DORA-Art10-P1

Article
10 (1)
Pillar
ICT Risk Management
Regulation Ref
Regulation (EU) 2022/2554, Article 10(1)
Last Reviewed
2026-01-15

Financial entities shall have in place mechanisms to promptly detect anomalous activities, including ICT network performance issues and ICT-related incidents, and to identify potential material single points of failure.

Evidence Profiles

ICT Monitoring and Detection Configuration PARTIAL

JSON configuration export of monitoring tools, alert thresholds, anomaly detection rules, and SIEM configurations as required by DORA Article 10.

Formats
JSON
Evidence Class
ict-monitoring-config
Availability
PARTIAL
Update Frequency
quarterly
Typical Author
Security Operations Manager
Approval Chain
Security Operations Manager → CISO

Content Sections

Expected Fields

Common Quality Issues

View Example

Generated example artifact using the default institution profile (COMMON availability, synthetic data only).

JSON — Inline Preview
{
  "configVersion": "2.3",
  "exportDate": "2025-01-10",
  "institution": "Nordvik Bank AG",
  "exportedBy": "Security Operations Manager",
  "monitoringTools": [
    {
      "toolId": "MON-001",
      "name": "Splunk Enterprise",
      "category": "SIEM",
      "version": "9.2.1",
      "deployment": "On-premises (Zurich DC-1)",
      "logSourcesConnected": 47,
      "eventsPerSecond": 12500,
      "retentionDays": 365,
      "status": "Active"
    },
    {
      "toolId": "MON-002",
      "name": "CrowdStrike Falcon",
      "category": "EDR",
      "version": "7.10",
      "deployment": "Cloud-managed",
      "endpointsCovered": 1389,
      "status": "Active"
    },
    {
      "toolId": "MON-003",
      "name": "Palo Alto Cortex XSOAR",
      "category": "SOAR",
      "version": "8.5",
      "deployment": "On-premises (Zurich DC-1)",
      "playbooksActive": 28,
      "status": "Active"
    },
    {
      "toolId": "MON-004",
      "name": "Qualys VMDR",
      "category": "Vulnerability Management",
      "version": "Cloud",
      "deployment": "Cloud-managed",
      "assetsScanned": 1247,
      "scanFrequency": "Weekly (external), Monthly (internal)",
      "status": "Active"
    },
    {
      "toolId": "MON-005",
      "name": "Darktrace Enterprise",
      "category": "Network Anomaly Detection",
      "version": "6.1",
      "deployment": "On-premises (Zurich DC-1)",
      "networkSegmentsMonitored": 5,
      "status": "Active"
    }
  ],
  "alertRules": {
    "totalRules": 342,
    "byCategory": {
      "authentication_anomaly": 45,
      "privilege_escalation": 38,
      "data_exfiltration": 32,
      "malware_detection": 52,
      "network_anomaly": 41,
      "policy_violation": 28,
      "system_availability": 35,
      "configuration_change": 22,
      "third_party_integration": 18,
      "compliance_monitoring": 31
    },
    "bySeverity": {
      "critical": 48,
      "high": 87,
      "medium": 124,
      "low": 83
    },
    "sampleRules": [
      {
        "ruleId": "ALR-AUTH-001",
        "name": "Multiple Failed Authentication — Critical System",
        "severity": "High",
        "condition": "5+ failed login attempts within 10 minutes on critical systems",
        "action": "Alert SOC analyst; auto-lock account after 10 attempts",
        "lastTriggered": "2025-01-08T14:23:00Z"
      },
      {
        "ruleId": "ALR-PRIV-001",
        "name": "Privileged Account Used Outside Business Hours",
        "severity": "High",
        "condition": "Privileged account login between 22:00-06:00 CET on non-change-window days",
        "action": "Alert SOC analyst; require justification within 4 hours",
        "lastTriggered": "2025-01-06T03:15:00Z"
      },
      {
        "ruleId": "ALR-DATA-001",
        "name": "Large Data Transfer to External Destination",
        "severity": "Critical",
        "condition": "Outbound data transfer >500MB to non-whitelisted destination",
        "action": "Alert SOC analyst immediately; auto-block if confidence >80%",
        "lastTriggered": "2024-12-19T11:42:00Z"
      },
      {
        "ruleId": "ALR-NET-001",
        "name": "Anomalous Network Traffic Pattern",
        "severity": "Medium",
        "condition": "Darktrace model breach score >75% for any device",
        "action": "Alert SOC analyst; initiate investigation workflow",
        "lastTriggered": "2025-01-09T08:55:00Z"
      }
    ]
  },
  "detectionCoverage": {
    "overallCoveragePercent": 87.5,
    "byZone": {
      "production": 95.0,
      "dmz": 92.0,
      "management": 88.0,
      "user": 82.0,
      "development": 68.0
    },
    "knownGaps": [
      "Cloud-native services (AWS Lambda, API Gateway) — partial log integration",
      "Development environment — limited monitoring coverage",
      "IoT devices (building management) — not integrated with SIEM"
    ]
  },
  "singlePointsOfFailureMonitored": true,
  "spofMonitoringDetails": [
    {
      "spofId": "SPOF-001",
      "description": "SWIFT Alliance Gateway",
      "monitoringMethod": "Heartbeat check every 30 seconds; transaction throughput monitoring",
      "alertThreshold": "No heartbeat for 2 minutes or throughput drop >50%"
    },
    {
      "spofId": "SPOF-002",
      "description": "SAN Storage Infrastructure",
      "monitoringMethod": "SNMP monitoring of disk health, I/O latency, and replication status",
      "alertThreshold": "Disk failure, I/O latency >50ms, or replication lag >5 minutes"
    }
  ]
}

