T1572 — Protocol Tunneling

# T1572 - Protocol Tunneling

## SOC Recommendation
Investigate Protocol Tunneling activity in the context of Command and Control: 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 |
|---|---|---|
| User Geolocation Logon Pattern Analysis | Detect | Monitor for User Geolocation Logon Pattern Analysis indicators relevant to this technique. |
| Network Traffic Filtering | Isolate | Apply Network Traffic Filtering to contain the blast radius once this technique is observed. |

## 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
//TOR Node Network Indicators - Block Recommended
let timeFrame= 5m;
CyfirmaIndicators_CL 
| where ConfidenceScore >= 80
    and TimeGenerated between (ago(timeFrame) .. now())
    and pattern !contains 'file:hashes' and RecommendedActions has 'Block' and Roles has 'TOR'
| extend IPv4 = extract(@"ipv4-addr:value\s*=\s*'([^']+)'", 1, pattern)
| extend IPv6 = extract(@"ipv6-addr:value\s*=\s*'([^']+)'", 1, pattern)
| extend URL = extract(@"url:value\s*=\s*'([^']+)'", 1, pattern)
| extend Domain = extract(@"domain-name:value\s*=\s*'([^']+)'", 1, pattern)
| extend parsed = parse_json(extensions)
| extend extensionKeys = bag_keys(parsed)
| mv-expand extensionKeys
| extend extensionKeyStr = tostring(extensionKeys)
| extend ext = parsed[extensionKeyStr]
| extend props = ext.properties
| extend 
    extension_id = extensionKeyStr,
    ASN_Owner = props.asn_owner,
    ASN = props.asn,
    ProviderName = 'CYFIRMA',
    ProductName = 'DeCYFIR/DeTCT'
| project
    IPv4,
    IPv6,
    URL,
    Domain,
    ThreatActors,
    RecommendedActions,
    Sources,
    Roles,
    Country,
    IPAbuse,
    name,
    Description,
    ConfidenceScore,
    IndicatorID,
    created,
    modified,
    valid_from,
    Tags,
    ThreatType,
    TimeGenerated,
    SecurityVendors,
    ProductName,
    ProviderName
```
```kql
//TOR Node Network Indicators - Monitor Recommended 
let timeFrame= 5m;
CyfirmaIndicators_CL 
| where ConfidenceScore >= 80
    and TimeGenerated between (ago(timeFrame) .. now())
    and pattern !contains 'file:hashes' and RecommendedActions has 'Monitor' and Roles has 'TOR'
| extend IPv4 = extract(@"ipv4-addr:value\s*=\s*'([^']+)'", 1, pattern)
| extend IPv6 = extract(@"ipv6-addr:value\s*=\s*'([^']+)'", 1, pattern)
| extend URL = extract(@"url:value\s*=\s*'([^']+)'", 1, pattern)
| extend Domain = extract(@"domain-name:value\s*=\s*'([^']+)'", 1, pattern)
| extend parsed = parse_json(extensions)
| extend extensionKeys = bag_keys(parsed)
| mv-expand extensionKeys
| extend extensionKeyStr = tostring(extensionKeys)
| extend ext = parsed[extensionKeyStr]
| extend props = ext.properties
| extend 
    extension_id = extensionKeyStr,
    ASN_Owner = props.asn_owner,
    ASN = props.asn,
    ProviderName = 'CYFIRMA',
    ProductName = 'DeCYFIR/DeTCT'
| project
    IPv4,
    IPv6,
    URL,
    Domain,
    ThreatActors,
    RecommendedActions,
    Sources,
    Roles,
    Country,
    IPAbuse,
    name,
    Description,
    ConfidenceScore,
    IndicatorID,
    created,
    modified,
