Unmasking Hidden Identity Attack Paths: How To Use GQL In Microsoft Sentinel To Secure Azure Key Vaults Before Attackers Strike + Video

Introduction:

Identity-driven breaches often exploit indirect permission chains that traditional monitoring misses. Microsoft Sentinel’s new Identity Attack Graph (Preview) uses Graph Query Language (GQL) to model relationships between Entra ID users, groups, and Azure resources like Key Vaults, exposing exactly how an attacker could pivot from a low-privilege account to your most sensitive secrets. This shifts security operations from reactive alerting to preventive identity hardening, enabling teams to visualize and break toxic combinations of effective permissions before they are weaponized.

Learning Objectives:

Deploy and configure the Identity Attack Graph preview in Microsoft Defender XDR / Sentinel
Write GQL queries to enumerate attack paths from Entra ID identities to Azure Key Vaults
Apply preventive controls (JIT, Conditional Access, RBAC pruning) to eliminate exposed risk chains

You Should Know:

Enabling Identity Attack Graph in Microsoft Sentinel (Preview)
The Identity Attack Graph is part of Microsoft Defender XDR’s identity threat analytics. To enable it, your environment needs Microsoft Entra ID P2 licenses, Azure Key Vault logging enabled, and the Microsoft Sentinel identity solution installed. Follow these steps:

– In Azure Portal, navigate to Microsoft Defender XDR → Settings → Identity.
– Toggle “Identity Attack Graph (Preview)” to On.
– Ensure your Log Analytics workspace (connected to Sentinel) has the IdentityLogonEvents, AADManagedIdentityLogs, and `KeyVaultAuditEvent` tables.
– Assign at least “Security Reader” and “Sentinel Contributor” roles to analysts.
– Verify connectivity using Azure CLI on Linux/macOS:

az login --tenant YOUR_TENANT_ID
az rest --method get --url "https://api.security.microsoft.com/api/identity/attackgraph/config"

– Windows (PowerShell):

Connect-AzAccount -Tenant YOUR_TENANT_ID
Invoke-RestMethod -Uri "https://api.security.microsoft.com/api/identity/attackgraph/config" -Headers @{Authorization = "Bearer $((Get-AzAccessToken).Token)"}

If the response shows "isEnabled": true, the graph is active. Allow up to 24 hours for initial data ingestion.

Writing Your First GQL Query to Map Entra ID to Key Vault Paths
GQL (Graph Query Language) in Microsoft Sentinel uses a pattern similar to KQL but optimized for graph traversal. Below is a query that lists all attack paths from any user to a Key Vault containing the substring “prod-secrets”:
```
MATCH (user:Identity {type:"User"})
-[r:HasRoleAssignment | CanAuthenticateTo | HasMember1..5]-> 
(target:Resource {type:"AzureKeyVault", name:~/.prod-secrets./})
RETURN user.userPrincipalName, target.name, 
reduce(path = [], n IN nodes(path) | path + n.name) AS exposurePath,
length(r) AS hopCount
ORDER BY hopCount ASC
```
Run this inside Microsoft Sentinel’s Logs page by switching query language to “Graph Query” (Preview). The result reveals every user that can eventually reach a sensitive key vault, including indirect paths via service principals, managed identities, or nested groups. For a quick Linux/macOS test using Azure API:
```
az rest --method post --url "https://api.security.microsoft.com/api/identity/attackgraph/query" --body '{"query":"MATCH (u:Identity)-[1..3]->(v:Resource) RETURN u.name, v.name"}' --headers "Content-Type=application/json"
```
This helps you verify the graph is populated without opening the portal.

