Cloud Posture + Attack Surface Signals in Microsoft Sentinel (Prisma Cloud + Cortex Xpanse)

Microsoft expanded Microsoft Sentinel’s connector ecosystem with Palo Alto integrations that pull cloud posture, cloud workload runtime, and external attack surface signals into the SIEM, so your SOC can correlate “what’s exposed” and “what’s misconfigured” with “what’s actively being attacked.” Specifically, the Ignite connectors list includes Palo Alto: Cortex Xpanse CCF and Palo Alto: Prisma Cloud CWPP.

Why these connectors matter for Sentinel detection engineering

Traditional SIEM pipelines ingest “events.” But exposure and posture are just as important as the events—because they tell you which incidents actually matter.

• Attack surface (Xpanse) tells you what’s reachable from the internet and what attackers can see.
• Posture (Prisma CSPM) tells you which controls are broken (public storage, permissive IAM, weak network paths).
• Runtime (Prisma CWPP) tells you what’s actively happening inside workloads (containers/hosts/serverless).

In Sentinel, these become powerful when you can join them with your “classic” telemetry (cloud activity logs, NSG flow logs, DNS, endpoint, identity). Result: fewer false positives, faster triage, better prioritization.

Connector overview (what each one ingests)

1) Palo Alto Prisma Cloud CSPM Solution

What comes in: Prisma Cloud CSPM alerts + audit logs via the Prisma Cloud CSPM API.
What it ships with: connector + parser + workbook + analytics rules + hunting queries + playbooks (prebuilt content).

Best for:

• Misconfig alerts: public storage, overly permissive IAM, weak encryption, risky network exposure.
• Compliance posture drift + audit readiness (prove you’re monitoring and responding).

2) Palo Alto Prisma Cloud CWPP (Preview)

What comes in: CWPP alerts via Prisma Cloud API (Compute/runtime side).
Implementation detail: Built on Codeless Connector Platform (CCP).

Best for:

• Runtime detections (host/container/serverless security alerts)
• “Exploit succeeded” signals that you need to correlate with posture and exposure.

3) Palo Alto Cortex Xpanse CCF

What comes in: Alerts logs fetched from the Cortex Xpanse API, ingested using Microsoft Sentinel Codeless Connector Framework (CCF).
Important: Supports DCR-based ingestion-time transformations that parse to a custom table for better performance.

Best for:

• External exposure findings and “internet-facing risk” detection
• Turning exposure into incidents only when the asset is critical / actively targeted.

Reference architecture (how the data lands in Sentinel)

Here’s the mental model you want for all three:

flowchart LR

A[Palo Alto Prisma Cloud CSPM] -->|CSPM API: alerts + audit logs| S[Sentinel Data Connector]

B[Palo Alto Prisma Cloud CWPP] -->|Prisma API: runtime alerts| S 

C[Cortex Xpanse] -->|Xpanse API: exposure alerts| S

S -->|CCF/CCP + DCR Transform| T[(Custom Tables)]

T --> K[KQL Analytics + Hunting] 

K --> I[Incidents]

I -->P[SOAR Playbooks]

K --> W[Workbooks / Dashboards]

Key design point: Xpanse explicitly emphasizes DCR transformations at ingestion time, use that to normalize fields early so your queries stay fast under load.

Deployment patterns (practical, SOC-friendly setup)

Step 0 — Decide what goes to “analytics” vs “storage”

If you’re using Sentinel’s data lake strategy, posture/exposure data is a perfect candidate for longer retention (trend + audit), while only “high severity” may need real-time analytics.

Step 1 — Install solutions from Content Hub

Install:

• Palo Alto Prisma Cloud CSPM Solution
• Palo Alto Prisma Cloud CWPP (Preview)
• Palo Alto Cortex Xpanse CCF

Step 2 — Credentials & least privilege

Create dedicated service accounts / API keys in Palo Alto products with read-only scope for:

• CSPM alerts + audit
• CWPP alerts
• Xpanse alerts/exposures

Step 3 — Validate ingestion (don’t skip this)

In Sentinel Logs:

1. Locate the custom tables created by each solution (Tables blade).
2. Run a basic sanity query:
   • “All events last 1h”
   • “Top 20 alert types”
   • “Distinct severities”

Tip: Save “ingestion smoke tests” as Hunting queries so you can re-run them after upgrades.