    valid_from,
    Tags,
    ThreatType,
    TimeGenerated,
    SecurityVendors,
    ProductName,
    ProviderName
```
```kql
let LearningPeriod = 7d;
let RunTime = 1h;
let StartLearningPeriod = LearningPeriod + RunTime;
let DetectionWindowStart = ago(RunTime);
let LearningPortToProtocol1 =  (AzureDiagnostics
| where TimeGenerated between (ago(StartLearningPeriod) .. ago(RunTime))
| where OperationName == "AzureFirewallApplicationRuleLog"
| extend msg_s= column_ifexists('msg_s',Message)
| parse msg_s with Protocol " request from " SourceIp ":" SourcePort:int " to " Fqdn ":" DestinationPort:int "." *
| where isnotempty(DestinationPort)
| summarize LearningTimeCount = count() by LearningTimeDstPort = DestinationPort, LearningTimeProtocol = Protocol, SourceIp, Fqdn);
let LearningPortToProtocol2 = (AZFWNetworkRule
| where TimeGenerated between (ago(StartLearningPeriod) .. ago(RunTime))
| where isnotempty(DestinationPort)
| extend Fqdn = DestinationIp
| summarize LearningTimeCount = count() by LearningTimeDstPort = DestinationPort, LearningTimeProtocol = Protocol, SourceIp, Fqdn);
let LearningPortToProtocol3 = (AZFWApplicationRule
| where TimeGenerated between (ago(StartLearningPeriod) .. ago(RunTime))
| where isnotempty(DestinationPort)
| summarize LearningTimeCount = count() by LearningTimeDstPort = DestinationPort, LearningTimeProtocol = Protocol, SourceIp, Fqdn);
let AlertTimePortToProtocol1 = (AzureDiagnostics
| where TimeGenerated between (DetectionWindowStart .. now())
| where OperationName == "AzureFirewallApplicationRuleLog"
| extend msg_s= column_ifexists('msg_s',Message)
| parse msg_s with Protocol " request from " SourceIp ":" SourcePort " to " Fqdn ":" DestinationPort:int "." *
| where isnotempty(DestinationPort)
| summarize AlertTimeCount = count() by AlertTimeDstPort = DestinationPort, AlertTimeProtocol = Protocol);
let AlertTimePortToProtocol2 = (AZFWNetworkRule
| where TimeGenerated between (DetectionWindowStart .. now())
| where isnotempty(DestinationPort)
| extend Fqdn = DestinationIp
| summarize AlertTimeCount = count() by AlertTimeDstPort = DestinationPort, AlertTimeProtocol = Protocol);
let AlertTimePortToProtocol3 = (AZFWApplicationRule
| where TimeGenerated between (DetectionWindowStart .. now())
| where isnotempty(DestinationPort)
| summarize AlertTimeCount = count() by AlertTimeDstPort = DestinationPort, AlertTimeProtocol = Protocol);
(union isfuzzy=true 
(AlertTimePortToProtocol1 
| join kind=leftouter (LearningPortToProtocol1) on $left.AlertTimeDstPort == $right.LearningTimeDstPort
| where LearningTimeProtocol != AlertTimeProtocol),
(AlertTimePortToProtocol2 
| join kind=leftouter (LearningPortToProtocol2) on $left.AlertTimeDstPort == $right.LearningTimeDstPort
| where LearningTimeProtocol != AlertTimeProtocol),
(AlertTimePortToProtocol3 
| join kind=leftouter (LearningPortToProtocol3) on $left.AlertTimeDstPort == $right.LearningTimeDstPort
| where LearningTimeProtocol != AlertTimeProtocol))
```

## Escalation Criteria
- Protocol Tunneling 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.

