CVE-2026-83548 Microsoft Sentinel · KQL

Detect SonicWall SMA1000 Server-Side Request Forgery Exploitation (CVE-2026-83548) in Microsoft Sentinel

Detects exploitation of CVE-2026-83548, a Server-Side Request Forgery (SSRF) vulnerability in SonicWall SMA1000 appliances. Unauthenticated attackers can coerce the appliance into issuing crafted HTTP/network requests to attacker-chosen internal or external destinations, enabling internal reconnaissance, metadata-service theft, and pivoting behind the perimeter. Listed in CISA KEV; actively exploited in the wild. This detection surfaces anomalous outbound/internal-bound requests originating from the SMA1000 management appliance, suspicious request patterns against the appliance's management/RAC endpoints, and the appliance reaching cloud metadata endpoints or internal RFC1918 hosts it should never contact.

MITRE ATT&CK

Tactic
Discovery Command and Control Reconnaissance

KQL Detection Query

Microsoft Sentinel (KQL)
kusto 
let smaAppliances = dynamic(["sma1000", "sslvpn", "sma-appliance"]);
let metadataIps = dynamic(["169.254.169.254", "100.100.100.200", "fd00:ec2::254"]);
CommonSecurityLog
| where DeviceVendor =~ "SonicWall"
| where DeviceProduct has_any ("SMA1000", "SMA 1000", "Secure Mobile Access")
| where DestinationIP in (metadataIps)
    or (ipv4_is_private(DestinationIP) and DestinationPort in (80, 443, 8080, 8443, 22, 3389, 6379, 9200, 2379))
| extend SsrfTarget = DestinationIP
| project TimeGenerated, DeviceVendor, DeviceProduct, SourceIP, DestinationIP = SsrfTarget, DestinationPort, RequestURL, DeviceAction, Message
| summarize RequestCount = count(), Targets = make_set(DestinationIP, 50), Ports = make_set(DestinationPort, 20) by SourceIP, bin(TimeGenerated, 15m)
| where RequestCount > 5 or array_length(Targets) > 3
| order by RequestCount desc
high severity medium confidence

Flags outbound requests originating from SonicWall SMA1000 appliance logs (CEF/CommonSecurityLog) that target cloud metadata IPs or a spread of internal RFC1918 services — the hallmark of SSRF-driven internal reconnaissance and metadata theft.

Data Sources

SonicWall SMA1000 syslog/CEFFirewall flow logs

Required Tables

CommonSecurityLog

False Positives & Tuning

  • Legitimate appliance health checks or update/license servers hosted on internal networks.
  • Administrator-initiated connectivity tests from the appliance CLI to internal hosts.
  • Backend authentication/RADIUS/LDAP traffic to internal identity services on standard ports.

Other platforms for CVE-2026-83548

Splunk (SPL) Elastic Security (Elastic) IBM QRadar (QRadar) Sumo Logic CSE (Sumo) Google Chronicle (YARA-L) CrowdStrike LogScale (LogScale) All platforms (combined) →

Testing Methodology

Validate this detection against 3 adversary techniques from Atomic Red Team. Each test below lists the behaviour to exercise and the telemetry you should expect to see. Executable commands and cleanup steps are available with Pro.

  1. Test 1Simulated SSRF request to cloud metadata endpoint

    Expected signal: Outbound connection from the host to 169.254.169.254 on port 80 recorded in network/proxy logs.

  2. Test 2Simulated SSRF internal service fan-out scan

    Expected signal: Multiple short-lived outbound connections from one source to 10.0.0.10 across many ports within 15 minutes.

  3. Test 3Simulated crafted request to appliance SSRF endpoint

    Expected signal: Inbound request to the appliance management endpoint followed by an appliance-sourced outbound request to the injected URL.

Last updated: 2026-09-03 Research depth: standard
References (5)

Response Playbook

Triage

  1. Confirm the source device is a SonicWall SMA1000 appliance and identify its firmware version; cross-reference against SNWLID-2026-0016 to confirm exposure to CVE-2026-83548.
  2. Review the destination targets of the flagged requests: metadata IPs (169.254.169.254 / 100.100.100.200) and internal service ports strongly indicate SSRF exploitation rather than benign traffic.
  3. Correlate the timing of anomalous outbound requests with inbound unauthenticated HTTP requests to the appliance's management/RAC endpoints to establish the attacker's entry request.
  4. Check whether the appliance is internet-exposed and whether it received requests from previously unseen external source IPs immediately preceding the SSRF activity.