Step 4 — Turn on included analytics content (then tune)

The Prisma Cloud CSPM solution comes with multiple analytics rules, hunting queries, and playbooks out of the box—enable them gradually and tune thresholds before going wide.

Detection engineering: high-signal correlation recipes

Below are patterns that consistently outperform “single-source alerts.” I’m giving them as KQL templates using placeholder table names because your exact custom table names/columns are workspace-dependent (you’ll see them after install).

Recipe 1 — “Internet-exposed + actively probed” (Xpanse + network logs)

Goal: Only fire when exposure is real and there’s traffic evidence.

let xpanse = <XpanseTable>

| where TimeGenerated > ago(24h)

| where Severity in ("High","Critical")

| project AssetIp=<ip_field>, Finding=<finding_field>, Severity, TimeGenerated;

let net = <NetworkFlowTable>

| where TimeGenerated > ago(24h)

| where Direction == "Inbound" | summarize Hits=count(), SrcIps=make_set(SrcIp, 50) by DstIp;

xpanse

| join kind=inner (net) on $left.AssetIp == $right.DstIp | where Hits > 50

| project TimeGenerated, Severity, Finding, AssetIp, Hits, SrcIps

Why it works: Xpanse gives you exposure. Flow/WAF/Firewall gives you intent.

Recipe 2 — “Misconfiguration that creates a breach path” (CSPM + identity or cloud activity)

Goal: Prioritize posture findings that coincide with suspicious access or admin changes.

let posture = <PrismaCSPMTable>

| where TimeGenerated > ago(7d)

| where PolicySeverity in ("High","Critical")

| where FindingType has_any ("Public", "OverPermissive", "NoMFA", "EncryptionDisabled")

| project ResourceId=<resource_id>, Finding=<finding>, PolicySeverity, FirstSeen=TimeGenerated;

let activity = <CloudActivityTable>

| where TimeGenerated > ago(7d)

| where OperationName has_any ("RoleAssignmentWrite","SetIamPolicy","AddMember","CreateAccessKey")

| project ResourceId=<resource_id>, Actor=<caller>, OperationName, TimeGenerated;

posture | join kind=inner (activity) on ResourceId

| project PolicySeverity, Finding, OperationName, Actor, FirstSeen, TimeGenerated

| order by PolicySeverity desc, TimeGenerated desc

Recipe 3 — “Runtime alert on a workload that was already high-risk” (CWPP + CSPM)

Goal: Raise severity when runtime alerts occur on assets with known posture debt.

let risky_assets = <PrismaCSPMTable>

| where TimeGenerated > ago(30d)

| where PolicySeverity in ("High","Critical")

| summarize RiskyFindings=count() by AssetId=<asset_id>;

<CWPPTable>

| where TimeGenerated > ago(24h)

| project AssetId=<asset_id>, AlertName=<alert>, Severity=<severity>, TimeGenerated, Details=<details>

| join kind=leftouter (risky_assets) on AssetId

| extend RiskScore = coalesce(RiskyFindings,0) |

 order by Severity desc, RiskScore desc, TimeGenerated desc

SOC outcome: same runtime alert, different priority depending on posture risk.

Operational (in real life)

1) Normalize severities early

If Xpanse is using DCR transforms (it is), normalize severity to a consistent enum (“Informational/Low/Medium/High/Critical”) to simplify analytics.

2) Deduplicate exposure findings

Attack surface tools can generate repeated findings. Use a dedup function (hash of asset + finding type + port/service) and alert only on “new or changed exposure.”

3) Don’t incident-everything

Treat CSPM findings as:

• Incidents only when: critical + reachable + targeted OR tied to privileged activity
• Tickets when: high risk but not active
• Backlog when: medium/low with compensating controls

4) Make SOAR “safe by default”

Automations should prefer reversible actions:

• Block IP (temporary)
• Add to watchlist
• Notify owners
• Open ticket with evidence bundle
  …and only escalate to destructive actions after confidence thresholds.