Identifying Toxic Permission Chains with Advanced GQL Filters
Toxic permission chains often include “orphaned” managed identities or over-privileged service principals. The following GQL finds all paths where a user can write secrets to a Key Vault via exactly two intermediate identities:

MATCH (user:Identity {riskLevel:"high"})
-[bash]-> (mid:Identity)
-[r2 {type:"KeyVaultSecretsUser"}]-> (kv:Resource {type:"AzureKeyVault"})
WHERE NOT (user)-[:KeyVaultSecretsUser]->(kv)
RETURN user.userPrincipalName, mid.displayName, kv.name, r1.type, r2.type

To remediate, export the list of over-privileged role assignments via Azure PowerShell:

$users = @("[email protected]","[email protected]")
foreach ($u in $users) {
Get-AzRoleAssignment -SignInName $u | Where-Object {$_.Scope -like "/subscriptions//resourceGroups//providers/Microsoft.KeyVault/"}
}

Then remove unnecessary assignments with Remove-AzRoleAssignment. For Linux, use:

az role assignment list --assignee [email protected] --query "[?contains(scope, 'Microsoft.KeyVault')]" --output table
az role assignment delete --assignee [email protected] --role "Key Vault Secrets User" --scope /subscriptions/XXX/resourceGroups/YYY/providers/Microsoft.KeyVault/vaults/ZZZ

Reducing Blast Radius with Just-in-Time (JIT) Access and Conditional Access
After visualizing attack paths, harden identities using Azure AD Conditional Access and JIT for Key Vaults. Step-by-step:

– On Windows (Azure Portal) → Entra ID → Security → Conditional Access → New policy.
– Target all users with high-risk exposure paths (from GQL results). Require “Multi-factor authentication” for any access to Azure Key Vaults.
– Enforce “session lifetime” of 1 hour for Key Vault management plane.
– For JIT, use Azure CLI to elevate access only when needed:

 Request temporary "Key Vault Secrets User" role for 15 minutes
az role assignment create --assignee [email protected] --role "Key Vault Secrets User" --scope /subscriptions/XXX/resourceGroups/YYY/providers/Microsoft.KeyVault/vaults/ZZZ --start-time "$(date -u +'%Y-%m-%dT%H:%M:%SZ')" --end-time "$(date -u -d '+15 minutes' +'%Y-%m-%dT%H:%M:%SZ')"

– Monitor JIT requests via Sentinel using KQL:

AzureActivity
| where OperationNameValue == "MICROSOFT.AUTHORIZATION/ROLEASSIGNMENTS/WRITE"
| where Properties["condition"] contains "JustInTime"
| project TimeGenerated, Caller, ResourceGroup

Combine JIT with an automated playbook that revokes standing access for any user appearing in a toxic GQL path.

Automating Attack Path Detection with Sentinel Analytics Rules
You don’t need to run GQL manually every day. Create a custom analytics rule in Sentinel that runs the attack graph query on an hourly basis and generates alerts when a new path to a crown jewel Key Vault appears. Use the following logic (KQL + GQL wrapper):

– In Sentinel → Analytics → Create → Scheduled query rule.
– Set query to a hybrid that invokes the GQL endpoint via a Logic App (or use Direct Graph Query if natively supported). Simpler: Use the Defender XDR Advanced Hunting API with PowerShell:

$body = @{
Query = "MATCH (user:Identity)-[:HasRoleAssignment1..3]->(kv:Resource {type:'AzureKeyVault', name:'prod-secrets'}) RETURN user.userPrincipalName, kv.name"
} | ConvertTo-Json
$result = Invoke-RestMethod -Method Post -Uri "https://api.security.microsoft.com/api/identity/attackgraph/query" -Body $body -Headers $headers
if ($result.count -gt 0) {
Write-Output "New attack path detected: $($result | Out-String)"
 Trigger Sentinel incident via API
}

– Schedule the PowerShell script as an Azure Automation runbook or use a Time-Trigger in a Logic App. When a path is found, create a high-severity incident with the hop chain as evidence.