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• /api/techniques/T1572.json
• /api/recommendations/T1572.json
• /api/d3fend/T1572.json
• /api/mappings/T1572.json
• /api/confluence/T1572.md

Example curl:

curl https://atlas.basyrix.com/api/recommendations/T1572.json

Response:

{
  "technique_id": "T1572",
  "name": "Protocol Tunneling",
  "priority": "high",
  "status": "draft",
  "version": "0.1.0",
  "last_reviewed": "2026-07-23",
  "generated_by": "SOC Response Atlas by Basyrix",
  "tactics": [
    "Command and Control"
  ],
  "platforms": [
    "ESXi",
    "Linux",
    "macOS",
    "Windows"
  ],
  "summary": "Adversaries may tunnel network communications to and from a victim system within a separate protocol to avoid detection/network filtering and/or enable access to otherwise unreachable systems. Tunneling involves explicitly encapsulating a protocol within another. This behavior may conceal malicious traffic by blending in with existing traffic and/or provide an outer layer of encryption (similar to a VPN)...",
  "soc_recommendation": "Investigate Protocol Tunneling activity in the context of Command and Control: confirm scope, affected host/identity, and whether it matches expected administrative behaviour before deciding this is benign.",
  "d3fend_mappings": [
    {
      "id": "D3-UGLPA",
      "name": "User Geolocation Logon Pattern Analysis",
      "relationship": "detect",
      "practical_action": "Monitor for User Geolocation Logon Pattern Analysis indicators relevant to this technique.",
      "tooling": [
        "Defender for Endpoint"
      ]
    },
    {
      "id": "D3-NTF",
      "name": "Network Traffic Filtering",
      "relationship": "isolate",
      "practical_action": "Apply Network Traffic Filtering to contain the blast radius once this technique is observed.",
      "tooling": [
        "Sentinel",
        "Defender for Endpoint"
      ]
    }
  ],
  "investigation_steps": {
    "microsoft": [
      "Review Defender for Endpoint / Defender XDR alerts and timeline for the affected host or identity.",
      "Check Sentinel analytics rules and incidents correlated with this technique.",
      "Review Entra ID sign-in and audit logs if the technique involves an identity or cloud resource."
    ],
    "generic": [
      "Confirm whether the observed protocol tunneling activity matches expected administrative or application behaviour.",
      "Identify the host, account, or resource where the activity occurred and its business criticality.",
      "Check for related alerts before and after this activity to reconstruct the broader intrusion timeline.",
      "Real detection reference: \"CYFIRMA - High severity TOR Node Network Indicators - Block Recommended Rule\" -- \"This KQL query identifies network-based indicators from CYFIRMA intelligence that are associated with the role 'TOR'. These indicators may include IP addresses, domains, and URLs related to Tor network activity. Threat actors often use Tor for anonymous communication, command and control, data exfiltration, and evasion of network defenses.\""
    ]
  },
  "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": [
    {
      "name": "Contain the affected host or account",
      "category": "Containment",
      "risk": "Medium",
      "automation_safe": false,
      "approval_required": true,
      "tool": "Defender for Endpoint / Entra ID",
      "notes": "Requires approval -- confirm malicious intent before isolating a host or disabling an account."
    },
    {
      "name": "Collect and preserve evidence",
      "category": "Investigation",
      "risk": "Low",
      "automation_safe": true,
      "approval_required": false,
      "tool": "Defender for Endpoint",
      "notes": "Safe -- read-only evidence collection."