Expected Structured Facts

Example structured facts that Detrixa would extract from this evidence (synthetic data, deterministic seed).

ict_detection_capabilities_status — fs-ict-detection-capabilities
{
  "factId": "c1d2e3f4-a5b6-7890-cdef-100000000011",
  "evidenceId": "a0b1c2d3-e4f5-6789-abcd-100000000011",
  "evidenceClassId": "ict-detection-capabilities",
  "factType": "ict_detection_capabilities_status",
  "data": {
    "assessment_date": "2025-01-10",
    "has_anomaly_detection": true,
    "has_siem": true,
    "monitoring_coverage_percent": 87.5,
    "single_points_of_failure_monitored": true,
    "alert_rules_count": 342,
    "mean_time_to_detect_hours": 2.3
  },
  "provenance": "deterministic",
  "extractorVersion": "dora-test-generator/0.1.0",
  "extractedAt": "2025-01-15T09:00:00Z",
  "supersededBy": null
}

ICT Detection Capabilities Summary RARE

Plain text summary of the institution's detection capabilities, including coverage assessment, detection gaps, and improvement roadmap.

Formats
PLAIN_TEXT
Evidence Class
ict-detection-capabilities
Availability
RARE
Update Frequency
annual
Typical Author
SOC Manager
Approval Chain
SOC Manager → CISO

Content Sections

Expected Fields

Common Quality Issues

View Example

Generated example artifact using the default institution profile (COMMON availability, synthetic data only).

PLAIN_TEXT — Inline Preview
ICT DETECTION CAPABILITIES SUMMARY
Nordvik Bank AG
Assessment Date: 10 January 2025
Prepared by: SOC Manager (Katrin Halvorsen, CISO oversight)
Next Assessment: 10 January 2026
Classification: Internal — Restricted

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

DETECTION CAPABILITY OVERVIEW

Nordvik Bank AG operates a multi-layered detection capability designed to identify
anomalous activities, ICT-related incidents, and potential material single points
of failure in accordance with DORA Article 10.

The detection architecture comprises five integrated components:

  1. SIEM Platform (Splunk Enterprise 9.2.1)
     — Centralised log collection from 47 sources across all security zones
     — 342 active correlation rules covering 10 threat categories
     — Real-time alerting with automated triage via SOAR integration
     — Average event ingestion: 12,500 events per second

  2. Endpoint Detection and Response (CrowdStrike Falcon 7.10)
     — Deployed on 1,389 endpoints (servers and workstations)
     — Behavioural analysis with machine learning-based threat detection
     — Automated containment for high-confidence malware detections
     — Coverage: 98% of managed endpoints

  3. Network Anomaly Detection (Darktrace Enterprise 6.1)
     — Unsupervised machine learning monitoring all five network zones
     — Self-learning baseline of normal network behaviour
     — Real-time detection of lateral movement, C2 communication, and
       data exfiltration patterns
     — Integration with SIEM for correlated alerting

  4. Vulnerability Management (Qualys VMDR)
     — Continuous vulnerability scanning of 1,247 assets
     — Weekly external scans, monthly internal scans
     — Automated prioritisation based on asset criticality and exploit
       availability

  5. Security Orchestration (Palo Alto Cortex XSOAR 8.5)
     — 28 automated playbooks for common alert types
     — Automated enrichment of alerts with threat intelligence
     — Mean time to triage reduction: 65% since deployment

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

COVERAGE ASSESSMENT

Overall Detection Coverage: 87.5%

Coverage by Security Zone:

  Zone              Coverage    Assessment
  ─────────────────────────────────────────────────────────────────────────────
  Production         95.0%      Strong — all critical systems fully monitored
                                with real-time alerting and automated response
  DMZ                92.0%      Strong — web application firewall, IDS/IPS,
                                and full packet capture active
  Management         88.0%      Adequate — privileged access monitoring and
                                configuration change detection active
  User               82.0%      Adequate — EDR coverage good; email security
                                gateway and DLP active; some gaps in cloud
                                application monitoring
  Development        68.0%      Below target — limited monitoring; reliance
                                on network-level detection only

Coverage by Threat Category (MITRE ATT&CK alignment):