Containment

  1. Restrict inbound access to the SMA1000 management interface to trusted admin IPs and place the appliance behind a WAF/ACL until patched per the SonicWall advisory.
  2. Apply the SonicWall SMA1000 firmware fix referenced in SNWLID-2026-0016; if a patch is not yet deployable, follow vendor interim mitigations and isolate the appliance from internal service ranges.
  3. Block the appliance's egress to cloud metadata IPs and to sensitive internal service ports at the firewall to neutralize the SSRF impact.

Evidence Collection

  1. Preserve SMA1000 appliance logs (management, access, and syslog/CEF exports) covering the exploitation window before rotation.
  2. Capture firewall/proxy flow records showing appliance-sourced connections to metadata and internal targets, including full URLs and destination ports.

Escalation Criteria

  • !Escalate to incident response if the appliance successfully reached a cloud metadata endpoint (potential credential/token theft).
  • !Escalate if SSRF pivoting reached internal management, database, or identity services, indicating lateral movement beyond the appliance.

Investigation Guide

Related Techniques

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Forensic Artifacts

  • >SMA1000 appliance access/management logs showing crafted requests to the vulnerable endpoint and subsequent outbound connections.
  • >Firewall/proxy connection records with appliance as source and metadata/internal IPs as destination.
  • >Appliance process/network state at time of exploitation (if console access preserved).

Tuning Guidance

Baseline the SMA1000 appliance's legitimate egress (update/licensing servers, RADIUS/LDAP/identity backends) and allowlist those destinations to reduce noise. Tighten the internal-target port list to services actually present in your environment, and lower the request-count threshold for appliances that should have minimal or no internal egress. Once patched, retain the metadata-endpoint hunt as a standing high-severity alert since the appliance should never contact metadata IPs.

Hunting Queries

Hunt for any SMA1000 appliance request reaching cloud metadata endpoints — a high-fidelity indicator of successful SSRF credential theft.

Hunting — KQL
kql 
CommonSecurityLog | where DeviceVendor =~ "SonicWall" and DeviceProduct has "SMA1000" | where DestinationIP in ("169.254.169.254","100.100.100.200") | project TimeGenerated, SourceIP, DestinationIP, RequestURL, DeviceAction
Hunting — SPL
spl 
index=network sourcetype="sonicwall:sma" (dest_ip="169.254.169.254" OR dest_ip="100.100.100.200") | table _time src_ip dest_ip url action

Atomic Red Team Tests

Test 1 Simulated SSRF request to cloud metadata endpoint
linux

Emulates the appliance being coerced into requesting the cloud instance metadata service, as seen in CVE-2026-83548 exploitation. Lab-only.

Command

bash 
curl -s -m 5 -o /dev/null -w '%{http_code}\n' http://169.254.169.254/latest/meta-data/iam/security-credentials/

Cleanup

bash 
echo 'No cleanup required; no local artifacts created.'

Expected Telemetry

Outbound connection from the host to 169.254.169.254 on port 80 recorded in network/proxy logs.

Expected Detection

KQL/SPL metadata-endpoint rule and hunt fire on the appliance-sourced request to 169.254.169.254.

Test 2 Simulated SSRF internal service fan-out scan
linux

Emulates SSRF-driven internal reconnaissance by connecting to multiple internal service ports in a short window. Lab-only, use a controlled internal range.

Command

bash 
for p in 80 443 8080 8443 22 6379 9200 2379; do curl -s -m 2 -o /dev/null http://10.0.0.10:$p/ ; done

Cleanup

bash 
echo 'No cleanup required; no local artifacts created.'

Expected Telemetry

Multiple short-lived outbound connections from one source to 10.0.0.10 across many ports within 15 minutes.

Expected Detection

Fan-out threshold (distinct_targets/ports and request_count) trips the primary detection across all SIEM dialects.

Test 3 Simulated crafted request to appliance SSRF endpoint
windows

Emulates an unauthenticated attacker sending a crafted URL parameter to the SMA1000 management endpoint to trigger a server-side request. Lab-only against a test appliance.

Command

powershell 
powershell -c "try { Invoke-WebRequest -UseBasicParsing -TimeoutSec 5 -Uri 'https://sma-lab.internal/__api__/v1/logon/gateway?url=http://169.254.169.254/latest/meta-data/' } catch { $_.Exception.Message }"

Cleanup

powershell 
powershell -c "Remove-Variable -Name * -ErrorAction SilentlyContinue"

Expected Telemetry

Inbound request to the appliance management endpoint followed by an appliance-sourced outbound request to the injected URL.

Expected Detection

Correlation of inbound crafted request with outbound metadata/internal connection surfaces in triage step 3 and the primary detection.

Related Detections

Tactic Hubs

TA0007DiscoveryTA0011Command and ControlTA0043Reconnaissance

Related Techniques

T1090ProxyT1046Network Service DiscoveryT1552.005Cloud Instance Metadata API

Same Tactic: Discovery

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