    }
  ],
  "queries": {
    "kql": [
      {
        "name": "fa53ac37-a646-4106-91b6-ce478a1b5323 — CYFIRMA - High severity TOR Node Network Indicators - Block Recommended Rule",
        "description": "\"This KQL query identifies network-based indicators from CYFIRMA intelligence that are associated with the role 'TOR'. These indicators may include IP addresses, domains, and URLs related to Tor network activity. Threat actors often use Tor for anonymous communication, command and control, data exfiltration, and evasion of network defenses.\" (Source: Microsoft's official Azure-Sentinel Detections (MIT licensed).)",
        "query": "//TOR Node Network Indicators - Block Recommended\nlet timeFrame= 5m;\nCyfirmaIndicators_CL \n| where ConfidenceScore >= 80\n    and TimeGenerated between (ago(timeFrame) .. now())\n    and pattern !contains 'file:hashes' and RecommendedActions has 'Block' and Roles has 'TOR'\n| extend IPv4 = extract(@\"ipv4-addr:value\\s*=\\s*'([^']+)'\", 1, pattern)\n| extend IPv6 = extract(@\"ipv6-addr:value\\s*=\\s*'([^']+)'\", 1, pattern)\n| extend URL = extract(@\"url:value\\s*=\\s*'([^']+)'\", 1, pattern)\n| extend Domain = extract(@\"domain-name:value\\s*=\\s*'([^']+)'\", 1, pattern)\n| extend parsed = parse_json(extensions)\n| extend extensionKeys = bag_keys(parsed)\n| mv-expand extensionKeys\n| extend extensionKeyStr = tostring(extensionKeys)\n| extend ext = parsed[extensionKeyStr]\n| extend props = ext.properties\n| extend \n    extension_id = extensionKeyStr,\n    ASN_Owner = props.asn_owner,\n    ASN = props.asn,\n    ProviderName = 'CYFIRMA',\n    ProductName = 'DeCYFIR/DeTCT'\n| project\n    IPv4,\n    IPv6,\n    URL,\n    Domain,\n    ThreatActors,\n    RecommendedActions,\n    Sources,\n    Roles,\n    Country,\n    IPAbuse,\n    name,\n    Description,\n    ConfidenceScore,\n    IndicatorID,\n    created,\n    modified,\n    valid_from,\n    Tags,\n    ThreatType,\n    TimeGenerated,\n    SecurityVendors,\n    ProductName,\n    ProviderName"
      },
      {
        "name": "6f107cf8-02f9-4440-b5d8-1235293e5ad7 — CYFIRMA - High severity TOR Node Network Indicators - Monitor Recommended Rule",
        "description": "\"This KQL query identifies network-based indicators from CYFIRMA intelligence that are associated with the role 'TOR'. These indicators may include IP addresses, domains, and URLs related to Tor network activity. Threat actors often use Tor for anonymous communication, command and control, data exfiltration, and evasion of network defenses.\" (Source: Microsoft's official Azure-Sentinel Detections (MIT licensed).)",
        "query": "//TOR Node Network Indicators - Monitor Recommended \nlet timeFrame= 5m;\nCyfirmaIndicators_CL \n| where ConfidenceScore >= 80\n    and TimeGenerated between (ago(timeFrame) .. now())\n    and pattern !contains 'file:hashes' and RecommendedActions has 'Monitor' and Roles has 'TOR'\n| extend IPv4 = extract(@\"ipv4-addr:value\\s*=\\s*'([^']+)'\", 1, pattern)\n| extend IPv6 = extract(@\"ipv6-addr:value\\s*=\\s*'([^']+)'\", 1, pattern)\n| extend URL = extract(@\"url:value\\s*=\\s*'([^']+)'\", 1, pattern)\n| extend Domain = extract(@\"domain-name:value\\s*=\\s*'([^']+)'\", 1, pattern)\n| extend parsed = parse_json(extensions)\n| extend extensionKeys = bag_keys(parsed)\n| mv-expand extensionKeys\n| extend extensionKeyStr = tostring(extensionKeys)\n| extend ext = parsed[extensionKeyStr]\n| extend props = ext.properties\n| extend \n    extension_id = extensionKeyStr,\n    ASN_Owner = props.asn_owner,\n    ASN = props.asn,\n    ProviderName = 'CYFIRMA',\n    ProductName = 'DeCYFIR/DeTCT'\n| project\n    IPv4,\n    IPv6,\n    URL,\n    Domain,\n    ThreatActors,\n    RecommendedActions,\n    Sources,\n    Roles,\n    Country,\n    IPAbuse,\n    name,\n    Description,\n    ConfidenceScore,\n    IndicatorID,\n    created,\n    modified,\n    valid_from,\n    Tags,\n    ThreatType,\n    TimeGenerated,\n    SecurityVendors,\n    ProductName,\n    ProviderName"