  Tactic                  Coverage    Key Detection Methods
  ─────────────────────────────────────────────────────────────────────────────
  Initial Access           85%        Email gateway, WAF, IDS/IPS
  Execution                80%        EDR behavioural analysis, SIEM rules
  Persistence              75%        EDR, configuration monitoring
  Privilege Escalation     82%        PAM monitoring, SIEM correlation
  Defence Evasion          70%        EDR, Darktrace anomaly detection
  Credential Access        88%        PAM, authentication monitoring
  Discovery                72%        Darktrace, SIEM network rules
  Lateral Movement         78%        Darktrace, network segmentation alerts
  Collection               75%        DLP, SIEM data access rules
  Exfiltration             80%        DLP, Darktrace, proxy monitoring
  Command and Control      82%        DNS monitoring, Darktrace, IDS/IPS
  Impact                   85%        System availability monitoring, EDR

Mean Time to Detect (MTTD): 2.3 hours (target: <4 hours)
Mean Time to Respond (MTTR): 4.1 hours (target: <8 hours)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

KNOWN GAPS

Gap ID   Area                          Severity   Description
─────────────────────────────────────────────────────────────────────────────────
GAP-001  Cloud-Native Services          Medium     AWS Lambda functions and API
                                                   Gateway logs partially integrated
                                                   with SIEM. Serverless execution
                                                   events not fully captured.

GAP-002  Development Environment         Low       Development zone has network-level
                                                   monitoring only. No EDR or SIEM
                                                   agent deployment on dev servers.

GAP-003  IoT/Building Management         Low       Building management system (HVAC,
                                                   physical access) not integrated
                                                   with SIEM. Separate monitoring by
                                                   facilities team.

GAP-004  Encrypted Traffic Inspection    Medium     East-west encrypted traffic within
                                                   the production zone is not subject
                                                   to TLS inspection. Relies on
                                                   endpoint-level detection.

GAP-005  User Behaviour Analytics        Medium     No dedicated UEBA solution for
                                                   detecting insider threats based on
                                                   behavioural patterns. Current
                                                   detection relies on rule-based
                                                   SIEM alerts.

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

IMPROVEMENT ROADMAP

  Priority   Initiative                          Target Date   Budget (CHF)
  ─────────────────────────────────────────────────────────────────────────────
  High       Complete AWS CloudTrail and          Q1 2025       45,000
             Lambda log integration with SIEM

  High       Deploy UEBA solution for insider     Q2 2025       180,000
             threat detection (Exabeam or
             Microsoft Sentinel UEBA module)

  Medium     Implement TLS inspection for         Q2 2025       75,000
             east-west production traffic

  Medium     Extend EDR deployment to             Q1 2025       15,000
             development environment

  Low        Integrate building management         Q3 2025       25,000
             system alerts with SIEM

  Low        Implement MITRE ATT&CK-based         Q2 2025       —
             detection coverage mapping and
             gap analysis (internal effort)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Assessment conducted by: SOC Manager
Reviewed by: Katrin Halvorsen, CISO
Date: 10 January 2025

Expected Structured Facts

Example structured facts that Detrixa would extract from this evidence (synthetic data, deterministic seed).

ict_detection_capabilities_status — fs-ict-detection-capabilities
{
  "factId": "c1d2e3f4-a5b6-7890-cdef-100000000011",
  "evidenceId": "a0b1c2d3-e4f5-6789-abcd-100000000011",
  "evidenceClassId": "ict-detection-capabilities",
  "factType": "ict_detection_capabilities_status",
  "data": {
    "assessment_date": "2025-01-10",
    "has_anomaly_detection": true,
    "has_siem": true,
    "monitoring_coverage_percent": 87.5,
    "single_points_of_failure_monitored": true,
    "alert_rules_count": 342,
    "mean_time_to_detect_hours": 2.3
  },
  "provenance": "deterministic",
  "extractorVersion": "dora-test-generator/0.1.0",
  "extractedAt": "2025-01-15T09:00:00Z",
  "supersededBy": null
}

Fact Schemas

ict_detection_capabilities_status

Schema ID
fs-ict-detection-capabilities
Control
DORA-Art10-P1

Valid Ranges

assessment_date
within last 12 months
monitoring_coverage_percent
above 80% for adequate coverage

Related Schemas

JSON Schema

{
  "properties": {
    "alert_rules_count": {
      "minimum": 0,
      "type": "integer"
    },
    "assessment_date": {
      "format": "date",
      "type": "string"
    },
    "has_anomaly_detection": {
      "type": "boolean"
    },
    "has_siem": {
      "type": "boolean"
    },
    "mean_time_to_detect_hours": {
      "minimum": 0,
      "type": "number"
    },
    "monitoring_coverage_percent": {
      "maximum": 100,
      "minimum": 0,
      "type": "number"
    },
    "single_points_of_failure_monitored": {
      "type": "boolean"
    }
  },
  "required": [
    "assessment_date",
    "has_anomaly_detection",
    "has_siem",
    "monitoring_coverage_percent"
  ],
  "type": "object"
}