# T1211 - Exploitation for Stealth

## SOC Recommendation
Investigate Exploitation for Stealth activity in the context of Stealth: confirm scope, affected host/identity, and whether it matches expected administrative behaviour before deciding this is benign.

## D3FEND Mappings
| D3FEND Technique | Relationship | Practical SOC Action |
|---|---|---|
| Memory Boundary Tracking | Detect | Monitor for Memory Boundary Tracking indicators relevant to this technique. |
| Process Segment Execution Prevention | Harden | Apply Process Segment Execution Prevention to reduce this technique's viability before an incident occurs. |

## Investigation Steps
1. Review Defender for Endpoint / Defender XDR alerts and timeline for the affected host or identity.
2. Check Sentinel analytics rules and incidents correlated with this technique.
3. Review Entra ID sign-in and audit logs if the technique involves an identity or cloud resource.

## Evidence to Collect
- Host or resource affected
- Account or identity involved
- Timestamp of the activity
- Related process, file, or network artifact
- Any preceding or follow-on alerts

## Response Actions
| Action | Risk | Automation Safe | Approval Required |
|---|---|---|---|
| Contain the affected host or account | Medium | No | Yes |
| Collect and preserve evidence | Low | Yes | No |

## KQL
```kql
let Threshold = 3;
AzureDiagnostics
| where Category == "ApplicationGatewayFirewallLog"
| where action_s == "Matched"
| project transactionId_g, hostname_s, requestUri_s, TimeGenerated, clientIp_s, Message, details_message_s, details_data_s
| join kind = inner(
AzureDiagnostics
| where Category == "ApplicationGatewayFirewallLog"
| where action_s == "Blocked"
| parse Message with MessageText 'Total Inbound Score: ' TotalInboundScore ' - SQLI=' SQLI_Score ',XSS=' XSS_Score ',RFI=' RFI_Score ',LFI=' LFI_Score ',RCE=' RCE_Score ',PHPI=' PHPI_Score ',HTTP=' HTTP_Score ',SESS=' SESS_Score '): ' Blocked_Reason '; individual paranoia level scores:' Paranoia_Score
| where Blocked_Reason contains "SQL Injection Attack" and toint(SQLI_Score) >=10 and toint(TotalInboundScore) >= 15) on transactionId_g
| extend Uri = strcat(hostname_s,requestUri_s)
| summarize StartTime = min(TimeGenerated), EndTime = max(TimeGenerated), TransactionID = make_set(transactionId_g), Message = make_set(Message), Detail_Message = make_set(details_message_s), Detail_Data = make_set(details_data_s), Total_TransactionId = dcount(transactionId_g) by clientIp_s, Uri, action_s, SQLI_Score, TotalInboundScore
| where Total_TransactionId >= Threshold
```
```kql
let Threshold = 1;
AzureDiagnostics
| where Category =~ "FrontDoorWebApplicationFirewallLog"
| where action_s =~ "AnomalyScoring"
| where details_msg_s has "SQL Injection"
| parse details_data_s with MessageText "Matched Data:" MatchedData "AND " * "table_name FROM " TableName " " *
| project trackingReference_s, host_s, requestUri_s, TimeGenerated, clientIP_s, details_matches_s, details_msg_s, details_data_s, TableName, MatchedData
| join kind = inner(
AzureDiagnostics
| where Category =~ "FrontDoorWebApplicationFirewallLog"
| where action_s =~ "Block") on trackingReference_s
| summarize URI_s = make_set(requestUri_s,100), Table = make_set(TableName,100), StartTime = min(TimeGenerated), EndTime = max(TimeGenerated), TrackingReference = make_set(trackingReference_s,100), Matched_Data = make_set(MatchedData,100), Detail_Data = make_set(details_data_s,100), Detail_Message = make_set(details_msg_s,100), Total_TrackingReference = dcount(trackingReference_s) by clientIP_s, host_s, action_s
| where Total_TrackingReference >= Threshold
```
```kql
let Threshold = 3;  
AGWFirewallLogs
| where Action == "Matched"
| where Message has "SQL Injection"
| project TransactionId, Hostname, RequestUri, TimeGenerated, ClientIp, Message
| join kind = inner(
AGWFirewallLogs
| where Action == "Blocked"
| extend transactionId_g = tostring(TransactionId)) on TransactionId
| extend Uri = strcat(Hostname,RequestUri)
| summarize StartTime = min(TimeGenerated), EndTime = max(TimeGenerated), TransactionID = make_set(transactionId_g,100), Message = make_set(Message,100), Total_TransactionId = dcount(transactionId_g) by ClientIp, Uri, Action
| where Total_TransactionId >= Threshold
```

## Escalation Criteria
- Exploitation for Stealth activity observed on a privileged account or critical system.
- Activity follows or precedes other suspicious behaviour in the same investigation.
- Automated triage cannot confidently rule out malicious intent.

## False Positive Considerations
- Legitimate administrative or maintenance activity matching this pattern.
- Approved security testing or red team exercise.
- Known benign software producing similar telemetry.

Generated by SOC Response Atlas by Basyrix.