      },
      {
        "name": "826f930c-2f25-4508-8e75-a95b809a4e15 — Abnormal Port to Protocol",
        "description": "Identifies communication for well known protocol over a non-standard port based on learning period activity. This can indicate malicious communication (C2) or exfiltration by attackers trying to communicate over known ports (22:SSH, 80:HTTP) but dont use the known protocol headers to match the port number. Configurable Parameters: - Learning period time - learning period for protocol learning in days. Default is set to 7.' (Source: Microsoft's official Azure-Sentinel Detections (MIT licensed).)",
        "query": "let LearningPeriod = 7d;\nlet RunTime = 1h;\nlet StartLearningPeriod = LearningPeriod + RunTime;\nlet DetectionWindowStart = ago(RunTime);\nlet LearningPortToProtocol1 =  (AzureDiagnostics\n| where TimeGenerated between (ago(StartLearningPeriod) .. ago(RunTime))\n| where OperationName == \"AzureFirewallApplicationRuleLog\"\n| extend msg_s= column_ifexists('msg_s',Message)\n| parse msg_s with Protocol \" request from \" SourceIp \":\" SourcePort:int \" to \" Fqdn \":\" DestinationPort:int \".\" *\n| where isnotempty(DestinationPort)\n| summarize LearningTimeCount = count() by LearningTimeDstPort = DestinationPort, LearningTimeProtocol = Protocol, SourceIp, Fqdn);\nlet LearningPortToProtocol2 = (AZFWNetworkRule\n| where TimeGenerated between (ago(StartLearningPeriod) .. ago(RunTime))\n| where isnotempty(DestinationPort)\n| extend Fqdn = DestinationIp\n| summarize LearningTimeCount = count() by LearningTimeDstPort = DestinationPort, LearningTimeProtocol = Protocol, SourceIp, Fqdn);\nlet LearningPortToProtocol3 = (AZFWApplicationRule\n| where TimeGenerated between (ago(StartLearningPeriod) .. ago(RunTime))\n| where isnotempty(DestinationPort)\n| summarize LearningTimeCount = count() by LearningTimeDstPort = DestinationPort, LearningTimeProtocol = Protocol, SourceIp, Fqdn);\nlet AlertTimePortToProtocol1 = (AzureDiagnostics\n| where TimeGenerated between (DetectionWindowStart .. now())\n| where OperationName == \"AzureFirewallApplicationRuleLog\"\n| extend msg_s= column_ifexists('msg_s',Message)\n| parse msg_s with Protocol \" request from \" SourceIp \":\" SourcePort \" to \" Fqdn \":\" DestinationPort:int \".\" *\n| where isnotempty(DestinationPort)\n| summarize AlertTimeCount = count() by AlertTimeDstPort = DestinationPort, AlertTimeProtocol = Protocol);\nlet AlertTimePortToProtocol2 = (AZFWNetworkRule\n| where TimeGenerated between (DetectionWindowStart .. now())\n| where isnotempty(DestinationPort)\n| extend Fqdn = DestinationIp\n| summarize AlertTimeCount = count() by AlertTimeDstPort = DestinationPort, AlertTimeProtocol = Protocol);\nlet AlertTimePortToProtocol3 = (AZFWApplicationRule\n| where TimeGenerated between (DetectionWindowStart .. now())\n| where isnotempty(DestinationPort)\n| summarize AlertTimeCount = count() by AlertTimeDstPort = DestinationPort, AlertTimeProtocol = Protocol);\n(union isfuzzy=true \n(AlertTimePortToProtocol1 \n| join kind=leftouter (LearningPortToProtocol1) on $left.AlertTimeDstPort == $right.LearningTimeDstPort\n| where LearningTimeProtocol != AlertTimeProtocol),\n(AlertTimePortToProtocol2 \n| join kind=leftouter (LearningPortToProtocol2) on $left.AlertTimeDstPort == $right.LearningTimeDstPort\n| where LearningTimeProtocol != AlertTimeProtocol),\n(AlertTimePortToProtocol3 \n| join kind=leftouter (LearningPortToProtocol3) on $left.AlertTimeDstPort == $right.LearningTimeDstPort\n| where LearningTimeProtocol != AlertTimeProtocol))"