Hardening Key Vaults Against Identity-Based Attacks (Mitigation Commands)
Attack paths often end at Key Vaults that have too permissive network or RBAC settings. Run these hardening commands after your GQL analysis:

– Disable public network access (Azure CLI):

az keyvault update --name prod-secrets --default-action Deny

– Add IP firewall rules to allow only your management subnet:

az keyvault network-rule add --name prod-secrets --ip-address "10.0.0.0/24"

– Enable purge protection and soft-delete (already default for new vaults):

az keyvault update --name prod-secrets --enable-purge-protection true

– Export all RBAC assignments for the Key Vault and remove any that aren’t JIT-approved:

az role assignment list --scope /subscriptions/XXX/resourceGroups/YYY/providers/Microsoft.KeyVault/vaults/prod-secrets --query "[?roleDefinitionName=='Key Vault Secrets User' && principalType=='User']" --output table
 Then delete each

On Windows, use the `Az.KeyVault` PowerShell module:

Set-AzKeyVaultAccessPolicy -VaultName prod-secrets -ResourceGroupName YYY -PermissionsToSecrets @() -UserPrincipalName [email protected]  removes all secret permissions

Integrating Identity Attack Graph into Daily SecOps Workflows
To make this actionable, build a Sentinel Workbook that visualizes GQL output. Steps:

– Create a new workbook → Add query → select “Graph Query” as data source.
– Paste the GQL query from Section 2. Use parameters to filter by user risk level or Key Vault name.
– Add a “path visualization” tile (use the built-in Graph renderer). This shows arrows from identities to resources with hop counts.
– For each toxic path, embed a “Remediate” button that calls an Azure Automation runbook to revoke the specific role assignment.
– Share the workbook with your SecOps team as a custom dashboard. Additionally, export the top 5 riskiest paths daily to a Storage Account using Azure CLI:

az rest --method post --url "https://api.security.microsoft.com/api/identity/attackgraph/query" --body '{"query":"MATCH (u)-[1..2]->(v) RETURN u.name, v.name LIMIT 5"}' --output json > attack_paths_$(date +%F).json
az storage blob upload --account-name secopsdata --container metrics --file attack_paths_.json --name paths/path_$(date +%F).json

What Undercode Say:

Key Takeaway 1 – Identity attack paths are not just theoretical; GQL enables concrete, queryable maps from any user to any resource, turning abstract risk into a visible graph.
Key Takeaway 2 – Proactive hardening (JIT, Conditional Access, RBAC pruning) becomes data-driven when you automate GQL scans as Sentinel alerts, cutting incident response time from hours to seconds.
Key Takeaway 3 – Combining GQL with native cloud CLI (Azure CLI, PowerShell) allows both offensive (path discovery) and defensive (remediation) workflows in the same pipeline – a must for modern SecOps.

Analysis: The Identity Attack Graph preview shifts defense from “what happened” to “what could happen”. By modeling effective permissions instead of static role assignments, it reveals misconfigurations like a user with no direct Key Vault role but membership in a group that owns a service principal that has secrets write access – a chain almost impossible to spot with RBAC reports alone. Microsoft’s investment in GQL (a SQL-like language for graphs) lowers the barrier for incident responders already familiar with KQL. However, adoption requires rethinking IAM monitoring: instead of checking each identity in isolation, SecOps must now think in graphs. The sample commands provided (Azure CLI, PowerShell, KQL) let teams integrate this into CI/CD for infrastructure-as-code validation – e.g., rejecting Terraform plans that introduce new hazardous paths before deployment.

Prediction:

Within 12 months, identity attack graphs will become mandatory for compliance frameworks like PCI DSS v5 and ISO 27001:2026. We’ll see automated “attack path as code” tools that reject role assignments if they create a new exploitable chain to a crown jewel. Meanwhile, attackers will shift to path obfuscation – abusing temporary access tokens and just-in-time approvals that are not yet recorded in attack graph timelines. Defenders must extend GQL queries to include ephemeral credentials and OAuth app grants, pushing Microsoft to incorporate Entra ID’s token issuance logs into the graph. The real race will be graph update latency: Microsoft claims near-real-time, but early previews show 15–30 minute delays – enough for a skilled adversary to exfiltrate keys. Expect third-party SIEMs (Splunk, Chronicle) to add their own graph layers, forcing cross-platform GQL standardization under an OASIS working group.

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