --script http-headers <ai-agent-hostname> curl -k https://<ai-agent-endpoint>/api/conversations -H "Authorization: Bearer $test_token"
Windows – use Test-NetConnection to verify connectivity Test-NetConnection <ai-agent-hostname> -Port 443 Invoke-WebRequest -Uri "https://<ai-agent-endpoint>/api/health" -UseBasicParsing
- Native Case Management Across Sentinel + XDR Workloads
Previously, incidents from Microsoft 365 Defender (XDR) and Sentinel were siloed. The update introduces a unified case management interface that combines alerts from both, plus allows manual addition of indicators, notes, and evidence from AI agents.
Step‑by‑step cross‑workload investigation:
- From the Incidents pane, select a Sentinel incident that involves an AI agent alert.
- Click Link to case – then either create a new case or add to an existing XDR case.
- Inside the case, use the Evidence tab to pull in the AI agent’s conversation logs (available via Defender for Cloud Apps).
- Run a unified KQL query from the case view to correlate Sentinel and XDR data:
union SentinelEvents, M365DAlertEvents | where Timestamp > ago(24h) | where AIDataSensitivity contains "high" | project Timestamp, AlertName, AgentName, AccountUpn
- Escalate the case to Microsoft 365 Defender for automated remediation (e.g., isolate the AI agent’s host VM).
5. Cloud Hardening with Embedded Defender for Cloud
Defender for Cloud is now fully embedded, providing CSPM (Cloud Security Posture Management) and workload protections directly inside the Defender Portal. Use it to enforce security policies on AI‑hosting environments (Azure ML, Kubernetes with GPU nodes).
Step‑by‑step cloud hardening for AI workloads:
1. Navigate to Defender for Cloud > Recommendations.
- Filter by “AI workloads” – look for “AI agent should use managed identity instead of service principal.”
- Click the recommendation → Fix to auto‑generate a Terraform script or ARM template.
- For Kubernetes clusters running AI models, enable Defender’s K8s admission control:
– Go to Defender for Cloud > Environment settings > select your AKS cluster.
– Turn on “Audit AI pod configurations” – this prevents privilege escalation in containers hosting model inference.
5. Review Security explorer > AI attack paths – a new feature that maps potential lateral movement from a compromised AI agent to storage accounts.
Linux command to inspect Kubernetes AI pod security (requires kubectl and jq):
kubectl get pods -l app=copilot-agent -o json | jq '.items[].spec.containers[].securityContext' Look for privileged: true or allowPrivilegeEscalation: true
Windows PowerShell (using kubectl via WSL or native):
kubectl get pods --selector=app=ai-agent -o=jsonpath='{.items[].spec.containers[].securityContext}'
What Undercode Say:
- Key Takeaway 1: AI agents are no longer hidden “black boxes” – Microsoft now treats them as first‑class assets, with inventory, permissions, and logs. This forces security teams to embed AI agents into identity and access management (IAM) workflows.
- Key Takeaway 2: The built‑in API explorer and native case management bridge the gap between SOC analysts (using Sentinel) and XDR investigators. The result is a measurable reduction in mean time to respond (MTTR) for incidents involving AI or cross‑domain threats.
Analysis:
The May 2026 update reflects a broader industry trend: security platforms must absorb AI‑specific telemetry and provide actionable controls. By exposing Copilot Studio agents as “Assets,” Microsoft acknowledges that AI agents carry similar risks to user accounts – they can be abused to exfiltrate data, execute lateral movement, or conduct prompt injection attacks. Security teams should immediately audit their AI agent inventory, restrict permissions following least privilege, and integrate agent logs into Sentinel using the new KQL schema (AIAgentInteraction). The removal of friction between Sentinel and Defender XDR is a game‑changer for hybrid SOCs, but the real innovation is the API explorer, which enables custom playbooks and real‑time hunting at scale.
Prediction:
By Q4 2026, AI agent compromises will become a primary vector for data breaches in enterprises using Microsoft 365 Copilot. Expect Microsoft to release “AI Agent Threat Protection” as a premium add‑on, incorporating prompt injection detection, behavioral baselining, and automated quarantine of suspicious agents. Defenders who master the new Asset inventory and API explorer today will be ahead of the curve – while laggards will face AI‑driven supply chain attacks that bypass traditional EDR. Open‑source tools (e.g., custom Sentinel hunting queries for AI agent anomalies) will emerge on GitHub and platforms like azurehacking.com, further democratizing AI security. The only way to stay safe is to treat every AI agent as a privileged user with its own session context and data plane.
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Reported By: Rogierdijkman Microsoft – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