      }
    ],
    "spl": [],
    "esql": [
      {
        "name": "882a39ad-a404-45e3-b5d4-bc11d2b09818 — Potential DNS Exfiltration via Excessive Chunked Queries",
        "description": "(ESQL) Identifies potential DNS exfiltration on Windows hosts by detecting a high volume of DNS queries whose subdomain labels follow a chunked encoding pattern (index-payload.base_domain)... (Source: Elastic's official detection-rules repository (Elastic License v2).)",
        "query": "FROM logs-crowdstrike.fdr*, logs-endpoint.events.network-*, logs-windows.sysmon_operational-*\n| WHERE host.os.type == \"windows\"\n    AND event.category == \"network\"\n    AND event.action IN (\"lookup_requested\", \"DNSEvent (DNS query)\", \"DnsRequest\")\n    AND process.name != \"svchost.exe\"\n    AND dns.question.name RLIKE \"\"\"[0-9]{1,5}-[A-Za-z0-9+/=]{15,63}\\..+\"\"\"\n| GROK dns.question.name \"%{INT:chunk_index}-%{DATA:chunk_payload}\\\\.%{GREEDYDATA:Esql.base_domain}\"\n| WHERE chunk_index IS NOT NULL\n| EVAL payload_len = LENGTH(chunk_payload)\n| STATS\n    Esql.occurrences = COUNT(*),\n    Esql.unique_chunks = COUNT_DISTINCT(chunk_index),\n    Esql.max_index = MAX(TO_INTEGER(chunk_index)),\n    Esql.avg_payload_len = AVG(payload_len)\n  BY process.name, Esql.base_domain, user.id, user.name, host.id, host.name, data_stream.namespace, DATE_TRUNC(5 minutes, @timestamp)\n| WHERE Esql.occurrences >= 30\n    AND Esql.unique_chunks >= 30\n    AND Esql.avg_payload_len >= 20\n| SORT Esql.unique_chunks DESC\n| LIMIT 20\n| KEEP host.id, host.name, process.name, user.id, user.name, data_stream.namespace, Esql.*"
      },
      {
        "name": "9f1c4ca3-44b5-481d-ba42-32dc215a2769 — Potential Protocol Tunneling via EarthWorm",
        "description": "(EQL) Identifies the execution of the EarthWorm tunneler. Adversaries may tunnel network communications to and from a victim system within a separate protocol to avoid detection and network filtering, or to enable access to otherwise unreachable systems. (Source: Elastic's official detection-rules repository (Elastic License v2).)",
        "query": "process where host.os.type == \"linux\" and event.type == \"start\" and\nevent.action in (\"exec\", \"start\", \"exec_event\", \"ProcessRollup2\", \"executed\", \"exec_event\", \"process_started\") and\nprocess.args : \"-s\" and process.args : \"-d\" and process.args : \"rssocks\""
      }
    ]
  },
  "automation": {
    "safe": [
      "Add recommendation as Sentinel incident comment.",
      "Run enrichment queries.",
      "Create ServiceNow SecOps task."
    ],
    "approval_required": [
      "Contain or disable the affected host/account.",
      "Any change to production configuration."
    ]
  },
  "escalation_criteria": [
    "Protocol Tunneling 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."
  ],
  "confluence": {
    "title": "T1572 - Protocol Tunneling Response Guidance",
    "labels": [
      "mitre",
      "attack",
      "d3fend",
      "secops",
      "basyrix"
    ],
    "sections": [
      "summary",
      "d3fend_mappings",
      "investigation_steps",
      "response_actions",
      "queries",
      "automation",
      "escalation_criteria",
      "false_positive_considerations"
    ]
  }
}